Q4 2026 Braze Inc Earnings Call

March 24, 2026

Speaker #1: During this call, we will make statements related to our business that are forward-looking under federal securities laws and the Safe Harbor provisions of the Private Securities Litigation Reform Act of 1995.

Christopher Ferris: During this call, we will make statements related to our business that are forward-looking under federal securities laws and the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. These statements include, but are not limited to, statements regarding our financial outlook for Q1 and the fiscal year ended 31 January 2027, the anticipated benefits from and product advancements due to the combination of Braze and ongoing developments in BrazeAI technology, our expectations concerning new customer verticals, our anticipated customer behaviors, including vendor consolidation and replacement trends and their impact on Braze, our potential market opportunity and our ability to effectively execute on such opportunity, the execution and anticipated benefits of our share repurchase program, and our long-term financial targets and goals, including our expectations regarding our profitability framework.

Chris Ferris: During this call, we will make statements related to our business that are forward-looking under federal securities laws and the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. These statements include, but are not limited to, statements regarding our financial outlook for Q1 and the fiscal year ended 31 January 2027, the anticipated benefits from and product advancements due to the combination of Braze and ongoing developments in BrazeAI technology, our expectations concerning new customer verticals, our anticipated customer behaviors, including vendor consolidation and replacement trends and their impact on Braze, our potential market opportunity and our ability to effectively execute on such opportunity, the execution and anticipated benefits of our share repurchase program, and our long-term financial targets and goals, including our expectations regarding our profitability framework.

Speaker #1: These statements include, but are not limited to: statements regarding our financial outlook for the first quarter and the fiscal year ended January 31, 2027, the anticipated benefits from and product advancements due to the combination of Braze and ongoing developments in Braze AI technology, our expectations concerning new customer verticals, our anticipated customer behaviors including vendor consolidation and replacement trends and their impact on Braze, our potential market opportunity, and our ability to effectively execute on such opportunity, the execution and anticipated benefits of our share repurchase program, and our long-term financial targets and goals, including our expectations regarding our profitability framework.

Speaker #1: These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations and reflect our views only as of today.

Christopher Ferris: These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations and reflect our views only as of today. We assume no obligation to update any such forward-looking statements. For a discussion of material risks and uncertainties that could affect our actual results, please refer to the risks identified in today's press release and our SEC filings, both available on the investor relations section of our website. I'd also like to remind you that today's call will include certain non-GAAP financial measures used by management to evaluate our ongoing operations and to aid investors in further understanding the company's fiscal Q4 2026 performance, in addition to the impact these items have on the financial results.

Chris Ferris: These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations and reflect our views only as of today. We assume no obligation to update any such forward-looking statements. For a discussion of material risks and uncertainties that could affect our actual results, please refer to the risks identified in today's press release and our SEC filings, both available on the investor relations section of our website. I'd also like to remind you that today's call will include certain non-GAAP financial measures used by management to evaluate our ongoing operations and to aid investors in further understanding the company's fiscal Q4 2026 performance, in addition to the impact these items have on the financial results.

Speaker #1: We assume no obligation to update any such forward-looking statements. For discussion of material risks and uncertainties that could affect our actual results, please refer to the risks identified in today's press release and our SEC filings, both available on the Investor Relations section of our website.

Speaker #1: I'd also like to remind you that today's calls will include certain non-GAAP financial measures used by management to evaluate our ongoing operations and to aid investors in further understanding the company's fiscal fourth quarter 2026 performance, in addition to the impact these items have on the financial results.

Speaker #1: Please refer to the reconciliations of our non-GAAP financial measures to the most directly comparable financial measures calculated in accordance with US GAAP, included in our earnings release under the Investor Relations section. Financial measures provided should not be considered as a substitute for, or superior to, the financial measures of financial performance prepared in accordance with US GAAP. And now, I'd like to turn the call over to Bill.

Christopher Ferris: Please refer to the reconciliations of our non-GAAP financial measures to the most directly comparable financial measures calculated in accordance with U.S. GAAP included in our earnings release under the investor relations section of our website. The non-GAAP financial measures provided should not be considered as a substitute for or superior to the financial measures of financial performance prepared in accordance with U.S. GAAP. Now I'd like to turn the call over to Bill.

Chris Ferris: Please refer to the reconciliations of our non-GAAP financial measures to the most directly comparable financial measures calculated in accordance with U.S. GAAP included in our earnings release under the investor relations section of our website. The non-GAAP financial measures provided should not be considered as a substitute for or superior to the financial measures of financial performance prepared in accordance with U.S. GAAP. Now I'd like to turn the call over to Bill.

Speaker #2: Thank you, Chris, and good afternoon, everyone. Today, we reported outstanding fourth quarter results that further validate our product leadership, go-to-market approach, and financial strategy.

William Magnuson: Thank you, Chris, and good afternoon, everyone. Today, we reported outstanding Q4 results that further validate our product leadership, go-to-market approach, and financial strategy. In Q4, we generated $205 million of revenue, up 28% year over year and 8% from the prior quarter. Organic revenue growth accelerated year over year for the third straight quarter, while we continued to drive operating efficiency in our business. Trailing 12-month dollar-based net retention showed strength as well, inflecting positively during the quarter to reach 109%. Two milestones underscored this momentum in our business. During the quarter, we surpassed $1 billion in remaining performance obligations as customers increasingly commit to Braze for their long-term customer engagement needs.

Bill Magnuson: Thank you, Chris, and good afternoon, everyone. Today, we reported outstanding Q4 results that further validate our product leadership, go-to-market approach, and financial strategy. In Q4, we generated $205 million of revenue, up 28% year over year and 8% from the prior quarter. Organic revenue growth accelerated year over year for the third straight quarter, while we continued to drive operating efficiency in our business. Trailing 12-month dollar-based net retention showed strength as well, inflecting positively during the quarter to reach 109%. Two milestones underscored this momentum in our business. During the quarter, we surpassed $1 billion in remaining performance obligations as customers increasingly commit to Braze for their long-term customer engagement needs.

Speaker #2: In Q4, we generated $205 million of revenue, up 28% year over year and 8% from the prior quarter. Organic revenue growth accelerated year over year for the third straight quarter, but we continued to drive operating efficiency in our business.

Speaker #2: Trailing 12-month dollar-based net retention showed strength as well, inflecting positively during the quarter to reach $109%. Two milestones underscored this momentum in our business.

Speaker #2: During the quarter, we surpassed $1 billion in remaining performance obligations, as customers increasingly commit to Braze for their long-term customer engagement needs. Early in fiscal 2027, we passed $800 million in annual recurring revenue, demonstrating continued strong demand for the high ROI delivered by our platform.

William Magnuson: Early in fiscal 2027, we passed $800 million in annual recurring revenue, demonstrating continued strong demand for the high ROI delivered by our platform. We are incredibly proud of these achievements, and I thank our team across the world for their tireless efforts over the past year. For the full fiscal year 2026, we delivered 24% year-over-year revenue growth and $28 million of non-GAAP operating income, with operating margins expanding nearly 400 basis points over the prior year. This performance demonstrates our ability to deliver on our profitability framework, even while accelerating our investments in Braze AI and completing the successful transformation of last summer's acquisition of OfferFit into the rapidly growing Braze Decisioning Studio.

Bill Magnuson: Early in fiscal 2027, we passed $800 million in annual recurring revenue, demonstrating continued strong demand for the high ROI delivered by our platform. We are incredibly proud of these achievements, and I thank our team across the world for their tireless efforts over the past year. For the full fiscal year 2026, we delivered 24% year-over-year revenue growth and $28 million of non-GAAP operating income, with operating margins expanding nearly 400 basis points over the prior year. This performance demonstrates our ability to deliver on our profitability framework, even while accelerating our investments in Braze AI and completing the successful transformation of last summer's acquisition of OfferFit into the rapidly growing Braze Decisioning Studio.

Speaker #2: We are incredibly proud of these achievements, and I thank our team across the world for their tireless efforts over the past year. For the full fiscal year 2026, we delivered 24% year-over-year revenue growth and $28 million of non-GAAP operating income, with operating margins expanding nearly 400 basis points over the prior year.

Speaker #2: This performance demonstrates our ability to deliver on our profitability framework, even while accelerating our investments in Braze AI and completing the successful transformation of last summer's acquisition of OfferFit into the rapidly growing Braze Decisioning Studio.

Speaker #2: We also realized $42 million of non-GAAP net income in FY26, up from $18 million last year, and generated $58 million of free cash flow, providing us with financial flexibility to invest thoughtfully in shaping the future of customer engagement.

William Magnuson: We also realized $42 million of non-GAAP net income in FY 2026, up from $18 million last year, and generated $58 million free cash flow, providing us with the financial flexibility to invest thoughtfully in shaping the future of customer engagement. Our financial strength has also enabled Braze to initiate its first share repurchase program, a milestone that reflects our high conviction in our long-term growth opportunity. Isabelle will provide more details on this program later in the call. Our business momentum accelerated in Q4 as brands look to transform their businesses with AI and further leverage their ongoing investments in first-party data and direct-to-consumer relationships. Q4 bookings rose over 50% year over year as we established a new high water mark for average sales price and saw particular strength in the enterprise.

Bill Magnuson: We also realized $42 million of non-GAAP net income in FY 2026, up from $18 million last year, and generated $58 million free cash flow, providing us with the financial flexibility to invest thoughtfully in shaping the future of customer engagement. Our financial strength has also enabled Braze to initiate its first share repurchase program, a milestone that reflects our high conviction in our long-term growth opportunity. Isabelle will provide more details on this program later in the call. Our business momentum accelerated in Q4 as brands look to transform their businesses with AI and further leverage their ongoing investments in first-party data and direct-to-consumer relationships. Q4 bookings rose over 50% year over year as we established a new high water mark for average sales price and saw particular strength in the enterprise.

Speaker #2: Our financial strength has also enabled Braze to initiate its first share repurchase program, a milestone that reflects our high conviction in our long-term growth opportunity.

Speaker #2: Isabelle will provide more details on this program later in the call. Our business momentum accelerated in the fourth quarter, as brands looked to transform their businesses with AI and further leverage their ongoing investments in first-party data and direct-to-consumer relationships.

Speaker #2: Q4 bookings rose over 50% year over year, as we established a new high watermark for average sales price and saw particular strength in the enterprise.

Speaker #2: Net customer additions increased by 81 sequentially, up 14% year over year, while 500,000-plus customers increased by 30 sequentially, up 35% year over year. Additionally, million-dollar-plus customers rose 28% year over year, up from 18% year-over-year growth in Q4 of last year.

William Magnuson: Net customer additions increased by 81 sequentially, up 14% year over year, while $500,000-plus customers increased by 30 sequentially, up 35% year over year. Additionally, $1 million-plus customers rose 28% year over year, up from 18% year over year growth in Q4 of last year. Large deal velocity was also impressive as we signed 29 deals in excess of $500,000 this quarter, including seven $1 million-plus deals and an expansion that increased our eight-figure customer count to 4. Notable new business wins and existing customer expansions include Dis-Chem, Goodnotes, ID.me, King, Life360, Mytheresa, PowerUs, Realestate.co.nz, Shell Mobility and Convenience, and ThriftBooks, along with many others. While new logo wins were strong, upsells also showed strength as existing customers expanded across channels, adopted new BrazeAI capabilities, and deepened their integrations with the Braze Data Platform.

Bill Magnuson: Net customer additions increased by 81 sequentially, up 14% year over year, while $500,000-plus customers increased by 30 sequentially, up 35% year over year. Additionally, $1 million-plus customers rose 28% year over year, up from 18% year over year growth in Q4 of last year. Large deal velocity was also impressive as we signed 29 deals in excess of $500,000 this quarter, including seven $1 million-plus deals and an expansion that increased our eight-figure customer count to 4. Notable new business wins and existing customer expansions include Dis-Chem, Goodnotes, ID.me, King, Life360, Mytheresa, PowerUs, Realestate.co.nz, Shell Mobility and Convenience, and ThriftBooks, along with many others. While new logo wins were strong, upsells also showed strength as existing customers expanded across channels, adopted new BrazeAI capabilities, and deepened their integrations with the Braze Data Platform.

Speaker #2: Large deal velocity was also impressive, as we signed 29 deals in excess of $500,000 this quarter, including $7 million-plus deals and an expansion that increased our eight-figure customer count to four.

Speaker #2: Notable new business wins and existing customer expansions include Discem, GoodNotes, ID.me, King, Live360, MyTeresa, PowerUs, realestate.co.nz, Shell Mobility & Convenience, and ThriftBooks, along with many others.

Speaker #2: While new logo wins were strong, upsells also showed strength, as existing customers expanded across channels, adopted new Braze AI capabilities, and deepened their integrations with the Braze data platform.

Speaker #2: This expansion of our land-and-expand strategy to include growth in data integrations and AI workloads is a testament to both Braze's composable design and our position as mission-critical infrastructure for our diverse and demanding global customer base.

William Magnuson: This expansion of our land and expand strategy to include growth in data integrations and AI workloads is a testament to both Braze's composable design and our position as mission-critical infrastructure for our diverse and demanding global customer base. Competitive takeaways from the legacy marketing clouds in Q4 continue to validate the market's preference for Braze's AI-driven omni-channel approach to deliver on modern customer engagement use cases at scale. This quarter, brands across diverse industries and geographies migrated from legacy platforms to Braze, including a global heritage footwear brand, a global genealogy company, a leading American cybersecurity company, an American department store chain, an American financial solutions company, a European travel insurance provider, a European national lottery, a luxury hotel group based in APAC, and a large Latin American bank. Looking ahead, we are well-positioned to capitalize on the momentum we've been building over the past several quarters.

Bill Magnuson: This expansion of our land and expand strategy to include growth in data integrations and AI workloads is a testament to both Braze's composable design and our position as mission-critical infrastructure for our diverse and demanding global customer base. Competitive takeaways from the legacy marketing clouds in Q4 continue to validate the market's preference for Braze's AI-driven omni-channel approach to deliver on modern customer engagement use cases at scale. This quarter, brands across diverse industries and geographies migrated from legacy platforms to Braze, including a global heritage footwear brand, a global genealogy company, a leading American cybersecurity company, an American department store chain, an American financial solutions company, a European travel insurance provider, a European national lottery, a luxury hotel group based in APAC, and a large Latin American bank. Looking ahead, we are well-positioned to capitalize on the momentum we've been building over the past several quarters.

Speaker #2: Competitive takeaways from the legacy marketing clouds in the fourth quarter continue to validate the market's preference for Braze's AI-driven, omnichannel approach to deliver on modern customer engagement use cases at scale.

Speaker #2: This quarter, brands across diverse industries and geographies migrated from legacy platforms to Braze, including a global heritage footwear brand, a global genealogy company, a leading American cybersecurity company, an American department store chain, an American financial solutions company, a European travel insurance provider, a European national lottery, a luxury hotel group based in APAC, and a large Latin American bank.

Speaker #2: Looking ahead, we are well positioned to capitalize on the momentum we've been building over the past several quarters. Our go-to-market motion, under the leadership of Chief Revenue Officer Ed McDonald, who joined in late Q2, is operating at a high level, delivering a meaningful improvement in sales productivity.

William Magnuson: Our go-to-market motion under the leadership of Chief Revenue Officer Ed McDonnell, who joined in late Q2, is operating at a high level, delivering a meaningful improvement in sales productivity. Pipeline generation was also strong in Q4, indicating robust market demand for our AI-driven solutions, particularly in the enterprise. The field of customer engagement is moving faster now than it has in years, and Braze continues to be perfectly positioned to turn AI disruption into opportunity. By driving platform innovation in tandem with the evolving craft of customer engagement, Braze has been actively redefining the front door to marketing technology for most of the last decade. This innovative leadership continues to drive share gain in the enterprise, and it's why both our customer community and broader partner ecosystem continue to compound with ambition and optimism.

Bill Magnuson: Our go-to-market motion under the leadership of Chief Revenue Officer Ed McDonnell, who joined in late Q2, is operating at a high level, delivering a meaningful improvement in sales productivity. Pipeline generation was also strong in Q4, indicating robust market demand for our AI-driven solutions, particularly in the enterprise. The field of customer engagement is moving faster now than it has in years, and Braze continues to be perfectly positioned to turn AI disruption into opportunity. By driving platform innovation in tandem with the evolving craft of customer engagement, Braze has been actively redefining the front door to marketing technology for most of the last decade. This innovative leadership continues to drive share gain in the enterprise, and it's why both our customer community and broader partner ecosystem continue to compound with ambition and optimism.

Speaker #2: Pipeline generation was also strong in the fourth quarter, indicating robust market demand for our AI-driven solutions, particularly in the enterprise. The field of customer engagement is moving faster now than it has in years, and Braze continues to be perfectly positioned to turn AI disruption into opportunity.

Speaker #2: By driving platform innovation in tandem with the evolving craft of customer engagement, Braze has been actively redefining the front door to marketing technology for most of the last decade.

Speaker #2: This innovative leadership continues to drive share gain in the enterprise, and it's why both our customer community and broader partner ecosystem continue to compound with ambition and optimism.

Speaker #2: Our competitive position rests on four foundational strengths that position us to capitalize on AI-driven disruption. First, the Braze data platform and customer engagement stack serve as critical infrastructure for our customers, delivering secure and reliable performance at massive scale.

William Magnuson: Our competitive position rests on four foundational strengths that position us to capitalize on AI-driven disruption. First, the Braze Data Platform and customer engagement stack serve as critical infrastructure for our customers, delivering secure and reliable performance at massive scale. Unlike applications that manage workflows and tasks that are ultimately executed by humans, Braze has always been a platform wielded by small teams of builders to directly execute massive, complex workloads. During calendar year 2025 alone, we powered 4.5 trillion messages in Canvas actions, processed over 25 trillion data points, executed 3.1 trillion AI decisioning inferences, and made 8.7 trillion updates to our user profile system of record. This execution capability provides brands with confidence to deploy business-critical programs for entire global audiences, confidence that no point solution can match.

