01
Can agents reach the page and read it?
Reach & read
Fetch, robots, sitemap, raw vs rendered HTML, and confirmation that Gemini / OpenAI actually read the URL.
The Agentic Commerce Index · 2026 Edition
Dataïads is certified Google Generative AI for Marketing 2026.The Agentic Commerce Index.
Are your products ready to be
by AI agents?
Enter the public URL of a product page (a single item detail page), not a category page or the homepage.
In 30 seconds, find out whether your product pages are ready to be understood, extracted and recommended by ChatGPT and Gemini, and identify the 3 quick wins that change everything.
Calibrated for
ChatGPT
Gemini
Reading · ≈ 30 sec.Modes · agent-agnostic + major AIs
Google Certification · 2026
Dataïads is certified Google Generative AI for Marketing 2026.
§ I · Why now
Commerce is becoming agentic. Your pages must keep up.
70 %
Of e‑commerce traffic will go through LLMs by 2027.
Projection Dataiads Research · 2026
2 × 3
Two parallel readings (agent-agnostic + major AIs) across three sub-scores each.
Methodology V1
30 s
Average time to generate a complete Readiness Score.
Dataiads Research · 2026
Google Generative AI for Marketing Certification · 2026
Dataïads is certified Google Generative AI for Marketing 2026.
Dataïads is part of the first wave of Google-certified partners on Generative AI applied to marketing in France. This certification, earned alongside Artefact, Jellyfish, Fifty-five, Monks and Cosmo5, recognizes the depth of our R&D on generative AI and product feeds.
The Agentic Commerce Index is one of the initiatives stemming from the Media Readiness Program 2026 : measuring how brands stay visible in ChatGPT, Gemini and AI Mode.
§ II · Methodology
The 3 questions an agent asks itself.
Each sub-score answers a concrete question an AI agent asks itself while reading your product page before it can recommend it.
02
Can agents extract reliable facts?
Product Data
Schema.org Product / Offer on the crawler side, facts extracted in strict JSON on the Gemini + OpenAI side, multi-provider confidence.
03
Can agents decide whether to recommend?
Semantic Decisioning
Use cases, target audience, differentiation, FAQ, specs, reviews - extracted from the actual content observed by the agents.
Read the detailed methodology and its editorial limits.
Full methodology →“Creative and product data now drive the targeting. The product page is the interface between your brand and the agent.”
Dataiads Research · 2026
§ Readings
The context that makes this score useful.
Four Dataïads analyses to read before or after your audit, plus the FAQ and the glossary on the resources page.
See all resources →LLMO / GEO · Dataïads ↗
SEO, GEO and AI agents: the Push & Pull playbook for 2026
Combine Push (GMC, UCP, ACP feeds) and Pull (optimized PDP) to get cited by ChatGPT, Gemini, Perplexity and Copilot.
LLMO / GEO · Dataïads ↗
LLMO for e-commerce: when SEO is no longer enough
LLMO optimizes so that LLMs choose your content as a trusted source, beyond traditional SEO.
Agentic commerce · Dataïads ↗
Sephora in ChatGPT: the first major retail integration
Discovery-first in ChatGPT, checkout at the retailer: the post-Instant Checkout coexistence model.
Agentic commerce · Dataïads ↗
OpenAI drops Instant Checkout: a pivot toward product discovery
ChatGPT refocuses on discovery; retailers keep the transaction, data and loyalty.
§ III · For e‑commerce players
Audit a product page now.
Overall score (average of agent-agnostic + major AIs), 3 sub-scores, quick wins and sector comparison. Free, no sign-up for the score.
Run the audit