35+ best products we tested in 2025: Expert picks for phones, TVs, AI, and more

ZDNET's Best of 2025 awards lists category winners across consumer and enterprise tech — notable mentions include the Samsung Galaxy Z Fold 7, iPhone 17, Oppo Find X9 Pro (smartphones); Lenovo ThinkPad X9 Aura and Alienware 18 Area 51 (laptops); Sony Bravia 8 II and TCL QM8K (TVs); AirPods Pro 3 and Sony WH-1000XM6 (audio); and AI tools such as Codex and OpenAI's Sora 2. The roundup emphasizes trends likely to influence product roadmaps and consumer purchasing (AI integration into workflows, advanced imaging/foldables, health-focused wearables, and privacy/security tools), but these editorial awards are primarily demand and perception signals rather than drivers of immediate market or earnings shifts.

Analysis

Market structure: The awards reinforce a premiumization bifurcation — winners are ecosystem leaders (AAPL, SONY, DELL, LOGI, META) that capture ASP and services upside while mid‑tier OEMs face margin compression. Expect leaders to realize a 3–7% incremental revenue uplift over the next 12 months from higher ASPs, sensor/mini‑LED demand and bundled services; this favors large-cap tech equity exposure and uplifts demand for specialty semiconductors and display materials (copper/rare earths modestly higher). Cross‑asset: stronger tech cash flows support risk assets and should modestly tighten credit spreads (IG spreads -5–10bps) while increasing skew in tech options markets.

Risk assessment: Tail risks include EU/US regulatory action on health/data collection (high impact, low prob), NAND/DRAM price collapses from inventory destocking, and China supply‑chain disruptions. Immediate (days): headline-driven knee‑jerk flows; short (weeks–months): retail holiday sell‑through and inventory reports; long (quarters–years): structural AR/AI adoption and recurring services monetization. Hidden dependency: supplier concentration (TSMC, Sony sensors, Samsung panels) creates single‑point production risk; catalyst watchlist: Dec–Jan sell‑through, March supply chain data, and Q1 earnings commentary.

Trade implications: Tactical longs: AAPL and SONY for premium hardware + services exposure; defensive hardware exposure via DELL/LOGI. Use size‑controlled option structures to buy upside (call spreads) and hedge systemic tech risk with index puts. Pair ideas: long LOGI vs short SNDK on expectations peripherals demand and slower NAND price recovery. Time trades into near‑term retail/data releases (initiate 0–30 days, trim on +12–20% moves; stop losses at -8–12%).

Contrarian angles: Consensus underestimates recurring services lift — Apple’s wearables/health could sustain margins beyond device cycles, making AAPL less cyclical than peers. Conversely AR/smart‑glasses adoption is overhyped short term; META’s hardware may disappoint vs expectations, creating idiosyncratic drawdown risk. Historical parallel: 2017 premiumization spike then midcycle inventory correction — watch inventory/sell‑through metrics to avoid getting caught in a similar drawdown. Unintended consequence: more advanced health features invite regulation and compliance costs that compress gross margins by several hundred bps over time.

Key Decisions for Investors

• Establish a 2–3% long position in AAPL shares (ticker AAPL) over a 3–9 month horizon and pair it with a 3‑month call spread: buy a 5% OTM call and sell a 15% OTM call sized to cap cost; target +12–18% upside, stop loss -8%.
• Initiate a 1.5–2% long position in SONY (SONY) shares to capture TV/imaging ASP tailwinds; target +15–25% over 6–12 months, trim 50% at +15% and use a -10% stop loss.
• Implement a 1% pair trade: long LOGI (LOGI) and short SNDK (SNDK) equal dollar size, 3–6 month horizon expecting LOGI to outperform by 10–15%; unwind if relative moves exceed +/-12% or after next quarter results.
• Buy downside protection: purchase 3‑month 5% OTM puts on QQQ sized to cover 3–5% portfolio downside (or equivalent notional) to hedge a tech drawdown heading into January retail and Q4 earnings; reassess post holiday sell‑through data.