Bill Magnuson: Our competitive position rests on four foundational strengths that position us to capitalize on AI-driven disruption. First, the Braze Data Platform and customer engagement stack serve as critical infrastructure for our customers, delivering secure and reliable performance at massive scale. Unlike applications that manage workflows and tasks that are ultimately executed by humans, Braze has always been a platform wielded by small teams of builders to directly execute massive, complex workloads. During calendar year 2025 alone, we powered 4.5 trillion messages in Canvas actions, processed over 25 trillion data points, executed 3.1 trillion AI decisioning inferences, and made 8.7 trillion updates to our user profile system of record. This execution capability provides brands with confidence to deploy business-critical programs for entire global audiences, confidence that no point solution can match.

Speaker #2: Unlike applications that manage workflows and tasks that are ultimately executed by humans, Braze has always been a platform wielded by small teams of builders to directly execute massive, complex workloads.

Speaker #2: During calendar year 2025 alone, we powered 4.5 trillion messages in Canvas actions, processed over 25 trillion data points, executed 3.1 trillion AI decisioning inferences, and made 8.7 trillion updates to our user profile system of record.

Speaker #2: This execution capability provides brands with confidence to deploy business-critical programs for entire global audiences—confidence that no point solution can match. Second, our vertically integrated data and decisioning architecture allows for capabilities that no one else can replicate.

William Magnuson: Second, our vertically integrated data and decisioning architecture allows for capabilities that no one else can replicate. The Braze Data Platform feeds real-time context into control planes like Canvas and Decisioning Studio, which then serve as a substrate for agentic AI execution. This tight integration between data infrastructure and AI decisioning, combined with the most comprehensive set of marketing, conversational, and product channels on the market, delivers differentiated outcomes rooted in real customer data, not just generic LLM outputs. Third, our composable AI architecture is compounding the value of our deep infrastructure and comprehensive platform. At our Forge customer conference in September, we announced the upcoming betas for both BrazeAI Operator and the Agent Console to be available in Q1 and Q2, respectively. Last month, we beat those delivery timelines by months and launched both Operator and Agent Console into general availability.

Bill Magnuson: Second, our vertically integrated data and decisioning architecture allows for capabilities that no one else can replicate. The Braze Data Platform feeds real-time context into control planes like Canvas and Decisioning Studio, which then serve as a substrate for agentic AI execution. This tight integration between data infrastructure and AI decisioning, combined with the most comprehensive set of marketing, conversational, and product channels on the market, delivers differentiated outcomes rooted in real customer data, not just generic LLM outputs. Third, our composable AI architecture is compounding the value of our deep infrastructure and comprehensive platform. At our Forge customer conference in September, we announced the upcoming betas for both BrazeAI Operator and the Agent Console to be available in Q1 and Q2, respectively. Last month, we beat those delivery timelines by months and launched both Operator and Agent Console into general availability.

Speaker #2: The Braze data platform feeds real-time context into control planes like Canvas and Decisioning Studio, which then serve as the substrate for agentic AI execution.

Speaker #2: This tight integration between data infrastructure and AI decisioning, combined with the most comprehensive set of marketing, conversational, and product channels on the market, delivers differentiated outcomes rooted in real customer data—not just generic LLM outputs.

Speaker #2: Third, our composable AI architecture is compounding the value of our deep infrastructure and comprehensive platform. At our FORGE customer conference in September, we announced the upcoming betas for both Braze AI Operator and the Agent Console to be available in Q1 and Q2, respectively.

Speaker #2: Last month, we beat those delivery timelines by months and launched both Operator and Agent Console into general availability, leveraging the flexibility of composable data and the power of composable intelligence.

William Magnuson: Leveraging the flexibility of composable data and the power of composable intelligence, these products have been able to quickly spread their wings and capability because they wield the differentiated power, performance, and scale that Braze has delivered to the market for years. The excitement from customers and partners around both launches has been palpable. Agent Console is seeing rapid uptake across a wide array of use cases, and BrazeAI Operator is accelerating and evolving workflows for thousands of Braze dashboard users every week, automating campaign, Canvas, and agent creation, deepening quality assurance checks, and uncovering data insights through simple conversational prompts.

Bill Magnuson: Leveraging the flexibility of composable data and the power of composable intelligence, these products have been able to quickly spread their wings and capability because they wield the differentiated power, performance, and scale that Braze has delivered to the market for years. The excitement from customers and partners around both launches has been palpable. Agent Console is seeing rapid uptake across a wide array of use cases, and BrazeAI Operator is accelerating and evolving workflows for thousands of Braze dashboard users every week, automating campaign, Canvas, and agent creation, deepening quality assurance checks, and uncovering data insights through simple conversational prompts.

Speaker #2: These products have been able to quickly spread their wings and capability because they wield the differentiated power, performance, and scale that Braze has delivered to the market for years.

Speaker #2: The excitement from customers and partners around both launches has been palpable. Agent Console is seeing rapid uptake across a wide array of use cases, and Braze AI Operator is accelerating and evolving workflows for thousands of Braze dashboard users every week—automating campaign, Canvas, and agent creation, deepening quality assurance checks, and uncovering data insights through simple conversational prompts.

Speaker #2: Operator is first trained with Braze's documentation, use case libraries, and source code, and then enhanced by a comprehensive knowledge of each customer's data models, brand strategy, and integration details.

William Magnuson: Operator is first trained with Braze's documentation, use case libraries, and source code, and then enhanced by a comprehensive knowledge of each customer's data models, brand strategy, and integration details, enabling each Braze user's operator to answer difficult questions and execute complex tasks as it navigates the dashboard in front of their eyes. Operator also integrates with Snowflake's Cortex code to drive analytics insights that feed back into campaign strategies, and its skills continue to advance rapidly, including the recently trained capability to build directly inside the Agent Console. While eager beta testers of the Agent Console repeatedly asked us for more templates, we leaped over their request for faster horses and instead delivered a powerful prompt-to-agent capability that turns simple inspiration into sophisticated agents, each specifically configured according to a customer's Braze integration and existing marketing programs.

Bill Magnuson: Operator is first trained with Braze's documentation, use case libraries, and source code, and then enhanced by a comprehensive knowledge of each customer's data models, brand strategy, and integration details, enabling each Braze user's operator to answer difficult questions and execute complex tasks as it navigates the dashboard in front of their eyes. Operator also integrates with Snowflake's Cortex code to drive analytics insights that feed back into campaign strategies, and its skills continue to advance rapidly, including the recently trained capability to build directly inside the Agent Console. While eager beta testers of the Agent Console repeatedly asked us for more templates, we leaped over their request for faster horses and instead delivered a powerful prompt-to-agent capability that turns simple inspiration into sophisticated agents, each specifically configured according to a customer's Braze integration and existing marketing programs.

Speaker #2: Enabling each Braze user's Operator to answer difficult questions and execute complex tasks as it navigates the dashboard in front of their eyes. Operator also integrates with Snowflake's Cortex Code to drive analytics insights that feed back into campaign strategies, and its skills continue to advance rapidly, including the recently trained capability to build directly inside the Agent Console.

Speaker #2: While eager beta testers of the Agent Console repeatedly asked us for more templates, we leaped over their request for faster horses and instead delivered a powerful prompt-to-agent capability that turned simple inspiration into sophisticated agents, each specifically configured according to a customer's Braze integration and existing marketing programs.

Speaker #2: These agents are already being deployed to enhance customer journeys in Canvas and to drive data enrichment workloads in the Braze data platform's Catalog feature.

William Magnuson: These agents are already being deployed to enhance customer journeys in Canvas and to drive data enrichment workloads in the Braze Data Platform's catalog feature. All of this works in tandem with BrazeAI Decisioning Studio, which harnesses modern reinforcement learning to achieve maximum performance in the most important parts of the user journey. Just as we delivered the most comprehensive solution for cross-channel marketing in the age of deterministic automation, we're building BrazeAI to combine the flexibility of a composable architecture with the power of frontier AI across multiple fields of research to deliver a comprehensive solution for AI-driven customer engagement. Fourth, we believe Braze occupies a unique position in the software landscape as a rare hybrid of a revenue-driving engine and mission-critical operational capability.

Bill Magnuson: These agents are already being deployed to enhance customer journeys in Canvas and to drive data enrichment workloads in the Braze Data Platform's catalog feature. All of this works in tandem with BrazeAI Decisioning Studio, which harnesses modern reinforcement learning to achieve maximum performance in the most important parts of the user journey. Just as we delivered the most comprehensive solution for cross-channel marketing in the age of deterministic automation, we're building BrazeAI to combine the flexibility of a composable architecture with the power of frontier AI across multiple fields of research to deliver a comprehensive solution for AI-driven customer engagement. Fourth, we believe Braze occupies a unique position in the software landscape as a rare hybrid of a revenue-driving engine and mission-critical operational capability.

Speaker #2: And all of this works in tandem with Braze AI Decisioning Studio, which harnesses modern reinforcement learning to achieve maximum performance in the most important parts of the user journey.

Speaker #2: Just as we delivered the most comprehensive solution for cross-channel marketing in the age of deterministic automation, we're building Braze AI to combine the flexibility of a composable architecture with the power of frontier AI across multiple fields of research to deliver a comprehensive solution for AI-driven customer engagement.

Speaker #2: Fourth, we believe Braze occupies a unique position in the software landscape as a rare hybrid of a revenue-driving engine and mission-critical operational capability. Whether it's the urgency of responding to an evolving emergency, the pressure of publishing a message that will be read by hundreds of millions of people, or the criticality of executing deeply optimized marketing programs that drive a business's most important quarterly results, brands trust Braze with their most important workloads because we provide the agility, observability, and reliability that business-critical infrastructure demands.

William Magnuson: Whether it's the urgency of responding to an evolving emergency, the pressure of publishing a message that will be read by hundreds of millions of people, or the criticality of executing deeply optimized marketing programs that drive a business's most important quarterly results, brands trust Braze with their most important workloads because we provide the agility, observability, and reliability that business-critical infrastructure demands. In an environment where companies must maximize every dollar of uplift, this proven ability to deliver measurable ROI at scale makes Braze an essential and highly optimized component of the modern enterprise stack, not a discretionary tool. As we look ahead, Braze will continue to invest with focus to remain at the frontier of consumer and technological change, turning disruption into opportunity as our customers transform their jobs, their businesses, and the experiences that they deliver to consumers.

Bill Magnuson: Whether it's the urgency of responding to an evolving emergency, the pressure of publishing a message that will be read by hundreds of millions of people, or the criticality of executing deeply optimized marketing programs that drive a business's most important quarterly results, brands trust Braze with their most important workloads because we provide the agility, observability, and reliability that business-critical infrastructure demands. In an environment where companies must maximize every dollar of uplift, this proven ability to deliver measurable ROI at scale makes Braze an essential and highly optimized component of the modern enterprise stack, not a discretionary tool. As we look ahead, Braze will continue to invest with focus to remain at the frontier of consumer and technological change, turning disruption into opportunity as our customers transform their jobs, their businesses, and the experiences that they deliver to consumers.

Speaker #2: In an environment where companies must maximize every dollar of uplift, this proven ability to deliver measurable ROI at scale makes Braze an essential and highly optimized component of the modern enterprise stack—not a discretionary tool.

Speaker #2: As we look ahead, Braze will continue to invest with focus to remain at the frontier of consumer and technological change, turning disruption into opportunity as our customers transform their jobs, their businesses, and the experiences that they deliver to consumers.

Speaker #2: We are rapidly advancing our platform and enhancing our global customer community to scale agentic use cases across marketing programs, customer conversations, product experiences, and data workloads, enabling brands to turn context into connection and achieve in the AI era what they have been striving for all along: stronger business performance built on durable customer relationships.

William Magnuson: We are rapidly advancing our platform and enhancing our global customer community to scale agentic use cases across marketing programs, customer conversations, product experiences, and data workloads, enabling brands to turn context into connection and achieve in the AI era what they have been striving for all along: stronger business performance built on durable customer relationships. I'll wrap my remarks by emphasizing what a great position we are in as we enter our next phase of growth in fiscal 2027 and beyond. Thank you for your interest and support. Now I'll turn the call over to Isabelle.

Bill Magnuson: We are rapidly advancing our platform and enhancing our global customer community to scale agentic use cases across marketing programs, customer conversations, product experiences, and data workloads, enabling brands to turn context into connection and achieve in the AI era what they have been striving for all along: stronger business performance built on durable customer relationships. I'll wrap my remarks by emphasizing what a great position we are in as we enter our next phase of growth in fiscal 2027 and beyond. Thank you for your interest and support. Now I'll turn the call over to Isabelle.

Speaker #2: I'll wrap my remarks by emphasizing what a great position we are in as we enter our next phase of growth in fiscal 2027 and beyond.

Speaker #2: Thank you for your interest and support, and now I'll turn the call over to Isabelle.

Speaker #1: Thank you, Bill, and thank you everyone for joining us today. We reported an outstanding fourth quarter, with revenue increasing 28% year over year to $205.2 million, driven by a combination of existing customer contract expansions, renewals, and new business.

Isabelle Winkles: Thank you, Bill, and thank you everyone for joining us today. We reported an outstanding Q4 with revenue increasing 28% year over year to $205.2 million, driven by a combination of existing customer contract expansions, renewals, and new business. BrazeAI Decisioning Studio, formerly known as OfferFit, contributed $5.7 million of revenue in the quarter. This implies an organic revenue growth rate of 24.3% year over year. We're excited to see continued strength from our core business as organic revenue growth accelerated for the third sequential quarter, and we realized robust bookings and strong demand signal for Decisioning Studio and our other AI products. As Bill mentioned, in February, BrazeAI Agent Console transitioned to general availability, and we're pleased to report immediate and persistent consumption of our Flexible Credits in its first month of release.

Speaker #1: Braze AI Decisioning Studio, formerly known as OfferFit, contributed $5.7 million of revenue in the quarter. This implies an organic revenue growth rate of 24.3% year over year.

Speaker #1: We're excited to see continued strength from our core business, as organic revenue growth accelerated for the third sequential quarter, and we realized robust bookings and strong demand signals for Decisioning Studio and our other AI products.

Speaker #1: As Bill mentioned, in February, Agent Console transitioned to general availability, and we're pleased to report immediate and persistent consumption of our flexible credits in its first month of release.

Speaker #1: In Q4, our total customer count increased 14% year over year to 2,609 customers as of January 31, up 313 from the same period last year and up 81 from the prior quarter.

Isabelle Winkles: In Q4, our total customer count increased 14% year over year to 2,609 customers as of 31 January, up 313 from the same period last year and up 81 from the prior quarter. Our total number of large customers, which we define as those spending at least $500,000 annually, grew 35% year over year to 333, and as of 31 January, contributed 64% to our total ARR. This compares to a 62% contribution as of the same quarter last year. As a reminder, a customer is counted when their service date is effective, not when a contract is signed. As such, some new logos won in the Q4 will appear in our customer count in the Q1 of fiscal 2027.

Speaker #1: Our total number of large customers, which we define as those spending at least $500,000 annually, grew 35% year over year to 333. And as of January 31, they contributed 64% to our total ARR.

Speaker #1: This compares to a 62% contribution as of the same quarter last year. As a reminder, a customer is counted when their service date is effective, not when a contract is signed.

Speaker #1: As such, some new logos won in the fourth quarter will appear in our customer count in the first quarter of fiscal 2027. Measured across all customers, dollar-based net retention was 109%, up from 108% in the third quarter of this year.

Isabelle Winkles: Measured across all customers, dollar-based net retention was 109%, up from 108% in Q3 this year. Dollar-based net retention for our large customers was 110%, in line with Q3 this year. Expansion was again broadly distributed across industries and geographic regions. Revenue outside the US contributed 45% to our total revenue in Q4, consistent with the prior quarter of this year and the prior year quarter. In Q4, our total remaining performance obligation was just over $1 billion, up 30% year-over-year and up 16% sequentially. Current RPO was $642 million, up 27% year-over-year and up 12% sequentially.

Speaker #1: Dollar-based net retention for our large customers was 110%, in line with the third quarter of this year. Expansion was again broadly distributed across industries and geographic regions.

Speaker #1: Revenue outside the U.S. contributed 45% to our total revenue in the fourth quarter, consistent with the prior quarter of this year and the prior year quarter.

Speaker #1: In the fourth quarter, our total remaining performance obligation was just over $1 billion, up 30% year over year and up 16% sequentially. Current RPO was $642 million, up 27% year over year and up 12% sequentially.

Speaker #1: The strong year-over-year growth in RPO and CRPO was driven by four factors: strong Q4 bookings, healthy Q4 renewals, a large quarter for available renewal dollars, and a small increase in overall duration of contracts.

Isabelle Winkles: The strong year-over-year growth in RPO and CRPO was driven by four factors. Strong Q4 bookings, healthy Q4 renewals, a large quarter for available renewal dollars, and a small increase in overall duration of contracts. Non-GAAP gross profit in the quarter was $138 million, representing a non-GAAP gross margin of 67.2%. This compares to a non-GAAP gross profit of $112 million and non-GAAP gross margin of 69.9% in the Q4 of last year. The decrease in year-over-year margin percentage was driven primarily by higher premium messaging volumes and hosting costs, partially offset by improved efficiencies in personnel costs. Non-GAAP sales and marketing expenses were $70 million, or 34% of revenue, compared to $60 million, or 37% of revenue in the prior year quarter.

Speaker #1: Non-GAAP gross profit in the quarter was $138 million, representing a non-GAAP gross margin of 67.2%. This compares to a non-GAAP gross profit of $112 million and non-GAAP gross margin of 69.9% in the fourth quarter of last year.

