Observed Signal · Sep 17, 2026 · Market Signal · Source: AppNexus · Impact: 3/5
Four foundations to get your brand AI-ready for the holidays
Prepare your brand for AI-driven holiday shopping by strengthening four foundations: product feeds, measurement, campaign performance, and AI visibility. Published September 17, 2026.
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How Brands Become Visible to AI Shopping Agents
Sponsored by Adobe Commerce, the article explains how AI shopping assistants (e.g., ChatGPT, Gemini) are reshaping product discovery and creating a new discoverability requirement for retailers. Adobe reports AI-referred traffic to U.S. retail sites rose 393% year-over-year in Q1 2026 and converts 42% better than other traffic. Adobe’s research finds the average AI readiness score for U.S. retail product pages is 66% (best 82.5%, lowest 54.2%), indicating many product pages are not machine‑readable. The piece advises prioritizing high-value SKUs, adding structured, explicit product attributes (titles, specs, use cases, availability), and running audits with tools like Adobe’s AI Content Visibility Checker. Quotes come from Adobe’s Shaun McCran and Alex Jose, and the article cites BCG warnings about risks in the agentic commerce era.
Four holiday reports reveal split on AI adoption
Four vendor reports (Basis, Salesforce, Attentive, Alchemer) agree that holiday shoppers are starting earlier, spending more deliberately, and expecting more relevant experiences. They diverge sharply on AI: Attentive reports high usage (around 70%) across the shopping journey, Basis finds only 17% expect to use AI while shopping, Alchemer measures trust in AI recommendations at 35.4%, and Salesforce frames AI agents as an emerging product-discovery channel. The differences largely reflect varying questions and measurement approaches (usage, intent, trust, or future channel readiness). The reports imply marketers should prepare product information and fundamentals (accurate product data, reviews, personalized offers) for AI-driven discovery even as consumer adoption and trust remain uneven.
Preparing Brands for AI Discovery and Action
The article explains how search is shifting from page rankings to AI-driven recommendations and lays out a three-layer framework — Eligibility, Recommendation, Transaction — for brands to be discoverable, trusted, and actionable by AI systems. It highlights technical changes such as query fan-out, grounding limits, machine-friendly delivery, and differing AI operator intents. The piece recommends structured data, entity clarity, corroboration across sources, and machine-executable interfaces (APIs, authentication, commerce protocols) while urging new measurement approaches that track citations, readiness, and business impact rather than clicks alone.
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