Trustpilot Group plc (TRTPF) Q4 2025 Earnings Call Transcript

Trustpilot reported strong FY2025 results with bookings up 18% in constant currency and adjusted EBITDA rising 69%, returning $72M to shareholders via buybacks. Active reviews increased 20% to 361M and click-throughs from AI search grew nearly 15x as Trustpilot opened its data to LLMs, driving enterprise demand. Management also upgraded guidance, citing AI-driven demand and a strengthening growth flywheel.

Analysis

Trustpilot’s decision to open its proprietary review graph to large language models creates a thin-but-deep moat: curated human trust signals are uniquely hard for generalist models to synthesize at scale without direct access. Over 6–18 months this should translate into higher enterprise willingness to pay for API access and placement controls because brands will prioritize visibility in AI-generated answers the same way they did for paid search; that dynamic amplifies ARPU per large customer more than linear active-user growth would suggest.

Second-order winners include martech vendors and e‑commerce platforms that embed Trustpilot signals into conversion funnels — expect stronger integration deals (and potential revenue sharing) with Shopify/Shopify-adjacent partners and higher switching costs for retailers who internalize AEO (answer engine optimization). Conversely, aggregators whose monetization depends on raw traffic (ad-supported review sites, certain SEO consultancies) face margin pressure as value shifts to licensed data and API monetization rather than clicks.

Material risks concentrate around platform dependency and regulatory/data-quality vectors. If one or two LLM providers internalize or license competing datasets, pricing leverage could flip quickly; likewise, imminent AI/consumer privacy regulation and coordinated review-manipulation attacks (synthetic review poisoning) could increase moderation costs and depress monetization for 12–24 months.

Net, the setup favors an asymmetric call on a narrow set of SaaS/marketplace review assets with strong data provenance and enterprise go-to-market. Near-term multiple expansion is plausible as sellside updates AI-adoption models, but the long-term winner-take-most outcome requires sustained exclusivity of the dataset and robust defenses against data poisoning and regulatory tightening.

Key Decisions for Investors

• Long TRTPF (or local listing) — buy into a 6–18 month thesis on AEO monetization: initiate a core position sized to deliver 3–5% portfolio exposure, target 30–50% upside if enterprise ARPU expands and multiples re-rate; use a 25% trailing stop or hedge with 12–18 month OTM puts at ~15–20% cost to cap downside.
• Pair trade: long TRTPF / short YELP — YELP is more consumer-local and ad-dependent; expect relative outperformance for Trustpilot if AEO deals accelerate. Size as a market‑neutral pair, target 200–400bp outperformance in 9–12 months, cut if spread narrows by >150bps in 3 months.
• Buy TRTPF 12–18 month call spread (buy 12‑month ATM call, sell 24‑month higher strike) to capture re-rate while financing time value; this yields positive theta vs outright calls — appropriate for investors bullish on AEO adoption but cautious on long tail regulatory risk.
• Event hedge: purchase short-dated put protection around major LLM partner earnings/announcements (30–90 days) — negative partner statements or in‑house model rollouts are discrete downside catalysts that could compress multiple immediately.