Speaker #1: The decrease in year-over-year margin percentage was driven primarily by higher premium messaging volumes and hosting costs, partially offset by improved efficiencies in personnel costs.

Speaker #1: Non-GAAP sales and marketing expenses were $70 million, or 34% of revenue, compared to $60 million, or 37% of revenue in the prior year quarter.

Speaker #1: While the dollar increase reflects our year-over-year investment in headcount cost to support our ongoing growth and global expansion, the improved efficiency reflects our disciplined approach to investment as we continue to scale and expand our go-to-market organization.

Isabelle Winkles: While the dollar increase reflects our year-over-year investment in headcount cost to support our ongoing growth and global expansion, the improved efficiency reflects our disciplined approach to investment as we continue to scale and expand our go-to-market organization. non-GAAP R&D expense was $29 million, or 14% of revenue, compared to $23 million, or 14% of revenue in the prior year quarter. The dollar increase was primarily driven by increased headcount cost to support the expansion of our existing offerings, as well as to develop new products and features to drive growth. Our R&D expenditures reflect our intentional, yet disciplined technology investment strategy and are in line with our long-term non-GAAP R&D percent of revenue targets of 13% to 15%.

Speaker #1: Non-GAAP R&D expense was $29 million, or 14% of revenue, compared to $23 million, or 14% of revenue, in the prior year quarter. The dollar increase was primarily driven by increased headcount costs to support the expansion of our existing offerings, as well as to develop new products and features to drive growth.

Speaker #1: Our R&D expenditures reflect our intentional yet disciplined technology investment strategy, and are in line with our long-term non-gap R&D percent of revenue targets of 13% to to 15%.

Speaker #1: Non-GAAP G&A expense was $25 million, or 12% of revenue, compared to $21 million, or 13% of revenue in the prior year quarter. The improved efficiency reflects increasing scale across public company expenses and the benefit of leveraging strategic locations for headcount expansion.

Isabelle Winkles: Non-GAAP G&A expense was $25 million, or 12% of revenue, compared to $21 million, or 13% of revenue in the prior year quarter. The improved efficiency reflects increasing scale across public company expenses and the benefit of leveraging strategic locations for headcount expansion. Non-GAAP operating income was $15 million, or 7% of revenue, compared to a non-GAAP operating income of $8 million, or 5% of revenue in the prior year quarter. Non-GAAP net income attributable to Braze shareholders in the quarter was $11 million, or $0.10 per share, compared to $12 million, or $0.12 per share in the prior year quarter. Non-GAAP net income was negatively impacted by a $5 million purchase accounting adjustment related to the deferred tax liability from OfferFit, the reinforcement learning engine company acquired in June of last year.

Speaker #1: Non-GAAP operating income was $15 million, or 7% of revenue, compared to non-GAAP operating income of $8 million, or 5% of revenue in the prior year quarter.

Speaker #1: Non-GAAP net income attributable to Braze shareholders in the quarter was $11 million, or $0.10 per share, compared to $12 million, or $0.12 per share, in the prior-year quarter.

Speaker #1: Non-GAAP net income was negatively impacted by a $5 million purchase accounting adjustment related to the deferred tax liability from OfferFit, the reinforcement learning engine company acquired in June of last year.

Speaker #1: Excluding this one-time adjustment, non-GAAP net income and earnings per share were $16 million and $0.15, respectively. Now, turning to the balance sheet and cash flow statement.

Isabelle Winkles: Excluding this one-time adjustment, non-GAAP net income and earnings per share were $16 million and $0.15, respectively. Now turning to the balance sheet and cash flow statement. We ended the quarter with approximately $416 million in cash equivalents, restricted cash, and marketable securities. Cash provided by operations during the quarter was $19 million, compared to cash provided by operations of $17 million in the prior year quarter. Including the cash impact of capitalized costs, free cash flow in the quarter was $14 million, compared to $15 million in the prior year quarter. As we have noted in the past, we expect our free cash flow to continue to fluctuate from quarter to quarter given the timing of customer and vendor payments.

Speaker #1: We ended the quarter with approximately $416 million in cash, cash equivalents, restricted cash, and marketable securities. Cash provided by operations during the quarter was $19 million, compared to cash provided by operations of $17 million in the prior year quarter.

Speaker #1: Including the cash impact of capitalized costs, free cash flow in the quarter was $14 million, compared to $15 million in the prior year quarter.

Speaker #1: And as we have noted in the past, we expect our free cash flow to continue to fluctuate from quarter to quarter, given the timing of customer and vendor payments.

Speaker #1: Before turning to guidance, I'd like to take a moment to highlight the board's $100 million share repurchase authorization. This authorization reflects our confidence in our fundamentals, outlook, and disciplined approach. We believe this share repurchase represents an efficient and meaningful way to drive shareholder value.

Isabelle Winkles: Before turning to guidance, I'd like to take a moment to highlight the board's $100 million share repurchase authorization. This authorization reflects our confidence in our fundamentals, outlook, and disciplined approach to capital allocation. We believe this share repurchase represents an efficient and meaningful way to drive shareholder value. As we noted in our earnings release today, the repurchase program includes a $50 million accelerated share repurchase transaction with respect to our stock, which we plan to enter into before the end of Q1. In addition, our guidance for share count and EPS includes only the estimated impact of the $50 million ASR.

Speaker #1: As we noted in our earnings release today, the repurchase program includes a $50 million accelerated share repurchase transaction with respect to our stock, which we plan to enter into before the end of the first quarter.

Speaker #1: In addition, our guidance for share count and EPS includes only the estimated impact of the $50 million ASR. For the first quarter of fiscal 2027, we expect revenue to be in the range of $204.5 million to $205.5 million, which represents a year-over-year growth rate of approximately 26% at the midpoint.

Isabelle Winkles: For Q1 of fiscal 2027, we expect revenue to be in the range of $204.5 to 205.5 million, which represents a year-over-year growth rate of approximately 26% at the midpoint. As a reminder, our Q1 contains 3 fewer days compared to the other three quarters of the year, which each contain 92 days. Q1 non-GAAP operating income is expected to be in the range of $10 to 11 million. At the midpoint, this implies a non-GAAP operating margin of approximately 5%. Q1 non-GAAP net income is expected to be $11 to 12 million, and Q1 non-GAAP net income per share in the range of $0.10 to $0.11, based on approximately 112 million weighted average diluted shares outstanding during the period.

Speaker #1: As a reminder, our first quarter contains three fewer days compared to the other three quarters of the year, which each contain 92 days. First quarter non-GAAP operating income is expected to be in the range of $10 million to $11 million.

Speaker #1: At the midpoint, this implies a non-GAAP operating margin of approximately 5%. First quarter non-GAAP net income is expected to be $11 to $12 million, and first quarter non-GAAP net income per share in the range of $0.10 to $0.11, based on approximately 112 million weighted average diluted shares outstanding during the period.

Speaker #1: For the full fiscal year 2027, we expect total revenue to be in the range of $884 million to $889 million, which represents a year-over-year growth rate of approximately 20% at the midpoint.

Isabelle Winkles: For the full fiscal year 2027, we expect total revenue to be in the range of $884 to 889 million, which represents a year-over-year growth rate of approximately 20% at the midpoint. Fiscal year 2027 non-GAAP operating income is expected to be in the range of $69 to 73 million. At the midpoint, this implies a non-GAAP operating margin of 8%, a more than 400 basis point improvement versus fiscal year 2026. Non-GAAP net income for the same period is expected to be in the range of $69 to 73 million, and net income per share is expected to be $0.61 to $0.65 per share based on a full year weighted average diluted share count of approximately 113 million shares. It's an exciting time at Braze.

Speaker #1: Fiscal year 2027 non-GAAP operating income is expected to be in the range of $69 million to $73 million. At the midpoint, this implies a non-GAAP operating margin of 8%, a more than 400 basis point improvement versus fiscal year 2026.

Speaker #1: Non-GAAP net income for the same period is expected to be in the range of $69 to $73 million. Net income per share is expected to be $0.61 to $0.65 per share, based on a full-year weighted average diluted share count of approximately 113 million shares.

Speaker #1: It's an exciting time at Braze. We remain committed to delivering industry-leading customer engagement solutions powered by AI as we continue executing against our long-term financial targets.

Isabelle Winkles: We remain committed to delivering industry-leading customer engagement solutions powered by AI as we continue executing against our long-term financial targets. With that, we'll now open the call for questions. Operator, please begin the Q&A.

Speaker #1: And with that, we'll now open the call for questions. Operator, please begin the Q&A.

Speaker #2: We will now begin Q&A. For today's session, we'll be utilizing the 'Raise Hand' feature.

Operator: We will now begin Q&A. For today's session, we'll be utilizing the raise hand feature. If you'd like to ask a question, simply click on the raise hand button at the bottom of your screen. Once you've been called on, please unmute yourself and begin to ask your question. Please limit to one question and one follow-up before jumping back in the queue. Thank you. We will now pause a moment to assemble the queue. Our first question will come from Ryan McWilliams with Wells Fargo. You may now unmute and ask your question.

Speaker #1: Feature . If you'd like to ask a question , simply click on the Raise hand button at the bottom of your screen . Once you've been called on , please unmute yourself and begin to ask your question .

Speaker #1: Please limit to one question and one follow-up before jumping back in the queue. Thank you. We will now pause a moment to assemble the queue. Our first question will come from Ryan McWilliams with Wells Fargo.

Speaker #1: You may now unmute and ask a question.

Speaker #2: Hey, thanks for taking the question. For Bill, great to see three straight quarters of organic revenue re-acceleration in the business.

Ryan McWilliams: Hey, thanks for taking the question. For Bill, great to see three straight quarters of organic revenue re-acceleration in the business. I know last year has benefited from some go-to-market changes along with moving past COVID era customer renewals. But how do you feel about the underlying growth trajectory of Braze from here? Like, has it improved more sustainably? I know it's early, but how do you envision AI layering in to support growth trends?

Speaker #2: I know last year has benefited from some go to market changes , along with moving past Covid era customer renewals . But how do you feel about the underlying growth trajectory of Braves from here ?

Speaker #2: Like , has it improved more sustainably ? And I know it's early , but how do you envision AI layering in to support growth trends ?

Speaker #3: Yeah , absolutely . Thanks , Ryan . And it's been a great , you know , back half of the year heading into Q4 .

William Magnuson: Yeah, absolutely. Thanks, Ryan, and it's been a great, you know, H2 heading into Q4. I think that the biggest difference in Q4 was also the differentiation of our AI roadmap, especially coming out of our Forge conference in September. It's clear that customers can see where we're going. They can see how our long-standing advantages are being made more accessible and more capable with further investments in Braze AI. That helped with both win rates and deal velocity in Q4, as a lot of the competitor FUD just didn't hold water against both our offering and our pace of new product delivery. We're also seeing stronger momentum with the partner ecosystem, including across both the global agency groups and the more focused regional players that are growing super fast through tight partnership with us.

Bill Magnuson: Yeah, absolutely. Thanks, Ryan, and it's been a great, you know, H2 heading into Q4. I think that the biggest difference in Q4 was also the differentiation of our AI roadmap, especially coming out of our Forge conference in September. It's clear that customers can see where we're going. They can see how our long-standing advantages are being made more accessible and more capable with further investments in Braze AI. That helped with both win rates and deal velocity in Q4, as a lot of the competitor FUD just didn't hold water against both our offering and our pace of new product delivery. We're also seeing stronger momentum with the partner ecosystem, including across both the global agency groups and the more focused regional players that are growing super fast through tight partnership with us.

Speaker #3: I think that the biggest difference in Q4 was also the differentiation of our AI roadmap, especially coming out of our FORWARD conference in September.

Speaker #3: It's clear that customers can see where we're going. They can see how our longstanding advantages are being made more accessible and more capable with further investments in AI.

Speaker #3: That helped with both win rates and deal velocity in Q4, as a lot of the competitor FUD just didn't hold water against both our offering and our pace of new product delivery.

Speaker #3: We're also seeing stronger momentum with the partner ecosystem, including across both the global agency groups and the more focused regional players that are growing super fast through tight partnership with us. And our global sales leaders are moving with high velocity.

William Magnuson: Ed, our global sales leaders are moving with high velocity. I think that when we look at it all coming together, you've got a robust product roadmap that's moving at pace. There's really exciting AI innovation that's not only bringing new capability, but it's also making our existing capability more accessible and more leverageable by our customer base. You know, we're out in front with that R&D advantage also being combined with a, you know, pricing model that's always been consumption-based with a global go-to-market organization that operates in all the world's major markets. You know, a global customer community that has always been the world's most ambitious and creative marketers who have been on the leading edge of, you know, rapidly building with Braze from the beginning.

Bill Magnuson: Ed, our global sales leaders are moving with high velocity. I think that when we look at it all coming together, you've got a robust product roadmap that's moving at pace. There's really exciting AI innovation that's not only bringing new capability, but it's also making our existing capability more accessible and more leverageable by our customer base. You know, we're out in front with that R&D advantage also being combined with a, you know, pricing model that's always been consumption-based with a global go-to-market organization that operates in all the world's major markets. You know, a global customer community that has always been the world's most ambitious and creative marketers who have been on the leading edge of, you know, rapidly building with Braze from the beginning.

Speaker #3: And so, I think that when we look at it all coming together, you've got a robust product roadmap that's moving at pace.

Speaker #3: There's really exciting AI innovation that's not only bringing new capability , but it's also making our existing capability more accessible and more leverageable by our customer base .

Speaker #3: And , you know , we're we're out in front with that R&D advantage . Also being combined with a , you know , pricing model that's always been consumption based with a global go to market organization that operates in all the world's major markets .

Speaker #3: And, you know, a global customer community that has always been the world's most ambitious and creative marketers, who have been on the leading edge of.

Speaker #3: Rapidly building with braze from the beginning . And so I think that this is just a great moment for all of our existing scale , performance and innovation advantages to come together .

William Magnuson: I think that this is just a great moment for all of our existing scale, performance, and innovation advantages to come together, and we're excited for this year.

Bill Magnuson: I think that this is just a great moment for all of our existing scale, performance, and innovation advantages to come together, and we're excited for this year.

Speaker #3: And we're excited for this year .

Ryan McWilliams: Really appreciate the color there. For Isabelle, it seems like the initial full year revenue guide is slightly stronger than past years. Love to hear if any change to guidance philosophy here, and what were some of the key points that helped you build up to the full year guide?

Speaker #2: Really appreciate the color there . And then for Isabel , it seems like the initial full year revenue guide is slightly stronger than last years .

Speaker #2: Love to hear if any changes to the guidance philosophy here . And what were some of the key points that helped you build up to the full year guide

Isabelle Winkles: Yes, thanks for the question. First of all, no change in the guidance philosophy. Really excited about the momentum that we saw in the business, you know, coming into Q4, coming out of Q4 in particular. As you know, Bill mentioned, across a number of different dimensions. You know, we're seeing more two-year contracts. We're seeing larger in-quarter contract sizes. Upsells continue to be really strong. There's real excitement around our AI capabilities, as Bill mentioned. Ongoing strength in the enterprise, ongoing strength in the Americas, which has been something we've been working on. You know, there's just a lot of momentum across a number of different dimensions.

Speaker #3: Yeah , thanks for the question . So first of all , no change in the guidance philosophy . Really excited about the momentum that we saw in the business .

Speaker #3: You know, coming into Q4, coming out of Q4 in particular, as you know, Bill mentioned across a number of different dimensions.

Speaker #3: You know , we're seeing more two year contracts . We're seeing larger in in deals in quarter contract sizes , upsells continue to be really strong .

Speaker #3: There's real excitement around our AI capabilities as Bill mentioned , ongoing strength in the enterprise , ongoing strength in the Americas , which has been something we've been working on .

Speaker #3: And so , you know , there's just a lot of momentum across a number of different dimensions I think , as we mentioned , bringing Ed on in the middle of last year , he has been furthering our efforts across a number of different things that we have already put into motion , and it's been really great to see some of that success across Verticalization .

Isabelle Winkles: I think as we mentioned, bringing Ed on, in the middle of last year, he has been furthering our efforts across a number of different things that we have already put into motion. It's been really great to see some of that success, across verticalization. Really excited for that. You're seeing that in our guide, and we're really comfortable with how we've guided for the year.

Speaker #3: So, really excited for that. And you're seeing that in our guide, and we're really comfortable with how we've guided for the year.

Operator: Our next question will come from Scott Berg with Needham.

Speaker #1: Our next question will come from Scott Berg with Needham.

Scott Berg: Hi, everyone. Really nice quarter, and my apologies, I'm in an airport in case there's background noise. The first question I wanted to ask was off of a channel check or a customer conversation, I guess that we had during the quarter. We got to speak with one of your largest customers, and they noted to us that they had an internal project that spanned 18 months and over $10 million in costs to try to actually replace their entire Braze deployment at this well-known brand. They killed the project because they were only able to achieve about a third of your functionality even after an 18-month timeframe.

Speaker #4: Hi everyone . Really nice quarter . And my apologies . I'm in an airport in case there's background noise But first question , I wanted to ask was off of a channel check or a customer conversation .

Speaker #4: I guess , that we had during the quarter . We got to speak with one of your largest customers , and they noted to us that they had had an internal project that spanned 18 months and over $10 million in costs to try to actually replace their entire lives at deployment at this at this well-known brand .

Speaker #4: But they killed the project because they were only able to achieve about a third of your functionality, even after an 18-month time frame.

Scott Berg: I guess, Bill, as you think about a customer in this situation that might want to, you know, custom code their own platform with one of these GenAI LLM models, what's most difficult to replace at the end of the day, that makes, you know, a customer's approach to this probably not feasible over time?

Speaker #4: I guess Bill , if you think about a customer in this situation , that might want to try to , you know , custom code their own platform with one of these AI ML models .

Speaker #4: What's most difficult to replace at the end of the day That makes , you know , a customer's approach . This probably not not feasible over time

William Magnuson: Yeah, I touched on this in the prepared remarks, but I think that the meat of this answer lies in the combined requirement of, one, a tightly integrated high-performance infrastructure that encapsulates both the context and the intelligence layers, two, the comprehensiveness required to handle both the vastness of the modern enterprise data landscape on the ingestion side, and then the complexity of customer journeys on the output or the interaction side. Within Braze, the Braze Data Platform is the dedicated context layer, and Canvas provides the control plane. They work together to engineer the context that the agent console and other BrazeAI capabilities harness to drive higher performing personalization and orchestration decisions.

Bill Magnuson: Yeah, I touched on this in the prepared remarks, but I think that the meat of this answer lies in the combined requirement of, one, a tightly integrated high-performance infrastructure that encapsulates both the context and the intelligence layers, two, the comprehensiveness required to handle both the vastness of the modern enterprise data landscape on the ingestion side, and then the complexity of customer journeys on the output or the interaction side. Within Braze, the Braze Data Platform is the dedicated context layer, and Canvas provides the control plane. They work together to engineer the context that the agent console and other BrazeAI capabilities harness to drive higher performing personalization and orchestration decisions.

Speaker #3: Yeah , I touched on this in the prepared remarks , but I think that the meat of this answer lies in the combined requirement of one , a tightly integrated , high performance infrastructure that encapsulates both the context and the intelligence layers .

Speaker #3: And two , the comprehensiveness required to handle both the vastness of the modern enterprise data landscape on the ingestion side , and then the complexity of customer journeys on the output or the interaction side within the braised data platform is the dedicated context layer , and canvas provides the control plane They work together to engineer the context that the agent console and other AI capabilities harness to drive higher performing personalization and orchestration decisions for B2C audiences , which of course , is where we primarily work .

William Magnuson: For B2C audiences, which of course is where we primarily work, this has to happen at massive scale, and performance needs to be able to drive real-time interaction across an ever-growing set of channels and direct-to-consumer product interfaces. Over a third of Braze customers use us for 5 or more channels. More than half of them use us for 4 or more. Amongst our 500K+ customers, more than 90% use our SDK, over 80% use Currents to export the data that Braze generates, and already 50% are now using Cloud Data Ingestion, which is our reverse ETL product that connects directly to cloud data warehouses like Snowflake, Databricks, and Google BigQuery. You overlay that with privacy, security, and regulatory concerns that are related to first-party data and communication consent.

Bill Magnuson: For B2C audiences, which of course is where we primarily work, this has to happen at massive scale, and performance needs to be able to drive real-time interaction across an ever-growing set of channels and direct-to-consumer product interfaces. Over a third of Braze customers use us for 5 or more channels. More than half of them use us for 4 or more. Amongst our 500K+ customers, more than 90% use our SDK, over 80% use Currents to export the data that Braze generates, and already 50% are now using Cloud Data Ingestion, which is our reverse ETL product that connects directly to cloud data warehouses like Snowflake, Databricks, and Google BigQuery. You overlay that with privacy, security, and regulatory concerns that are related to first-party data and communication consent.

Speaker #3: This has to happen at massive scale and performance needs to be able to drive real time interaction across an ever growing set of channels and direct to consumer product interfaces Over a third of customers use us for five or more channels , more than half of them use us for four or more , and amongst our 500 plus customers , more than 90% use our SDK Over 80% use currents to export the data that brace generates and already 50% are now using cloud data ingestion , which is our reverse ETL product that connects directly to cloud data like snowflake , Databricks , and Google .

Speaker #3: BigQuery . You overlay that with privacy , security , and regulatory concerns that are related to first party data and communication , consent .

William Magnuson: You add the operational demands that I also mentioned in the prepared remarks of things like demanding marketing schedules, the urgency of capitalizing on cultural moments or managing through emergencies. Finally, just consider how much investment is already going into building these direct-to-consumer audiences and first-party datasets in the first place. The combined customer acquisition costs and the product investments for major consumer brands, like, consider the amount that that represents. That's the investment that's already made, and then customer engagement is a multiplier on that investment, and that means that even small basis points matter when it comes to performance. In finance, you know, you all understand the importance of having an edge in data, especially when it's driving decisions on large positions. I think sophisticated customer engagement is that same edge on a brand's customer acquisition investment.

Bill Magnuson: You add the operational demands that I also mentioned in the prepared remarks of things like demanding marketing schedules, the urgency of capitalizing on cultural moments or managing through emergencies. Finally, just consider how much investment is already going into building these direct-to-consumer audiences and first-party datasets in the first place. The combined customer acquisition costs and the product investments for major consumer brands, like, consider the amount that that represents. That's the investment that's already made, and then customer engagement is a multiplier on that investment, and that means that even small basis points matter when it comes to performance. In finance, you know, you all understand the importance of having an edge in data, especially when it's driving decisions on large positions. I think sophisticated customer engagement is that same edge on a brand's customer acquisition investment.

Speaker #3: Then you add the operational demands that I also mentioned in the prepared remarks of things like demanding marketing schedules , the urgency of capitalizing on cultural moments or managing through emergencies , and then finally , just consider how much investment is already going into building these direct to consumer audiences and first party data sets .

Speaker #3: In the first place, the combined customer acquisition costs and the product investments for major consumer brands—like, consider the amount that that represents.

Speaker #3: That's the investment that's already made. And then customer engagement is a multiplier on that investment. And that means that even small basis points matter when it comes to performance.

Speaker #3: And finance . You all understand the importance of having an edge in data , especially when it's driving decisions on large positions . I think sophisticated customer engagement is that same edge on a brand's customer acquisition investment , and we see time and again that settling for good enough just to save a little bit of money on the software line item is really throwing away enterprise value optimization .

William Magnuson: You know, we see time and again that settling for good enough just to save a little bit of money on the software line item is really throwing away enterprise value optimization. You know, I know that's multifaceted, but I think that what you see in that anecdote that you shared is that there's a lot of kind of combination of the need for vertical integration, for reliability, for performance, and for comprehensiveness. You need to interface that with privacy, security, regulatory complexity and the need for, you know, this to be operated in real time. Doing so with an external environment and, you know, complicated businesses and complicated consumer journeys and all that complexity needs to be managed. You know, that requires, I think, a professional focus on building the tooling and the platforms that address this problem.

Bill Magnuson: You know, we see time and again that settling for good enough just to save a little bit of money on the software line item is really throwing away enterprise value optimization. You know, I know that's multifaceted, but I think that what you see in that anecdote that you shared is that there's a lot of kind of combination of the need for vertical integration, for reliability, for performance, and for comprehensiveness. You need to interface that with privacy, security, regulatory complexity and the need for, you know, this to be operated in real time. Doing so with an external environment and, you know, complicated businesses and complicated consumer journeys and all that complexity needs to be managed. You know, that requires, I think, a professional focus on building the tooling and the platforms that address this problem.

Speaker #3: And so I know that's multifaceted , but I think that what you see in that anecdote that you shared is that there's , there's a lot of kind of combination of the need for vertical integration for reliability , for performance , and for comprehensiveness .

Speaker #3: And then you need to interface that with privacy, security, regulatory complexity, and the need for this to be operated in real time.

Speaker #3: And doing so with a external environment . And , you know , complicated businesses and complicated consumer journeys and all that complexity needs to be managed .

Speaker #3: And, you know, that requires, I think, a professional focus on building the tooling and the platforms that address this problem.

Scott Berg: Excellent answer. Well understood. Thank you. I guess from a follow-up perspective, I've been at the Shoptalk Conference yesterday and today, and you all have a big presence here, obviously. There's a significant amount of brand momentum with this new universal commerce protocol in a couple of different areas. I know you all had released your SDK for ChatGPT last fall to take advantage of some of the apps they were embedding in their platform. As your customers use more of this UCP to capture transactions on these, you know, on these new channels and platforms, how do you all benefit? How do you capture some of that first-party data, you know, kind of, you know, rich in that workflow or process?

Speaker #4: Excellent answer . Well understood . Thank you . And then I guess from a follow up perspective , I've been at the shop conference yesterday and today , and you all have a big presence here .

Speaker #4: , but there's a significant amount of brand momentum with this new universal commerce protocol , a couple of different areas . I know you all had released your SDK for ChatGPT last fall to take advantage of some of the apps they were getting in their platform , but as your customers use more of this UCP to capture transactions on these on these new channels and platforms , how do you all benefit ?

Speaker #4: How do you capture some of that first-party data within that workflow or process?

William Magnuson: Yeah. I think two things. One is that Braze will always be invested in every new consumer interface that helps us understand the customer and the customer journey better, any source of first-party data. We will also invest in areas where we can communicate with customers and where we can help drive better personalization for the product experiences that are delivered to them. You know, no matter what happens with consumer devices or app stores, the most valuable customers to a brand are gonna continue to be those that they have a direct relationship with.

Bill Magnuson: Yeah. I think two things. One is that Braze will always be invested in every new consumer interface that helps us understand the customer and the customer journey better, any source of first-party data. We will also invest in areas where we can communicate with customers and where we can help drive better personalization for the product experiences that are delivered to them. You know, no matter what happens with consumer devices or app stores, the most valuable customers to a brand are gonna continue to be those that they have a direct relationship with.

Speaker #3: Yeah, so I think two things. One is that Braze, Inc. will always be invested in every new consumer interface. That helps us understand the customer and the customer journey better.

Speaker #3: Any source of first-party data. And we will also invest in areas where we can communicate with customers and where we can help drive better personalization for the product experiences that are delivered to them.

Speaker #3: And, you know, no matter what happens with consumer devices or app stores, the most valuable customers to a brand are going to continue to be those that they have a direct relationship with.

William Magnuson: Braze's bread and butter and focus has always been about helping brands expand and strengthen those audiences that they can access through direct-to-consumer interfaces, or, you know, other messaging channels that have low marginal costs that are dictated based off of user consent and the right to communicate with them, instead of needing to kind of pay to acquire the right to put a message in front of their eyes over and over again, which of course is a great way to acquire customers, but can't be how you run a business over the long term. Also managing the first-party data that contextualizes them, and then orchestrating the product and messaging interactions that enrich those relationships over time. I think, you know, we're always on top of new innovations and developments in new direct-to-consumer interfaces of all kinds.

Bill Magnuson: Braze's bread and butter and focus has always been about helping brands expand and strengthen those audiences that they can access through direct-to-consumer interfaces, or, you know, other messaging channels that have low marginal costs that are dictated based off of user consent and the right to communicate with them, instead of needing to kind of pay to acquire the right to put a message in front of their eyes over and over again, which of course is a great way to acquire customers, but can't be how you run a business over the long term. Also managing the first-party data that contextualizes them, and then orchestrating the product and messaging interactions that enrich those relationships over time. I think, you know, we're always on top of new innovations and developments in new direct-to-consumer interfaces of all kinds.

Speaker #3: Braze, Inc. bread and butter and focus has always been about helping brands expand and strengthen those audiences that they can access through direct to consumer interfaces or other messaging channels that have low marginal costs , that are dictated based off of user consent and the right to communicate with them instead of needing to kind of pay to acquire the right to put a message in front of their eyes over and over again , which of course is a great way to acquire customers , but can't be how you run a business over the long term .

Speaker #3: And also managing the first-party data, then contextualizing them and orchestrating the product and messaging interactions that enrich those relationships over time.

Speaker #3: And so I think , you know , we , we're , we're always on top of new innovations and developments in new direct to consumer interfaces of all kinds .

William Magnuson: We're always interested in how they can help us learn about customers better, communicate with them, in new ways. Of course, the more complex that landscape gets, the stronger the answer that I provided to your first question is because it means that there's even more complexity for where the data comes from. There's even more complexity for where the interactions are. As I, you know, mentioned in response to Ryan, I think that, you know, when we look at agentic workflows, they're also characterized by moving even faster. That's a place where our focus on performance that we've always historically had is gonna be even more important competitively.

Bill Magnuson: We're always interested in how they can help us learn about customers better, communicate with them, in new ways. Of course, the more complex that landscape gets, the stronger the answer that I provided to your first question is because it means that there's even more complexity for where the data comes from. There's even more complexity for where the interactions are. As I, you know, mentioned in response to Ryan, I think that, you know, when we look at agentic workflows, they're also characterized by moving even faster. That's a place where our focus on performance that we've always historically had is gonna be even more important competitively.

Speaker #3: We're always interested in how they can help us learn about customers better , communicate with them in new ways . And of course , the more complex that that landscape gets , the stronger the answer that I provided to your first question is because it means that there's even more complexity for where the data comes from .

Speaker #3: There's even more complexity for where the interactions are . And as I mentioned in , in response to Ryan , I think that , you know , when we look at Agentic workflows , they're also characterized by moving even faster .

Speaker #3: And that's a place where our focus on performance that we've always historically had is going to be even more important competitively.

Operator: Your next question will come from Raimo Lenschow with Barclays.

Speaker #1: Your next question will come from Raimo with Barclays.

Raimo Lenschow: Hey, thank you. Can you hear me okay?

Speaker #5: Thank you. Can you hear me? Okay.

Operator: Yeah, we can hear you great.

Speaker #6: Yeah, we can hear you. Great.

Raimo Lenschow: Okay, perfect. Thank you. Can I start with the DBNR, like, got better to 109. You talked about it the last few quarters that, you know, it's a lagging indicator that kind of takes some time to improve, but it's really nice to see the improvement now. Can you talk a little bit about the journey we should expect from here? That's my first question. Second question is, with Ed there joining Q2, normally the big changes to go-to-market happen more at the beginning of a new year. Is there anything we should be aware of as we go into this year in terms of changes that we should expect there? Thank you, and congrats from me as well.

Speaker #5: Okay , perfect . Thank you . Can I start with the dibner got better . 209 . You talked about it the last few quarters that , you know , it's a lagging indicator .

Speaker #5: That kind of takes some time to improve , but it's really nice to see the improvement . Now , can you talk a little bit about the journey we should expect from here ?

Speaker #5: Like is ? That's my first question . Second question is with they're joining Q2 . Normally the big changes to go to market happen more at the beginning of a new year .

Speaker #5: Is there anything we should be aware of as we go into this year, in terms of changes that we should expect there? Thank you, and congrats from me as well.

Isabelle Winkles: Yeah. On the DBNR, you know, one thing that I had been providing is at least a directional view on the in-quarter organic number. Over the last couple quarters, we had talked about it being a little bit below 107 and then a little bit above 107, and then continuing to kinda trend up from there. What I can say here is that the in-quarter organic is above, you know, where we're recording, so where we're reporting. You know, I think the direction of travel here, we're very comfortable with sort of what we're seeing. We're really excited about the momentum in the business that is driving this.

Speaker #6: Yeah . So on the Dibner , you know , one thing that I had been providing is at least a directional view on the in quarter organic number .

Speaker #6: And so over the last couple of quarters , we had talked about it being a little bit below 107 and then a little bit above hundred seven , and then continuing to trend up from there .

Speaker #6: What I can say here is that the in quarter organic is , is , is above , you know , where we're where we're recording .

Speaker #6: So we're , we're reporting . So , you know , I think the , the direction of travel here , we're very comfortable with sort of what we're seeing .

Speaker #6: We're really excited about the momentum in the business that is driving this . And so it is a lagging indicator . But you know , I think we are comfortable that some of the troughing that we have experienced over the last couple of quarters , we've talked about being through the belly of the beast .

Isabelle Winkles: It is a lagging indicator, but you know, I think we are comfortable that some of the troughing that we have experienced over the last couple quarters, we've talked about being through the belly of the beast, and we are in fact through the belly of the beast. Hopefully that's some helpful color, though we don't specifically guide on the metric.

Speaker #6: And we are in fact , through the belly of the beast . So hopefully that's that's some helpful color , though we don't specifically guide on the metric

Parker Lane: Perfect. Thank you.

Raimo Lenschow: Perfect. Thank you.

Isabelle Winkles: With regards to Ed, look, you know, I think in my last set of answers to questions here, I was indicating that, you know, Ed has been driving forward a number of initiatives that we had already put into motion. You know, not a lot of sort of massive changes. He is trying to be more effective and efficient about, you know, bringing on the new headcount and being rapid in the right areas, being disciplined about where that is being deployed, building out, you know, internal capabilities to help our sales team be more enabled and move more quickly. He

Speaker #5: Perfect . Thank you .

Speaker #6: And then with regards to editor , look , you know , I think in my last set of answers to questions here , I was indicating that , you know , editor has been driving forward a number of initiatives that we had already put into motion .

Speaker #6: And so , you know , not a lot of sort of massive changes . He is trying to be more effective and efficient about bringing on the new headcount and being rapid in the right areas , being disciplined about where that is being deployed , building out , you know , internal capabilities to help our sales team be more enabled and move more quickly .

Isabelle Winkles: You know, I think we said in the beginning, he's not only has he seen the movie, but he's seen the remake, and we're definitely seeing the impacts of that, and leveraging his relationships across the potential hires and prospects here. Nothing, you know, material that we need to kinda call out, and he's just, you know, moving things forward in a way that we feel really happy about.

Speaker #6: And he , you know , I think we said at the beginning , he's not only has he seen the movie , but he's seen the remake .

Speaker #6: And we're definitely seeing the the impacts of that . And leveraging his relationships across across the , the , you know , potential hires and , and prospects So nothing , you know , material that we need to kind of call out .

Speaker #6: And he's just , you know , moving things forward in a way that we feel really happy about

Parker Lane: Perfect. Thank you. Congrats.

Raimo Lenschow: Perfect. Thank you. Congrats.

Speaker #5: Perfect. Thank you. Congrats.

Operator: Your next question will come from Parker Lane with Stifel.

Speaker #1: Your next question will come from Parker Lane with Stifel .

Parker Lane: Hey, guys. Thanks for taking the question. Isabelle, maybe one for you on gross margins. If you look at premium messaging channel growth, you look at some of these new products you have and your comments about the immediate consumption of credits you see from Agent Console, what's the impact to the predictability of gross margins that you're seeing in this business? And what's the right way to think about not only the near-term picture, but sort of the mid-range picture of gross margins as well?

Speaker #7: Hey , guys . Thanks for taking the question . Isabel , maybe one for you on , on . Gross margins . If you look at premium messaging channel growth , you look at some of these new products you have and your comments about the immediate consumption of credits .

Speaker #7: You see from Asian console . What's the impact of the predictability of gross margins that you're seeing business ? And what's the right way to think about not only the near-term picture , but sort of the mid-range picture of gross margins as well

Isabelle Winkles: Yeah. Look, we've talked about the evolution of the premium messaging and how that mixes in. Just keep in mind that, you know, really over the last couple of years, the only new channels that we have introduced are in fact these premium messaging channels. Now we are introducing, you know, certainly with the advent of Agent Console and some of the other features here, things that mix in with a slightly better margin. That said, it's starting off of a small base, and so it's gonna take, you know, some time for all of that to kind of work itself in. Certainly the premium messaging is still in demand by our customers.

Speaker #6: Yeah . So look , we've talked about the evolution of the the premium messaging and how that mixes in . And just keep in mind that , you know , really over the last couple of years , the only new channels that we have introduced are in fact , these premium messaging channels .

Speaker #6: So now we are introducing , you know , certainly with the advent of agent console and some of the other features here , things that mix in with a slightly better margin .

Speaker #6: That said , it's starting off of a small base . And so it's going to take some time for all of that to kind of work itself in .

Speaker #6: And certainly the premium messaging is still in demand by our customers . And so I don't think there's so much of an issue necessarily with predictability , because we continue to look at that on a fairly detailed basis , but certainly , you know , we've got eyes on on the direction of travel .

Isabelle Winkles: I don't think there's so much of an issue necessarily with predictability because we, you know, continue to look at that on a fairly detailed basis. Certainly, you know, we've got eyes on the direction of travel. Really I think what's important is the 8% operating income margin that we feel really comfortable with for the year, and we're gonna continue to manage that.

Speaker #6: And really, I think what's important is the 8% operating income margin that we feel really comfortable with for the year, and we're going to continue to manage that.

Parker Lane: Got it. Thanks. Bill, one for you. You talked earlier about AI not just helping in the form of new products, but making your existing capabilities more approachable and accessible. I was wondering if you could provide a concrete example or two of what you're seeing there. Where do you expect that to translate into business results? Is that better win rates, better utilization, less churn, all the above?

Speaker #7: Got it . Thanks . And Bill , one for you . You talked earlier about AI not just helping in the form of new products , but making your existing capabilities more approachable and accessible .

Speaker #7: I was wondering if you could provide a concrete example or two of what you're seeing there , and where do you expect that to translate into business results ?

Speaker #7: Is that better win rates , better utilization , less churn ? All the above

William Magnuson: Yeah. I think that when you look at the history of Braze, we more often are held back by, you know, making sure that our customer base can really flex into the full power and sophistication that Braze has to offer. One of the things that is most exciting to me about the Braze AI potential right now is that we are both making Braze smarter and more powerful, and we're making it easier and faster to use. As we redefine that new front door to marketing technology again, the door is both easier to open, and when you get to the other side, you know, there's a lot more excitement and value generation there. You know, we're already seeing this in Agent Console.

Bill Magnuson: Yeah. I think that when you look at the history of Braze, we more often are held back by, you know, making sure that our customer base can really flex into the full power and sophistication that Braze has to offer. One of the things that is most exciting to me about the Braze AI potential right now is that we are both making Braze smarter and more powerful, and we're making it easier and faster to use. As we redefine that new front door to marketing technology again, the door is both easier to open, and when you get to the other side, you know, there's a lot more excitement and value generation there. You know, we're already seeing this in Agent Console.

Speaker #3: Yeah . So I think that when you look at the history of braze , we more often are held back by , you know , making sure that our customer base can really flex into the full power and sophistication that braze has to offer .

Speaker #3: And one of the things that is most exciting to me about the Braze, Inc. potential right now is that we are both making Braze smarter and more powerful, and we're making it easier and faster to use.

Speaker #3: And so as we redefine that new front door to marketing technology , again , the door is both easier to open . And when you get to the other side , you know , there's , there's a lot more excitement and value generation there .

Speaker #3: And , you know , we're already seeing this in the agent console . I mentioned an example in the prepared remarks where we had a lot of customers who were working on building new agents within , you know , within the beta test .

William Magnuson: I mentioned an example in the prepared remarks where we had a lot of customers who were working on building new agents within the beta test and were asking for more templates, more ideas, et cetera. We actually went through and we had already been working on prompt to campaign, prompt to email generation, prompt to Canvas, where people can actually write code their canvases directly from the Braze Operator. Not only is it providing you advice, it's literally grabbing control of the dashboard, and you watch it happen in front of your eyes. You're both learning. You're both, like, having the operator act for you, but you're also learning how to use it at the same time as you watch it.

Bill Magnuson: I mentioned an example in the prepared remarks where we had a lot of customers who were working on building new agents within the beta test and were asking for more templates, more ideas, et cetera. We actually went through and we had already been working on prompt to campaign, prompt to email generation, prompt to Canvas, where people can actually write code their canvases directly from the Braze Operator. Not only is it providing you advice, it's literally grabbing control of the dashboard, and you watch it happen in front of your eyes. You're both learning. You're both, like, having the operator act for you, but you're also learning how to use it at the same time as you watch it.

Speaker #3: And we're asking for more templates , more ideas , etc. . And we actually went through and we had already been working on prompt campaign prompt to email generation prompt to canvass where people can actually vibe code their canvases directly from the braze operator .

Speaker #3: And not only is it providing you advice, it's literally grabbing control of the dashboard, and you watch it happen in front of your eyes.

Speaker #3: And so you're both learning, you're both, like, having the operator act for you, but you're also learning how to use it at the same time as you watch it.

William Magnuson: That allows for marketers to then immediately go in and, you know, check things, to tweak them, to refine them, et cetera. I think as a platform that's used for publishing at massive scale or, you know, where there's a professional skill set of high consequence, you know, when you're running marketing programs that you're relying on to hit your quarterly numbers or that need to go out to, you know, 100 million people around the globe in response to a critical emergency or to take full advantage of an evolving cultural moment or what have you know, these are all places where you need to combine both rapid usability with high confidence.

Speaker #3: And that allows for—that allows for marketers to then immediately go in and check things, to tweak them, to refine them, etc.

Bill Magnuson: That allows for marketers to then immediately go in and, you know, check things, to tweak them, to refine them, et cetera. I think as a platform that's used for publishing at massive scale or, you know, where there's a professional skill set of high consequence, you know, when you're running marketing programs that you're relying on to hit your quarterly numbers or that need to go out to, you know, 100 million people around the globe in response to a critical emergency or to take full advantage of an evolving cultural moment or what have you know, these are all places where you need to combine both rapid usability with high confidence.

Speaker #3: . I think as a platform that's used for publishing at massive scale , or you know , where there's a professional skill set of high consequence , you know , when you're running marketing programs that you're relying on to hit your quarterly numbers or that need to go out to 100 million people around the globe in , a , in a , in response to a critical emergency or to take full advantage of an evolving cultural moment or what have you .

Speaker #3: You know , these are all places where you need to combine both rapid usability with high confidence and being able to , to see the operator , you know , building more confidence for people , speeding up their own workflows , providing that and providing that inspiration with our existing feature set is incredible .

William Magnuson: Being able to see the Operator, you know, building more confidence for people, speeding up their own workflows, providing that inspiration with our existing feature set is incredible. Then when we go over to the Agent Console, you know, where people are getting used to prompting, but, you know, there's still a lot to do there. Building a good agent does have a specialized skill set around it. There's still some work that you need to do around the outputs from the agent and helping make sure that there's consistency and that you're getting the right context in the context window. We've built incredible capability in Agent Console to manage that. Even more exciting is that Operator is helping write and inspire those agents for people.

Bill Magnuson: Being able to see the Operator, you know, building more confidence for people, speeding up their own workflows, providing that inspiration with our existing feature set is incredible. Then when we go over to the Agent Console, you know, where people are getting used to prompting, but, you know, there's still a lot to do there. Building a good agent does have a specialized skill set around it. There's still some work that you need to do around the outputs from the agent and helping make sure that there's consistency and that you're getting the right context in the context window. We've built incredible capability in Agent Console to manage that. Even more exciting is that Operator is helping write and inspire those agents for people.

Speaker #3: Then when we go over to the agent console , you know where people are , they're getting used to prompting , but you know , there's still a lot to do there .

Speaker #3: And , you know , building a good agent does have a , you know , a specialized skill set around it . There's still some work that you need to do around the outputs from the agent and helping make sure that there's consistency and that you're getting the right context and the context window .

Speaker #3: And we've built incredible capability in Agent Console to manage that. Even more exciting is that operators are helping, right? And inspire those agents for people.

William Magnuson: It's just driving faster adoption. It's driving higher levels of curiosity for people to be able to use new features that they maybe hadn't looked at before, and helping really build stronger confidence for them to use a system like Braze that, you know, is really it's always been a small number of builders and a small number of marketers wielding it at massive scale, and that has a stress and a pressure and a consequentialism to it, that, you know, having that Operator assistant there with you really helps increase confidence and we think is gonna drive a lot more usage.

Bill Magnuson: It's just driving faster adoption. It's driving higher levels of curiosity for people to be able to use new features that they maybe hadn't looked at before, and helping really build stronger confidence for them to use a system like Braze that, you know, is really it's always been a small number of builders and a small number of marketers wielding it at massive scale, and that has a stress and a pressure and a consequentialism to it, that, you know, having that Operator assistant there with you really helps increase confidence and we think is gonna drive a lot more usage.

Speaker #3: And so it's just driving faster adoption. It's driving higher levels of curiosity for people to be able to use new features that they maybe hadn't looked at before.

Speaker #3: And helping really build stronger confidence for them to use a system like braze that , you know , is really , it's always been a small number of builders and a small number of marketers wielding it at massive scale .

Speaker #3: And that has a stress and a pressure and a consequentialism to it that , you know , having that operator assistant there with you really helps increase confidence .

Speaker #3: And we think is going to drive a lot more usage

Operator: Your next question will come from Brent Thill with Stephens.

Speaker #1: Your next question will come from Brett Huff with Stephens.

Brent Thill: Good afternoon and congrats on seeing in the financials stuff that I know you all have been working on kind of in the background for a long time, so nice to see that. Two questions. One big picture. I think this is for you, Bill. Your conversations with folks you're selling to on AI, our checks tell us that data heterogeneity, you know, lack of AI talent, governance issues are all roadblocks. At the same time, companies seem to want quick hit, high ROI things that are happening in order to justify continued spend. You know, how are those conversations going with Braze?

Speaker #8: Good afternoon. And congrats on seeing in the financials stuff that I know you all have been working on kind of in the background for a long time.

Speaker #8: So nice to see that Two questions . One big picture . I think this is for you , Bill , as you're hearing , is conversations with folks you're selling to on AI are checks tell us that data heterogeneity , you know , lack of AI talent , governance issues are all roadblocks at the same time .

Speaker #8: Companies seem to want quick hit high ROI things that are happening in order to justify continued spend . How are you ? You know , how are those conversations going with Braze, Inc. your point about more features , easier to get to , but is there some anecdotes there that give us a little bit of meat on the bone on that , that we might be able to sort of get our head around ?

Brent Thill: I think your point about more features, easier to get to, but is there some anecdotes there that give us a little bit of meat on the bone on that we might be able to sort of get our head around?

William Magnuson: Well, I think first of all, every software investment decision being made right now, you have to have confidence that the company that you are, you know, spending the time to integrate with, to enable your teams on and to, you know, build with and commit to, has their arms around taking advantage of AI innovation. I think that's table stakes for everyone. Even if you as a team don't, like, have confidence that you're gonna be able to use it all on day zero, or maybe the incremental budget to, you know, drive new use cases isn't there yet, et cetera.

Bill Magnuson: Well, I think first of all, every software investment decision being made right now, you have to have confidence that the company that you are, you know, spending the time to integrate with, to enable your teams on and to, you know, build with and commit to, has their arms around taking advantage of AI innovation. I think that's table stakes for everyone. Even if you as a team don't, like, have confidence that you're gonna be able to use it all on day zero, or maybe the incremental budget to, you know, drive new use cases isn't there yet, et cetera.

Speaker #3: Yeah . Well , I think first of all , every software investment decision being made right now , you have to have confidence that the company that you are spending the time to integrate with , to enable your teams on and to , you know , to , to , to build with and commit to has their arms around taking advantage of AI innovation .

Speaker #3: And so I think that's table stakes for everyone , even if you as a team don't like , have confidence that you're going to be able to use it all on day zero , or maybe the incremental budget to , you know , drive new use cases isn't there yet , etc.

William Magnuson: There's just simply no one that is making a switch in a software vendor right now without having the confidence that it's the right vendor for them to bet on, you know, as they move into this future that's being transformed by AI. That's why, you know, I think if you go back to my answer to Ryan's first question in talking about the strength in Q4, so much of that just came out of the confidence in the roadmap and the confidence in the beta test. We were able to show live demos of Operator and Agent Console. You know, now obviously they're out there in general availability, so it's even more palpable for everyone. You know, I think that a lot of the things that you just said are true.

Bill Magnuson: There's just simply no one that is making a switch in a software vendor right now without having the confidence that it's the right vendor for them to bet on, you know, as they move into this future that's being transformed by AI. That's why, you know, I think if you go back to my answer to Ryan's first question in talking about the strength in Q4, so much of that just came out of the confidence in the roadmap and the confidence in the beta test. We were able to show live demos of Operator and Agent Console. You know, now obviously they're out there in general availability, so it's even more palpable for everyone. You know, I think that a lot of the things that you just said are true.

Speaker #3: . There's just simply no one that is making a switch in a software vendor right now without having the confidence that it's the right vendor for them to bet on , you know , as they move into this , into this future that's being transformed And that's why , you know , I think if you go back to my answer to Ryan's first question and talking about the strength in Q4 , so much of that just came out of the confidence in the roadmap and the confidence in the , you know , the beta test .

Speaker #3: We were able to show live demos of operator and agent console . You know , now obviously they're out there in general availability , availability .

Speaker #3: So it's even more palpable for everyone . And you know , I , I , I think that a lot of the things that you just said are true , there's a lot of sources of anxiety around there .

William Magnuson: There's a lot of sources of anxiety around there. A lot of this is still dynamic. It's changing really fast. At the end of the day, you know, we already see Agent Console driving stronger performance in ongoing campaigns. These aren't like brand new experimental use cases. You know, there's the same customer journeys are actually just being executed on with higher performance. It's driving real revenue, real performance uplift. It's doing so in, you know, an environment that's easy to test and experiment and scale with. I mentioned Canvas as an important control plane. You know, I think when you look at the difficulty of deploying AI in a lot of enterprises, a lot of it has to do with context engineering. It has to do with observability and governance and that control plane.

Bill Magnuson: There's a lot of sources of anxiety around there. A lot of this is still dynamic. It's changing really fast. At the end of the day, you know, we already see Agent Console driving stronger performance in ongoing campaigns. These aren't like brand new experimental use cases. You know, there's the same customer journeys are actually just being executed on with higher performance. It's driving real revenue, real performance uplift. It's doing so in, you know, an environment that's easy to test and experiment and scale with. I mentioned Canvas as an important control plane. You know, I think when you look at the difficulty of deploying AI in a lot of enterprises, a lot of it has to do with context engineering. It has to do with observability and governance and that control plane.

Speaker #3: A lot of this is still dynamic . It's changing really fast , but at the end of the day , you know , we already see agent console driving stronger performance in ongoing campaigns .

Speaker #3: These aren't like brand new experimental use cases . This is , you know , there's the same customer journeys are actually just being executed on with higher performance .

Speaker #3: It's driving real revenue , real performance uplift . It's doing so in an environment that's easy to test . And experiment and scale with .

Speaker #3: I mentioned Canvas as an important control plane. You know, I think when you look at the difficulty of deploying AI in a lot of enterprises, a lot of it has to do with context engineering.

Speaker #3: It has to do with observability . And governance . And that control plane . And when you look at Braves , the Braves data platform is providing that context .

William Magnuson: When you look at Braze, the Braze Data Platform is providing that context engineering. Canvas is providing that control plane. You know, we have Decisioning Studio as another angle of being able to bring in agentic decision-making over deep data science. You know, when that reinforcement learning approach is the right AI technique to apply depending on where you are in the customer journey. We have this full spectrum of the right solution and the right approach for the complex problem space of customer engagement, and we can help guide customers to that. You know, the vast majority of it is relying on the combination of a reliable, high-performance, stable and secure infrastructure that Braze has always maintained as a competitive advantage in our space. Now we're multiplying the value of that with our investments in BrazeAI.

Bill Magnuson: When you look at Braze, the Braze Data Platform is providing that context engineering. Canvas is providing that control plane. You know, we have Decisioning Studio as another angle of being able to bring in agentic decision-making over deep data science. You know, when that reinforcement learning approach is the right AI technique to apply depending on where you are in the customer journey. We have this full spectrum of the right solution and the right approach for the complex problem space of customer engagement, and we can help guide customers to that. You know, the vast majority of it is relying on the combination of a reliable, high-performance, stable and secure infrastructure that Braze has always maintained as a competitive advantage in our space. Now we're multiplying the value of that with our investments in BrazeAI.

Speaker #3: Engineering canvas is providing that control plane . You know , we have decisioning studio as another angle of being able to bring in Agentic decision making over deep data science .

Speaker #3: You know , when that reinforcement learning approach is the right AI technique to apply , depending on where you are in the customer journey .

Speaker #3: And we have this full spectrum of the right solution and the right approach for the complex problem space of customer engagement. And we can help guide customers to that.

Speaker #3: And , you know , the vast majority of it is relying on the combination of a reliable high performance , stable and secure infrastructure that braze has always maintained as a competitive advantage in our space .

Speaker #3: And now we're multiplying the value of that with our investments in AI.

Brent Thill: That's super helpful. Thanks for the insight. Isabelle, we're hearing more and more about verticalization. We also got an update on the gross margin, sort of maybe we're gonna get some tailwinds on that given the new AI products. Can you talk a little bit about sort of long-term any change in long-term sort of puts and takes on the gross margin pressures? Should we think about any step change for verticalization spending or is that just a matter of course?

Speaker #8: That's super helpful . For the insight and we're hearing more and more about Verticalization . And we also got an update on the gross margin , sort of maybe we're going to get some , some tailwinds on that given the new AI products .

Speaker #8: Can you talk a little bit about sort of long term , any change in long term sort of puts and takes on the the gross margin pressures and then should we think about any step change for verticalization spending , or is that just a matter of course .

William Magnuson: Yeah. I think on verticalization I would just consider that kind of a matter of ordinary course. We're just gonna continue to kind of expand slowly but methodically, just deepening our focus on some of the verticals. We've already started this over the last couple of years, and I would just kind of continue to expect that to kinda continue to expand. From a gross margin perspective, yeah, look, I mean, we've been talking about the impact of some of the premium messaging. I did indicate that in my response to one of the last questions that some of these new products and Agent Console does mix in with a better than company average margin.

Isabelle Winkles: Yeah. I think on verticalization I would just consider that kind of a matter of ordinary course. We're just gonna continue to kind of expand slowly but methodically, just deepening our focus on some of the verticals. We've already started this over the last couple of years, and I would just kind of continue to expect that to kinda continue to expand. From a gross margin perspective, yeah, look, I mean, we've been talking about the impact of some of the premium messaging. I did indicate that in my response to one of the last questions that some of these new products and Agent Console does mix in with a better than company average margin.

Speaker #6: Yeah . So I think on Verticalization , I would just consider that kind of a matter of ordinary course . We're just going to continue to kind of expand slowly , but methodically .

Speaker #6: Just deepening our focus on some of the verticals . We've already started this over the last couple of years , and I would just kind of continue just expect that to kind of continue to , to expand .

Speaker #6: And then from a gross margin perspective . Yeah , look , I mean , we've been talking about the , the impact of some of the premium messaging .

Speaker #6: And then I did indicate that in my response to one of the last questions that the some of these new products and agent console does mix in with better than company average margin , but it's obviously starting off from low dollars .

William Magnuson: It's obviously starting off from low dollars and so it will take a bit of time for that to kind of mix in more meaningfully. You know, what we're really focused on is the operating income margin down to the bottom line, and we feel really good about that 8%.

Isabelle Winkles: It's obviously starting off from low dollars and so it will take a bit of time for that to kind of mix in more meaningfully. You know, what we're really focused on is the operating income margin down to the bottom line, and we feel really good about that 8%.

Speaker #6: And so we'll take a bit of time for that to kind of mix in more meaningfully . And so , you know what we're really focused on is the operating income margin down to the bottom line .

Speaker #6: And we feel really good about that 8% .

Operator: In the interest of time, please limit to one question. Our next question will come from Arjun Bhatia with William Blair.

Speaker #1: In the interest of time, please limit to one question. Our next question will come from Arjun Bhatia with William Blair.

Arjun Bhatia: Perfect. Thank you guys. Bill, maybe can we touch on it seems like Agent Console is obviously getting a lot of traction and I'm just curious if you can kind of put that into perspective of when that might help monetization. Which types of customers do you think will adopt that first? In the broader scheme of things, you know, we're hearing a lot about obviously third-party agent proliferation. I'm curious how that mixes in with Agent Console and if you have any views on what access third-party agents would have to Braze or not have to Braze, and the data that you store for your customers.

Speaker #9: Perfect . Thank you guys . Bill , maybe can we touch on it seems like Agent Console is obviously getting a lot of traction and I'm just curious if you can kind of put that into perspective of when that might help .

Speaker #9: Monetization , which types of customers do you think will adopt that first ? And then in the broader scheme of things , you know , we're hearing a lot about , obviously third party agent proliferation .

Speaker #9: So I'm curious how that mixes in with agent console. And if you have any views on what access third-party agents would have to Braze or not have to Braze, and the data that you store for your customers.

William Magnuson: Yeah. I'll just hit those topics, one by one. Regarding Agent Console and pacing of adoption and revenue, as I shared in the prepared remarks, both Agent Console and Operator went into general availability months ahead of schedule, and we're already seeing great uptake on both. You know, after just a few weeks, more than two-thirds of our customers are now actively using Operator, and we're watching Agent Console adoption grow week over week. I think we're gonna have a lot more to share about both of those at our City by City London, which is our second largest event of the year, just one month from now on 23 April at Olympia, London. We're also lining up the entire company and our partnership ecosystem to help push adoption.

Bill Magnuson: Yeah. I'll just hit those topics, one by one. Regarding Agent Console and pacing of adoption and revenue, as I shared in the prepared remarks, both Agent Console and Operator went into general availability months ahead of schedule, and we're already seeing great uptake on both. You know, after just a few weeks, more than two-thirds of our customers are now actively using Operator, and we're watching Agent Console adoption grow week over week. I think we're gonna have a lot more to share about both of those at our City by City London, which is our second largest event of the year, just one month from now on 23 April at Olympia, London. We're also lining up the entire company and our partnership ecosystem to help push adoption.

Speaker #3: Yeah . So I'll just hit those topics one by one . So regarding agent console and pacing of adoption and revenue , as I shared in the prepared remarks , both agent console and operator both went into general availability months ahead of schedule .

Speaker #3: And seeing great uptake on both . You know , after just a few weeks , more than two thirds of our customers are now actively using operator , and we're watching agent console adoption grow week over week .

Speaker #3: I think we're gonna have a lot more to share about both of those at our , at city by city , London , which is our second largest event of the year , just one month from now .

Speaker #3: On April 23rd at Olympia , London . And we're also lining up the entire company and our partnership ecosystem to help push adoption .

William Magnuson: You know, Agent Console is already showing material results for its beta testers and early adopters, and we're excited for it to spread rapidly across the customer base. But also remind, you know, you and everyone else quickly that Agent Console consumes flexible credits, so it is consumption-based pricing, but the revenue is recognized the same way that it is for messaging volumes, which is to say that it's ratably over the length of the contract. We expect usage of Agent Console to be supportive of early renewals and upsells. Keep in mind that the consumption of credits does not lead to immediate revenue recognition in our contracting model. We do have the benefit that we've been shifting to this flexible credits model over the last few years.

Bill Magnuson: You know, Agent Console is already showing material results for its beta testers and early adopters, and we're excited for it to spread rapidly across the customer base. But also remind, you know, you and everyone else quickly that Agent Console consumes flexible credits, so it is consumption-based pricing, but the revenue is recognized the same way that it is for messaging volumes, which is to say that it's ratably over the length of the contract. We expect usage of Agent Console to be supportive of early renewals and upsells. Keep in mind that the consumption of credits does not lead to immediate revenue recognition in our contracting model. We do have the benefit that we've been shifting to this flexible credits model over the last few years.

Speaker #3: Agent console is already showing material results for its beta testers and early adopters , and we're excited for it to spread rapidly across the customer base .

Speaker #3: But also remind you and everyone else quickly that agent console consumes flexible credits . So its billed or it's it is , it is consumption based pricing , but the revenue is recognized the same way that it is for messaging volumes , which is to say that it's radically over the length of the contract .

Speaker #3: So, we expect usage of Agent Console to be supportive of early renewals and upsells. But keep in mind that the consumption of credits does not lead to immediate revenue recognition in our contracting model.

Speaker #3: We do have the benefit that we've been shifting to this flexible credits model over the last few years , and the customers who have adopted the new credits plan , which has been , you know , as a reminder , has basically been the default for all renewals and new business over the course of the last couple years .

William Magnuson: The customers who have adopted the new credits plan, which has been, you know, as a reminder, has basically been the default for all renewals and new business over the course of the last couple years. It's already the majority of our customer base that they already have credits that are ready to be used for Agent Console. We do have a portion of our customer base that's still on older pricing that we are, you know, working hard to move into this new world so that they can also rapidly adopt Agent Console, and that's something that we'll be focused on throughout the year. With respect to looking at, you know, other tools, you know, I think Braze has always been built for composability and built for change.

Bill Magnuson: The customers who have adopted the new credits plan, which has been, you know, as a reminder, has basically been the default for all renewals and new business over the course of the last couple years. It's already the majority of our customer base that they already have credits that are ready to be used for Agent Console. We do have a portion of our customer base that's still on older pricing that we are, you know, working hard to move into this new world so that they can also rapidly adopt Agent Console, and that's something that we'll be focused on throughout the year. With respect to looking at, you know, other tools, you know, I think Braze has always been built for composability and built for change.

Speaker #3: So it's already the majority of our customer base that they already have credits that are ready to be used for agent console . We do have a portion of our customer base that's still on older pricing that we are working hard to move into this new world so that they can also rapidly adopt agent console .

Speaker #3: And that's something that will be focused on throughout the year with respect to looking at other tools . You know , I think Brace has always been built for composability and built for change .

William Magnuson: The combination of our composable architecture, our high-performance infrastructure, and our flexible APIs aren't just a strong foundation that we use to build our own innovation. I think they're also really well suited for marketer workflows that are both transforming and inflicting through the use of other AI tools. You know, we've always been architected to be composable, to be ecosystem neutral, and to integrate with other best-of-breed tools across the modern marketing stack. That's both for plugging in to enhance things like orchestration and predictive analytics decision-making, as well as personalization. It's also for evolving new channels, new use cases, new AI capabilities, et cetera. A few other things. I think we're also seeing that performance in the context layer is more important than ever with agentic consumers.

Bill Magnuson: The combination of our composable architecture, our high-performance infrastructure, and our flexible APIs aren't just a strong foundation that we use to build our own innovation. I think they're also really well suited for marketer workflows that are both transforming and inflicting through the use of other AI tools. You know, we've always been architected to be composable, to be ecosystem neutral, and to integrate with other best-of-breed tools across the modern marketing stack. That's both for plugging in to enhance things like orchestration and predictive analytics decision-making, as well as personalization. It's also for evolving new channels, new use cases, new AI capabilities, et cetera. A few other things. I think we're also seeing that performance in the context layer is more important than ever with agentic consumers.

Speaker #3: The combination of our composable architecture , our high performance infrastructure , and our flexible APIs aren't just as strong foundation that we use to build our own innovation .

Speaker #3: I think they're also really well suited for marketer workflows that are both transforming and inflecting through the use of other AI tools . You know , we've always been architected to be composable , to be ecosystem neutral , and to integrate with other best of breed tools across the modern marketing stack .

Speaker #3: And that's both for plugging into enhance things like orchestration and , and predictive analytics , decision making , as well as personalization . It's also for evolving new channels , new use cases , new AI capabilities , etc.

Speaker #3: a few other things . I think we're also seeing that performance in the context layer is more important than ever with agenda . Consumers , you know , agents move fast and their tireless .

William Magnuson: You know, agents move fast, and they're tireless, and we think that that's a perfect match for the performance and reliability advantage that Braze has always maintained over competing and homegrown products. You know, as I mentioned earlier, we've always been a platform where leading-edge marketers with a builder mindset can deploy and optimize sophisticated strategies. I think what we're doing with Operator and Agent Console is simultaneously putting more power in their hands and making it easier to use. There's also big advantages to, you know, a tool like Operator being inside the Braze dashboard information environment, having access to our internal use case libraries, the skills that we've built, the customer's dashboard information architecture, so that it can adapt recommendations and run the dashboard for them with knowledge of their specific Braze integration.

Bill Magnuson: You know, agents move fast, and they're tireless, and we think that that's a perfect match for the performance and reliability advantage that Braze has always maintained over competing and homegrown products. You know, as I mentioned earlier, we've always been a platform where leading-edge marketers with a builder mindset can deploy and optimize sophisticated strategies. I think what we're doing with Operator and Agent Console is simultaneously putting more power in their hands and making it easier to use. There's also big advantages to, you know, a tool like Operator being inside the Braze dashboard information environment, having access to our internal use case libraries, the skills that we've built, the customer's dashboard information architecture, so that it can adapt recommendations and run the dashboard for them with knowledge of their specific Braze integration.

Speaker #3: And we think that that's a perfect match for the performance and reliability advantage that Braze has always maintained over competing and homegrown products.

Speaker #3: And , you know , as I mentioned earlier , we've always been a platform where leading edge marketers with the builder mindset can deploy and optimize sophisticated strategies .

Speaker #3: And so I think what we're doing with Operator and Agent Console is simultaneously putting more power in their hands and making it easier to use.

Speaker #3: There's also big advantages to a tool like Operator being inside the Braze, Inc. dashboard information environment, having access to our internal use case libraries, the skills that we've built, the customer's dashboard information architecture, so that it can adapt recommendations and run the dashboard for them with knowledge of their specific Braze integration.

William Magnuson: We actually had a really great anecdote on BrazeAI Operator that was shared by a customer recently that they were working through a difficult challenge with Liquid that they had spent over an hour on, you know, using one of the big chat AI products. Operator solved the problem for them in a minute because Operator had full knowledge of the way that Braze uses Liquid, where it was in the dashboard, and the information architecture. You know, I think being able to adapt both the context and the semantic layer and be able to train the operator with the skills and the, you know, the knowledge of the dashboard architecture is gonna provide differentiation. You know, we've always been composable, built for change, and extensible.

Bill Magnuson: We actually had a really great anecdote on BrazeAI Operator that was shared by a customer recently that they were working through a difficult challenge with Liquid that they had spent over an hour on, you know, using one of the big chat AI products. Operator solved the problem for them in a minute because Operator had full knowledge of the way that Braze uses Liquid, where it was in the dashboard, and the information architecture. You know, I think being able to adapt both the context and the semantic layer and be able to train the operator with the skills and the, you know, the knowledge of the dashboard architecture is gonna provide differentiation. You know, we've always been composable, built for change, and extensible.

Speaker #3: We actually had a really great anecdote on Braze Operator that was shared by a customer recently that they were working through a difficult challenge with liquid that they had spent over an hour on , you know , using one of the leading edge , or using one of the the big chat AI products and operator solved the problem for them in a minute because operator had full knowledge of the way that braze liquid where it was in the dashboard and the information architecture .

Speaker #3: And so , you know , I think being able to adapt both the context and the semantic layer and be able to train the operator with the , the skills and the , you know , the knowledge of the dashboard architecture is going to provide differentiation .

Speaker #3: But , you know , we've always been composable , built for change and extensible . And so we're also already seeing a lot of customers that are using the Smtp server .

William Magnuson: We're also already seeing a lot of customers that are using the Braze MCP server and using our powerful and flexible APIs in order to innovate their own workflows outside of the ecosystem, and we embrace both of those through our composability.

Bill Magnuson: We're also already seeing a lot of customers that are using the Braze MCP server and using our powerful and flexible APIs in order to innovate their own workflows outside of the ecosystem, and we embrace both of those through our composability.

Speaker #3: And using our powerful and flexible APIs in order to innovate their own workflows outside of the ecosystem. And we embrace both of those through our composability.

Arjun Bhatia: Your next question will come from Taylor McGinnis with UBS.

Operator: Your next question will come from Taylor McGinnis with UBS.

Speaker #1: Your next question will come from Taylor McGinnis with UBS.

William Magnuson: Yeah. Hi. Thanks for taking my question. Bill, so I think there's, you know, a view out there that customer engagement and marketing software is more workflow-heavy and lacking data moats that could, you know, make it more vulnerable to AI disruption. You talked a lot about, you know, the context layer and what Braze is doing there, but could you just maybe unpack that, you know, for us? Like, what proprietary data moats does Braze have, and does that give you an edge in creating some of the AI solutions you talked about, like Decisioning Studio and Agent Console? Yeah. Let me answer that on two dimensions. First, talking about context engineering, with respect to Agent Console, and then second, talking about the broad.

Taylor McGinnis: Yeah. Hi. Thanks for taking my question. Bill, so I think there's, you know, a view out there that customer engagement and marketing software is more workflow-heavy and lacking data moats that could, you know, make it more vulnerable to AI disruption. You talked a lot about, you know, the context layer and what Braze is doing there, but could you just maybe unpack that, you know, for us? Like, what proprietary data moats does Braze have, and does that give you an edge in creating some of the AI solutions you talked about, like Decisioning Studio and Agent Console?

Speaker #10: Yeah . Hi . Thanks for taking my question . Bill . So I think there's , a view out there that customer engagement and marketing software is more workflow heavy and lacking data modes that could make it more vulnerable to AI disruption .

Speaker #10: You talked a lot about, you know, the context layer and what Braze is doing there, but could you just maybe unpack that for us?

Speaker #10: Like what proprietary data modes does brace have and does that give you an edge in creating some of the AI solutions ? You talked about ?

Speaker #10: Like Decisioning Studio and Agent Console?

Bill Magnuson: Yeah. Let me answer that on two dimensions. First, talking about context engineering, with respect to Agent Console, and then second, talking about the broad.

Speaker #3: Yeah . So let me answer that on two dimensions . First , talking about context engineering with respect to agent console and then second , talking about the broad , you know , when I talk about us having a full spectrum of AI technologies and how compose them together to drive more innovation in the future .

William Magnuson: You know, when I talk about us having a full spectrum of AI technologies and how we can compose them together to drive more innovation in the future. First on the context engineering point. You know, I think context engineering, of course, we know requires comprehensive rapid access to data. I think that underscores the criticality of the Braze Data Platform, and we were very happy to share some of the scale numbers on the Braze Data Platform recently. Over 25 trillion data points processed last year and widespread adoption of the multitude of integration options that we have. You know, I think that is the beginning of the story, because context engineering requires not just access to, you know, huge amounts of data quickly, but also deliberate design.

Bill Magnuson: You know, when I talk about us having a full spectrum of AI technologies and how we can compose them together to drive more innovation in the future. First on the context engineering point. You know, I think context engineering, of course, we know requires comprehensive rapid access to data. I think that underscores the criticality of the Braze Data Platform, and we were very happy to share some of the scale numbers on the Braze Data Platform recently. Over 25 trillion data points processed last year and widespread adoption of the multitude of integration options that we have. You know, I think that is the beginning of the story, because context engineering requires not just access to, you know, huge amounts of data quickly, but also deliberate design.

Speaker #3: So first on the context engineering point , you know , I think context engineering , of course , we know , requires comprehensive , rapid access to data .

Speaker #3: I think that underscores the criticality of the data platform . And we were very happy to share some of the scale numbers on the data platform .

Speaker #3: Recently , over 25 trillion data points processed last year . And widespread adoption of the multitude of integration options that we have . And , you know , I think that the that is the beginning of the story because context engineering requires not just access to huge amounts of data quickly , but also deliberate design , and not just because of the cost and performance considerations of large context windows , but also because the deliberate management of the attention of agents , which is , you know , a relatively new concept .

William Magnuson: Not just because of the cost and performance considerations of large context windows, but also because the deliberate management of the attention of agents, which is, you know, a relatively new concept. We generally tend to think about access to data as just a kind of storage cost, latency, and throughput. This idea of attention is really important as well because you can actually have context windows rot, and unless you can keep the agents focused, you start to see outcomes go down and the quality go down. You know, it sounds great to be able to dump a 200-page PDF brand book, every historical campaign result, and every raw data point that you've ever seen about a user into a large context window and hope for the best.

Bill Magnuson: Not just because of the cost and performance considerations of large context windows, but also because the deliberate management of the attention of agents, which is, you know, a relatively new concept. We generally tend to think about access to data as just a kind of storage cost, latency, and throughput. This idea of attention is really important as well because you can actually have context windows rot, and unless you can keep the agents focused, you start to see outcomes go down and the quality go down. You know, it sounds great to be able to dump a 200-page PDF brand book, every historical campaign result, and every raw data point that you've ever seen about a user into a large context window and hope for the best.

Speaker #3: We generally tend to think about access to data as just a kind of storage cost and latency and throughput . This idea of attention is really important as well , because you can actually you can have context windows rot .

Speaker #3: And unless you can keep the agents focused , you start to see outcomes go down and the quality go down . And you know , it sounds great to be able to dump a 200 page PDF brand book and every historical campaign result and every raw data point that you've ever seen about a user into a large context window and hope for the best .

William Magnuson: That's not only slow and expensive, it also leads to lower quality outcomes and higher volatility that creates both brand risk and lower performance. By taking the environment that we built in BrazeAI with the Braze Data Platform, with Canvas and Agent Console, they're designed to solve that problem for customers. It lets them and their BrazeAI Operator rapidly build, test, and scale new agentic ideas that they have with tremendous promise to improve consumer experience, enhance their own bottom lines, and do so in a way where the context is being managed and governed in a way that is privacy and regulatory compliant, and it's being engineered in a way that it's managing the attention of the agents, and it's doing so in a way that keeps, you know, performance, quality, and consistency, top of mind.

Bill Magnuson: That's not only slow and expensive, it also leads to lower quality outcomes and higher volatility that creates both brand risk and lower performance. By taking the environment that we built in BrazeAI with the Braze Data Platform, with Canvas and Agent Console, they're designed to solve that problem for customers. It lets them and their BrazeAI Operator rapidly build, test, and scale new agentic ideas that they have with tremendous promise to improve consumer experience, enhance their own bottom lines, and do so in a way where the context is being managed and governed in a way that is privacy and regulatory compliant, and it's being engineered in a way that it's managing the attention of the agents, and it's doing so in a way that keeps, you know, performance, quality, and consistency, top of mind.

Speaker #3: But that's not only slow and expensive , it also leads to lower quality outcomes and higher volatility . That creates both brand risk and lower performance .

Speaker #3: And so by taking the environment that we built in AI with the Braze data platform, with Canvas and Agent Console, they're designed to solve that problem for customers.

Speaker #3: It lets them and their Braze, Inc. operator rapidly build tests and scale new ideas that they have with tremendous promise to improve consumer experience , enhance their own bottom lines , and do so in a way where the context is being managed and governed in a way that is privacy and regulatory compliant , and it's being engineered in a way that it's managing the attention of the agents , and it's doing so in a way that keeps performance , quality and consistency top of mind .

William Magnuson: I think that whole problem space has a lot of additional complexity in it. We're working really hard to solve that for customers, and that's what's gonna be able to drive both defensibility and rapid adoption. You know, going from there over to decisioning, you've heard me speak about the full spectrum of AI technologies that Braze is investing in, and I think that this is another advantage of both our R&D scale and the composable high-performance infrastructure that we're built on top of. When we look at decisioning, there's another paradigm rising that relies on agentic intelligence overseeing deep data science that relies on reinforcement learning. You know, for those that maybe haven't looked at Decisioning Studio closely in the past, this approach is similar to what personalizes your Instagram feed and injects ads into it.

Bill Magnuson: I think that whole problem space has a lot of additional complexity in it. We're working really hard to solve that for customers, and that's what's gonna be able to drive both defensibility and rapid adoption. You know, going from there over to decisioning, you've heard me speak about the full spectrum of AI technologies that Braze is investing in, and I think that this is another advantage of both our R&D scale and the composable high-performance infrastructure that we're built on top of. When we look at decisioning, there's another paradigm rising that relies on agentic intelligence overseeing deep data science that relies on reinforcement learning. You know, for those that maybe haven't looked at Decisioning Studio closely in the past, this approach is similar to what personalizes your Instagram feed and injects ads into it.

Speaker #3: And so I think that whole problem space has a lot of additional complexity in it. We're working really hard to solve that for customers, and that's what's going to be able to drive both defensibility and rapid adoption.

Speaker #3: And then , you going from there over to decisioning . You've heard me speak about the full spectrum of AI technologies . That Brace is investing in .

Speaker #3: And I think that this is another advantage of both our R&D scale and the composable, high-performance infrastructure that we're built on top of.

Speaker #3: When we look at decisioning , there's another paradigm rising that is relies on agentic intelligence , overseeing deep data science that relies on reinforcement learning .

Speaker #3: And for those that maybe haven't looked at decisioning studio closely in the past , this approach is similar to what personalizes your Instagram feed and injects ads into it .

William Magnuson: It's the best way to enable the decisioning system to rapidly learn from past interactions across the rest of your customer base. You know, you can't just take like, "Hey, here's the last 10 million push notifications that I sent and how everyone responded to them and everything about them," and jam it all into a context window and expect an LLM to be able to, you know, keep its attention in the right place and make sense of that. But by using decisioning and reinforcement learning around that, you're actually able to find those hidden points of resonance between the content and the engagement strategy and the individual customers, and be able to drive that interaction. You know, that's also a field that's rapidly advancing.

Bill Magnuson: It's the best way to enable the decisioning system to rapidly learn from past interactions across the rest of your customer base. You know, you can't just take like, "Hey, here's the last 10 million push notifications that I sent and how everyone responded to them and everything about them," and jam it all into a context window and expect an LLM to be able to, you know, keep its attention in the right place and make sense of that. But by using decisioning and reinforcement learning around that, you're actually able to find those hidden points of resonance between the content and the engagement strategy and the individual customers, and be able to drive that interaction. You know, that's also a field that's rapidly advancing.

Speaker #3: And it's the best way to enable the decisioning system to rapidly learn from past interactions across the rest of your customer base . You can't just take like , hey , here's the last 10 million push notifications that I sent and how everyone responded to them and everything about them , and jam it all into a context window and expect an LLM to be able to , you know , keep its attention in the right place and make sense of that .

Speaker #3: But by using decisioning and reinforcement learning around that, you're actually able to find those hidden points of resonance between the content, the engagement strategy, and the individual customers, and be able to drive that interaction.

Speaker #3: And , you know , that's also a field that's rapidly advancing . We've talked about how today it's best deployed to optimize the most valuable transition points in the customer journey , like when a free trial streaming subscriber is upgrading to premium or when an on demand or a banking customer adopts a new service or an add on product that makes them more valuable and secure at the same time .

William Magnuson: We've talked about how today it's best deployed to optimize the most valuable transition points in the customer journey, like when a free trial streaming subscriber is upgrading to premium or when an on-demand or a banking customer adopts a new service or an add-on product, that makes them more valuable and stickier at the same time. You wanna bring that kind of heavyweight data science approach into those problems exactly because they're your most valuable and they're where you wanna have the best performance uplift.

Bill Magnuson: We've talked about how today it's best deployed to optimize the most valuable transition points in the customer journey, like when a free trial streaming subscriber is upgrading to premium or when an on-demand or a banking customer adopts a new service or an add-on product, that makes them more valuable and stickier at the same time. You wanna bring that kind of heavyweight data science approach into those problems exactly because they're your most valuable and they're where you wanna have the best performance uplift.

Speaker #3: So you want to bring the that kind of heavy weight data science approach into those problems . Exactly . Because of your most valuable .

Speaker #3: And they're where you want to have the best performance uplift . But over time , we plan to continue to use decisioning science combined with agentic reasoning to increase the applicability of both approaches across more and more of the small moments in a customer journey , as well , so that customers can continue to harness these different approaches to AI and combine them together to get the best outcomes for consumers and for their businesses .

William Magnuson: Over time, we plan to continue to use decisioning science combined with agentic reasoning to increase the applicability of both approaches across more and more of the small moments in a customer journey as well, so that customers can continue to harness these different approaches to AI and combine them together to get the best outcomes for consumers and for their businesses. You know, when we look broadly across the space, I think there's so much opportunity for additional value to be created out of depth. You know, if you go back to the question from earlier about, you know, why why it's hard to build Braze and why, you know, where that incremental value comes from, and think about the leverage that you get out of the investments that are made in building first-party audiences.

Bill Magnuson: Over time, we plan to continue to use decisioning science combined with agentic reasoning to increase the applicability of both approaches across more and more of the small moments in a customer journey as well, so that customers can continue to harness these different approaches to AI and combine them together to get the best outcomes for consumers and for their businesses. You know, when we look broadly across the space, I think there's so much opportunity for additional value to be created out of depth. You know, if you go back to the question from earlier about, you know, why why it's hard to build Braze and why, you know, where that incremental value comes from, and think about the leverage that you get out of the investments that are made in building first-party audiences.

Speaker #3: And so , you know , when we look broadly across the space , I think there's so much opportunity for additional value to be created out of depth .

Speaker #3: And , you know , if you go back to the question from earlier about , you know , why , why it's hard to build , praise and why , you know , where that incremental value comes from and think about the leverage that you get out of the investments that are made in building first party audiences , combining together these optimizations and being able to compound them over time and to be deliberate about it , is exactly how you drive additional bottom line .

William Magnuson: Combining together these optimizations and being able to compound them over time and to be deliberate about it is exactly how you drive additional bottom line. It's how you drive higher loyalty in your customer relationships, and it's how you get competitive edge in these ruthless consumer markets. You know, we just believe that the brands that win in these markets are gonna be the ones that are arming themselves with the most sophisticated tooling and the strongest context engineering, you know, not just trying to throw, you know, a whole bunch of data into a context window with a frontier model and hoping for the best.

Bill Magnuson: Combining together these optimizations and being able to compound them over time and to be deliberate about it is exactly how you drive additional bottom line. It's how you drive higher loyalty in your customer relationships, and it's how you get competitive edge in these ruthless consumer markets. You know, we just believe that the brands that win in these markets are gonna be the ones that are arming themselves with the most sophisticated tooling and the strongest context engineering, you know, not just trying to throw, you know, a whole bunch of data into a context window with a frontier model and hoping for the best.

Speaker #3: It's how you drive higher loyalty in your customer relationships , and it's how you get competitive edge in these ruthless consumer markets . And so , you know , we just believe that the , the brands that win in these markets are going to be the ones that are arming themselves with the most sophisticated tooling and the strongest context engineering , you know , not just trying to throw a whole bunch of data into a context window with a frontier model and hoping for the best

Operator: Your next question will come from Brian Peterson with Raymond James.

Speaker #1: Your next question will come from Brian Peterson with Raymond James.

William Magnuson: Congrats, guys. Thanks for letting me take a question here. The really good bookings this quarter, I'm curious, has that changed your thoughts on sales hiring as you enter fiscal year 2027? Isabelle, maybe you could unpack some of the individual margin drivers by OpEx line and gross margin as we think about ramp into that 8% number for fiscal year 2027. Thanks, guys.

Brian Peterson: Congrats, guys. Thanks for letting me take a question here. The really good bookings this quarter, I'm curious, has that changed your thoughts on sales hiring as you enter fiscal year 2027? Isabelle, maybe you could unpack some of the individual margin drivers by OpEx line and gross margin as we think about ramp into that 8% number for fiscal year 2027. Thanks, guys.

Speaker #11: Congrats , guys . Thanks for letting me take a question here . But so the really good bookings this quarter , I'm curious , has that changed your thoughts on sales , hiring ?

Speaker #11: And as you enter fiscal year '27? And Isabelle, maybe you could unpack some of the individual margin drivers by opex line and gross margin as we think about the ramp into that 8% number for fiscal year '27.

Isabelle Winkles: Yeah. Just in terms of hiring, and we talked about this as we were kind of closing out, you know, getting into the end of the year last year. As we've seen rep productivity continue to improve through last year, we already put into our plan that we were gonna hire incremental sales capacity. That is underway and has been underway and continues to work productively. Definitely excited about that. And then as we think about kind of the pathway here to the 8%, look, I mean, the place where it's gonna come out of mostly is, in fact, in sales and marketing. We continue to expect to get efficiencies of scale there.

Speaker #11: Thanks , guys .

Speaker #6: Yeah . So just in terms of hiring , and we talked about this as we were kind of closing out , you know , getting into the end of the year last year , as we've seen rep productivity continue to improve through last year , we already put into our plan that we were going to hire incremental sales capacity .

Speaker #6: So that is underway and has been underway . And continues to to . Work productively . So definitely excited about that . And then as we think about kind of the pathway here to , to the 8% , look , I mean , the place where it's going to come out of most mostly is in fact , in , in sales and marketing , we continue to , to expect to get efficiencies of scale there .

Isabelle Winkles: you know, G&A, as we continue to lean on some of these strategic locations, that's gonna be helpful as well. R&D, you know, we've said is already kind of just operating where we expect it to. We're really excited about the continued scale that we continue to get out of the sales and marketing space.

Speaker #6: And then G&A as we continue to lean on some of these strategic locations , that's going to be helpful as well . R&D , you know , we've said is already kind of just operating where we expect it to .

Speaker #6: So we're really excited about the continued scale that we're going to get, continue to get out of the sales and marketing place.

Operator: Your next question will come from David Hynes with Canaccord.

Speaker #1: Your next question will come from DJ Hynes with Canaccord.

David Hynes: Hey, guys. Congrats on the next quarter and the strong guide for fiscal 2027. Isabelle, I'm gonna pull on a bookings thread as well. When you talk about a 50% year-over-year increase in bookings, obviously, the timing of renewal cohorts can impact that math. I normally wouldn't ask a bookings question, but since you shared the metric, I'll press a little bit. Any way to help us think about net new ACV growth? Like, is that growing faster than run rate revenue growth? I'm just trying to get a handle on, you know, the magnitude of the strength you saw in the quarter.

Speaker #12: Hey guys, congrats on the nice quarter and the strong guide for fiscal ’27. Isabelle, I’m going to pull on that bookings thread as well.

Speaker #12: When you talk about a 50% year over year increase in bookings , obviously the timing of renewal cohorts can impact that math . I normally wouldn't ask for bookings question , but since you shared the metric , I'll press a little bit any way to help us think about net new ACV growth ?

Speaker #12: Like is that is that growing faster than run rate revenue growth ? I'm just trying to get a handle on , you know , the magnitude of the strength you saw in the quarter .

Isabelle Winkles: Yeah. I mean, look, I think both from like renewal cohorts that then kind of added to through upsells as well as kind of the net new business, I think both were really strong. I think the overall momentum in the business in Q4 you know definitely kind of accelerated within the quarter. The renewals that we saw were very, very strong and as we continue to kind of work on the down-sell pressure that we had been seeing in years past. I think it's a combination of kind of all of those things mixing together. Obviously that strength in Q4 was certainly a part of the storyline going into this year and what helps us with the guide and our confidence in the outlook.

Speaker #6: Yeah. I mean, look, I think both from, like, renewal cohorts that then kind of added to, through upsells, as well as kind of the net new business.

Speaker #6: I think both were , were really strong . So I think the , the overall , the momentum in the business in Q4 , you know , definitely kind of accelerated within the quarter .

Speaker #6: The renewals that we saw were , were very , very strong . And as we continue to kind of work on the down sell pressure that we had been seeing in years past , so I think it's a combination of kind of all of those things mixing together .

Speaker #6: And obviously, that strength in Q4 was certainly a part of the storyline going into this year. And what helped us with the guide and our confidence in the outlook.

Operator: Your next question will come from Nick Altmann with BTIG.

Speaker #1: Your next question will come from Nick Altmann with BTIG.

Nick Altmann: Awesome. Thank you. Isabelle, can you just talk about what drove the strength in professional services revenue this quarter? Just how much of the outperformance from Decisioning Studio is in subscription revenue versus professional services? Thanks.

Speaker #2: Awesome . Thank you . Isabel , can you just talk about what drove the strength and professional services revenue this quarter ? And just how much of the outperformance from this is in studio was in subscription revenue versus professional services ?

Isabelle Winkles: Yeah. I mean, they mix in a little bit more with a little bit more professional services, but the reality is the proportion of professional services writ large across the company, the mix shift isn't changing dramatically. You know, we really sell professional services in order to sell more software. As the bookings strength you know continues to be strong, there's some element of implementation and onboarding that's mixing into that. Obviously, we're also trying to bring in more partners to bring that in. You know, I wouldn't read too much into kind of the distribution between the two.

Speaker #2: Thanks .

Speaker #6: Yeah . I mean , they mix in a little bit more with a little bit more professional services . But the reality is the proportion of professional services writ large across the company , the mix shift isn't changing dramatically .

Speaker #6: And so , you know , the we , we really sell professional services in order to sell more software . And as the bookings strength continues to be strong , there's some element of implementation and onboarding that's mixing into that .

Speaker #6: Obviously , we're also trying to bring in more partners to bring that in . So , you know , I wouldn't read too much into kind of distribution between the two .

Isabelle Winkles: The reality is, we've got, you know, things like TAM and sell, so other professional services that are actually, you know, contractual over the full term of a customer's contract life, that continues to be strong. You know, it's a mix of different things, but the reality is that we truly sell professional services in order to sell more software.

Speaker #6: The reality is , and then we've got , you know , things like Tam and sell . So other professional services that are actually , you know , contractual over the , the full term of , of customers contract life that continues to be strong .

Speaker #6: So, you know, it's a mix of different things, but the reality is that we truly sell professional services in order to sell more software.

Operator: Your next question will come from Matthew VanVliet with Cantor Fitzgerald.

Speaker #1: Your next question will come from Matthew VanVliet with Cantor Fitzgerald.

Matthew VanVliet: Great. Thanks for taking the question. Maybe touching on the question about build it yourself earlier from a different angle, how are you guys using some of these AI coding tools internally to keep your advantage from a technical perspective and just, you know, evolve just as quickly as anybody else can? How is that, I guess, impacting the rapid adoption of some of this functionality? And if anything, how does it impact your cost structure?

Speaker #13: Great . Thanks for taking the question . Maybe touching on the question about build it yourself earlier from a different angle . How are you guys using some of these AI coding tools internally to keep your advantage ?

Speaker #13: From a technical perspective and just , you know , evolve just as quickly as anybody else can , how , how is that ?

Speaker #13: I guess, is that impacting the rapid adoption of some of this functionality? And if anything, how does it impact your cost structure?

William Magnuson: Yeah. You know, I think that when we look at Braze R&D overall, that my major takeaway is just how excited I am that we've got in place a cadre of long-tenured leaders that have a ton of experience navigating through disruption. We were born in the disruption of smartphones. We've been in probably the most competitive or like one of the most competitive software categories our whole existence. You know, we've got a team that knows how to navigate disruption and knows how to win together, including both of our technical co-founders still here, both of the OfferFit co-founders still here, and a bunch of long-tenured R&D leaders that, you know, are driving ahead innovation, pace, and urgency, combined with experience of navigating disruption and really understanding our deep global customer community.

Bill Magnuson: Yeah. You know, I think that when we look at Braze R&D overall, that my major takeaway is just how excited I am that we've got in place a cadre of long-tenured leaders that have a ton of experience navigating through disruption. We were born in the disruption of smartphones. We've been in probably the most competitive or like one of the most competitive software categories our whole existence. You know, we've got a team that knows how to navigate disruption and knows how to win together, including both of our technical co-founders still here, both of the OfferFit co-founders still here, and a bunch of long-tenured R&D leaders that, you know, are driving ahead innovation, pace, and urgency, combined with experience of navigating disruption and really understanding our deep global customer community.

Speaker #3: Yeah , so , you know , I think that when we look at Bray's R&D overall , that my major takeaway is just how excited I am that we've got in place .

Speaker #3: A cadre of long-tenured leaders that have a ton of experience navigating through disruption. We were born in the disruption of smartphones.

Speaker #3: We've been in probably the most competitive , like one of the most competitive software categories are whole existence . You know , we've got a team that knows how to navigate disruption and knows how to win together , including both of our technical co-founders still here , both of the offer fit co-founders still here , and a bunch of long tenured R&D leaders that you know are driving ahead .

Speaker #3: Innovation , pace and urgency combined with experience of navigating disruption and really understanding our deep global customer community . And so , you know , with respect to the adoption of agenda coding , you see it in the results .

William Magnuson: You know, with respect to the adoption of agentic coding, you see it in the results. Like, we released the operator and the agent console months ahead of schedule. That was due to a combination of a strong beta test, but also because of the velocity increases that we're seeing. Braze engineering is also at all-time highs in pull requests per engineer per week and lines of code per week. Just like AI slop, you know, isn't producing value for differentiated investment analysis, the volume of code, I think, isn't the whole story there. The craft of building and scaling a valuable software application for professional workflows and enterprise workloads that are also transforming themselves is gonna remain incredibly valuable. It's one that we're really excited to apply to customer engagement at scale.

Bill Magnuson: You know, with respect to the adoption of agentic coding, you see it in the results. Like, we released the operator and the agent console months ahead of schedule. That was due to a combination of a strong beta test, but also because of the velocity increases that we're seeing. Braze engineering is also at all-time highs in pull requests per engineer per week and lines of code per week. Just like AI slop, you know, isn't producing value for differentiated investment analysis, the volume of code, I think, isn't the whole story there. The craft of building and scaling a valuable software application for professional workflows and enterprise workloads that are also transforming themselves is gonna remain incredibly valuable. It's one that we're really excited to apply to customer engagement at scale.

Speaker #3: Like we released the Operator and the Agent Console months ahead of schedule. That was due to a combination of a strong beta test, but also because of the velocity increases that we're seeing.

Speaker #3: Bray's engineering is also at all time highs in pull requests , per engineer per week , and lines of code per week . But just like AI , you know , isn't producing value for differentiated investment analysis , the volume of code , I think isn't the whole story craft of building and scaling a valuable software application for professional workflows and enterprise workloads that are also transforming themselves is going to remain incredibly valuable .

Speaker #3: It's one that we're really excited to apply to customer engagement at scale , and I think that , you know , we're , we're we're right in the throes of this .

William Magnuson: I think that, you know, we're right in the throes of this. We're having fun with it. We're moving at pace, and we're really excited about what this means for our entire software category to go through another reinvention. You know, a team that was born exactly because of the opportunity that came out of the disruption of mobile gets to see, you know, our product space transform again, find new opportunity. But we get to do it this time with a global customer community, with a global go-to-market organization, and with a lot more experience. But we're, you know, moving faster than ever. It's just really exciting all around.

Bill Magnuson: I think that, you know, we're right in the throes of this. We're having fun with it. We're moving at pace, and we're really excited about what this means for our entire software category to go through another reinvention. You know, a team that was born exactly because of the opportunity that came out of the disruption of mobile gets to see, you know, our product space transform again, find new opportunity. But we get to do it this time with a global customer community, with a global go-to-market organization, and with a lot more experience. But we're, you know, moving faster than ever. It's just really exciting all around.

Speaker #3: We're having fun with it . We're moving at pace and we're really excited about what this means for our entire software category to , to go through another reinvention , you know , a team that was born exactly because of the opportunity that came out of the disruption of mobile gets to see , you know , our product space transform again , find new opportunity , but we get to do it this time with a global customer community , with a global go to market organization , and with a lot more experience .

Speaker #3: But we're moving faster than ever, so it's just really exciting all around.

Operator: Your next question will come from Brian Schwartz with Oppenheimer.

Speaker #1: Your next question will come from Brian Schwartz with Oppenheimer.

Brian Schwartz: For taking my question, and congrats on a strong finish to the year. Bill, wanted to ask you a question again on the moat with AI. Maybe I would ask you the question in the form of the origin of the data models. If you think about the outputs that are coming in your AI products from the decision engine, is it possible to think about what percentage of those of the AI output is coming from signals that's being trained on data specific and proprietary to Braze versus those third-party foundation models in the market? Thanks.

Speaker #14: Thank you for taking my question, and congrats on a strong finish to the year, Bill. I wanted to ask you a question again on the moat with AI.

Speaker #14: Maybe I would ask you the question in the form of the origin of the data model . So if you think about the the outputs that are coming in your AI products and the decision engine , is it possible to think about what percentage of those of the AI output is coming from signals that's being trained on data specific and proprietary to braise versus those third party foundation models in the market ?

William Magnuson: Yeah. When you look at, for instance, everything going on in decisioning, in Decisioning Studio, you know, those are reinforcement learning models that are proprietary to Braze. They're trained with our customer's data. The data is being fed through the Braze Data Platform. When you look at Agent Console, that is a combination of the context engineering that's being done by Braze that I spoke about earlier. Of course, it's relying on the foundational models to be able to provide the broad-based reasoning and personalization capability.

Bill Magnuson: Yeah. When you look at, for instance, everything going on in decisioning, in Decisioning Studio, you know, those are reinforcement learning models that are proprietary to Braze. They're trained with our customer's data. The data is being fed through the Braze Data Platform. When you look at Agent Console, that is a combination of the context engineering that's being done by Braze that I spoke about earlier. Of course, it's relying on the foundational models to be able to provide the broad-based reasoning and personalization capability.

Speaker #14: Thanks .

Speaker #3: Yeah . So when you look at , for instance , everything going on in decisioning , in decisioning studio , you know , those are reinforcement learning models that are proprietary to braise .

Speaker #3: They're trained with our customers' data. The data is being fed through the Braze data platform. When you look at agent console, that is a combination of the context engineering that's being done by Braze that I spoke about earlier.

Speaker #3: But of course , it's relying on the foundational models to be able to provide the the broad based reasoning and personalization capability . That's a big part of the distinction that I made earlier as well , because there's no one size fits all .

William Magnuson: That's a big part of the distinction that I made earlier as well, because there's no one size fits all, and while there's a lot of work that the foundational models can do and a lot of great opportunity for them to be able to do things like, you know, personalization once you already have a recommendation algorithm has narrowed down the choices and you wanna write an email that's maybe comparing the top choices to someone so that they can compare and contrast, and you can drive up the conversion window. You know, we've also found that being able to combine reinforcement learning with the intelligence that's in the foundational models is actually the best approach to not only get the highest performance, but to be able to improve it over time.

Bill Magnuson: That's a big part of the distinction that I made earlier as well, because there's no one size fits all, and while there's a lot of work that the foundational models can do and a lot of great opportunity for them to be able to do things like, you know, personalization once you already have a recommendation algorithm has narrowed down the choices and you wanna write an email that's maybe comparing the top choices to someone so that they can compare and contrast, and you can drive up the conversion window. You know, we've also found that being able to combine reinforcement learning with the intelligence that's in the foundational models is actually the best approach to not only get the highest performance, but to be able to improve it over time.

Speaker #3: And while there's a lot of work that the foundational models can do, and a lot of great opportunity for them to be able to do things like, you know, do personalization once you already have a recommendation algorithm that has narrowed down the choices, and you want to write an email that's maybe comparing the top choices to someone so that they can compare and contrast, and you can drive up the conversion window.

Speaker #3: But you know , we've also found that being able to combine reinforcement learning with the intelligence that's in the foundational models is actually the best approach to not only get the , the highest performance , but to be able to improve it over time .

William Magnuson: I'm sure you've seen in your own experimentation with LLMs that, you know, being able to continue to understand, like, what's driving their performance and improve it over time is more of an art than a science. The explainability and observability within them and the attribution of, you know, what data really drives better outcomes for them is still a very hard unsolved problem. Within decisioning and within the reinforcement learning engine, we're able to actually see what data is moving the needle, you know, and what can be thrown out, what can be optimized, and then go and search for more signals that are along the lines of the ones that are really driving better uplift, et cetera. I think that's why, you know, we think that the right approach here is multifaceted.

Bill Magnuson: I'm sure you've seen in your own experimentation with LLMs that, you know, being able to continue to understand, like, what's driving their performance and improve it over time is more of an art than a science. The explainability and observability within them and the attribution of, you know, what data really drives better outcomes for them is still a very hard unsolved problem. Within decisioning and within the reinforcement learning engine, we're able to actually see what data is moving the needle, you know, and what can be thrown out, what can be optimized, and then go and search for more signals that are along the lines of the ones that are really driving better uplift, et cetera. I think that's why, you know, we think that the right approach here is multifaceted.

Speaker #3: I'm sure you've seen in your own experimentation with LLMs that being able to continue to understand what's driving their performance, and improve it over time, is more of an art than a science.

Speaker #3: The explainability and observability within them, and the attribution of what data really drives better outcomes for them, is still a very hard, unsolved problem within decisioning. And within the reinforcement learning engine, we're able to actually see what data is moving the needle.

Speaker #3: You know, and what can be thrown out, what can be optimized, and then go and search for more signals that are along the lines of the ones that are really driving better uplift, etc.

Speaker #3: . So I think that's why , you know , we think that the right approach is multifaceted . It's multifaceted , both from a data source perspective , which is why you see the investment and the scale and the composability in the design of the data platform , and then also one where you need to be using multiple approaches to assemble context and utilize your own bespoke training alongside , of course , the formidable intelligence that exists in the frontier models

William Magnuson: It's multifaceted both from a data source perspective, which is why you see the investment, the scale, and the composability in the design of the Braze Data Platform, one where you need to be using multiple approaches to assemble context and utilize your own bespoke training alongside, of course, the formidable intelligence that exists in the frontier models.

Bill Magnuson: It's multifaceted both from a data source perspective, which is why you see the investment, the scale, and the composability in the design of the Braze Data Platform, one where you need to be using multiple approaches to assemble context and utilize your own bespoke training alongside, of course, the formidable intelligence that exists in the frontier models.

Operator: Your next question will come from Siti Panigrahi with Mizuho.

Speaker #1: Your next question will come from Siti Panigrahi with Mizuho.

Siti Panigrahi: Hey, can you hear me? All right.

Speaker #15: Can you hear me ? All right ? Yes . Thanks for taking my question . It's good to see some of this AI momentum .

Operator: Yes.

Siti Panigrahi: Thanks for taking my question. It's good to see some of this AI momentum. I wanna ask specifically OfferFit. It's been a year almost since acquisition. What kind of discussion you are having with your installed base? What kind of traction are you seeing cross-selling to the installed base? And then specifically, on the margin side, I know there are some kind of plan there to improve it. What kind of progress you are making on improving margin for OfferFit?

Speaker #15: I want to ask specifically about offer fit. It's been almost a year since the acquisition. What kind of discussions are you having with your install base?

Speaker #15: What kind of traction are you seeing cross-selling to the installed base? And then, specifically on the margin side, I know there are some kind of plans there to improve it.

Speaker #15: What kind of progress are you making on improving margin for our profit?

William Magnuson: Yeah. I think just on the install base, that's the primary area where, you know, the sales and the upsells are happening is in fact within our install base. There's a lot of momentum. The pipeline is strong. There's a lot of interest. On the margin front, yeah, look, there's a growth element here where, as we bring on the necessary staff to enable the implementations and onboardings for customers buying it, yeah, we have to, you know, handle that expense, and that does mix into margins as well. You know, we're very focused on that, and we've been working, continuing to work on the product.

Isabelle Winkles: Yeah. I think just on the install base, that's the primary area where, you know, the sales and the upsells are happening is in fact within our install base. There's a lot of momentum. The pipeline is strong. There's a lot of interest. On the margin front, yeah, look, there's a growth element here where, as we bring on the necessary staff to enable the implementations and onboardings for customers buying it, yeah, we have to, you know, handle that expense, and that does mix into margins as well. You know, we're very focused on that, and we've been working, continuing to work on the product.

Speaker #3: Yeah .

Speaker #6: So I think just on the install base , that is that's the primary area where the sales and the upsells are happening is in fact within our install base , there's a lot of momentum .

Speaker #6: The pipeline is strong , there's a lot of interest . And then on the margin front , yeah , look , there's a there's a growth element here where as we bring on the necessary staff to enable the implementations and onboardings for , for customers buying it .

Speaker #6: Yeah . There's , we have to , you know , handle that expense . And that does mix into margins as well . But you know , we're very focused on that .

Speaker #6: And we've been working, continuing to work on the product. And we're also working on expanding product tiers to include products that are a little bit more self-service.

William Magnuson: We're also working on expanding product tiers to include products that are a little bit more self-service, and those will also mix in with higher margins as well. A number of things in flight to continue to work on that. We're just excited overall for the momentum with our existing customers shaping up.

Isabelle Winkles: We're also working on expanding product tiers to include products that are a little bit more self-service, and those will also mix in with higher margins as well. A number of things in flight to continue to work on that. We're just excited overall for the momentum with our existing customers shaping up.

Speaker #6: And that will also those will also mix in with higher margins as well . So a number of things in flight to continue to work on that .

Speaker #6: But we're just excited overall for the momentum with our existing customers, and shaping up.

Operator: There are no more questions at this time. I'll now turn the call over to Bill for closing remarks.

Speaker #1: There are no more questions at this time. I'll now turn the call over to Bill for closing remarks.

William Magnuson: Thank you, everybody, for joining us today. As I mentioned, we're excited for City by City London in about a month, and then we will see you after Q1.

Speaker #3: Want to thank everybody . Thank you , everybody , for joining us today . As I mentioned , we're excited for City by City , London in about a month .

Bill Magnuson: Thank you, everybody, for joining us today. As I mentioned, we're excited for City by City London in about a month, and then we will see you after Q1.

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