ChatGPT is now a top retail referrer: your AEO playbook for assistant-sourced shopping clicks

Why this matters now

On September 24, 2025, Modern Retail reported significant assistant-driven traffic, noting that one in five of Walmart’s referral clicks in August came from ChatGPT, with similar lifts at other major retailers. See the coverage in Modern Retail reported 20% referrals. Multiple outlets have also noted that OpenAI has been exploring native checkout within ChatGPT in partnership discussions, which would move assistants from referral to transaction. See Reuters covered native checkout.

Define AEO for assistants

Answer Engine Optimization (AEO) means optimizing to be selected, summarized, and cited by assistants like ChatGPT, Copilot, and Perplexity. Unlike classic SEO, AEO prioritizes answer-ready, structured, entity-rich content that assistants can parse reliably and keep fresh. For broader strategy context, review our related guides: ChatGPT Answer Ads Playbook and model-aware AEO for Copilot.

The five-part AEO playbook

1) Build assistant-readable product Q&A and comparison content

Create explicit product Q&A that answers who it is for, what it solves, key specs, sizing, care, compatibility, warranty, and common objections. Keep answers short and declarative.
Publish head-to-head comparison pages that explain tradeoffs by audience and use case, not just spec tables.
Use clear headings, concise sentences, and a single main Product entity per page. Keep variants and bundles unambiguous.

2) Enrich Product and Offer data for price and stock freshness

On every shoppable SKU page, include Offer details: price, currency, availability, sale windows, and optional inventory signals when safe.
Add shipping details with delivery times, shipping rates, and return policies so assistants can reason about total cost and ETA.

3) Expose fast update feeds and clean deep links

Publish change feeds (RSS or Atom) by category and per SKU with correct timestamps and strong validators (ETag and Last-Modified) so assistants detect deltas quickly.
Enable push updates via a hub mechanism so subscribers receive price and availability changes rapidly.
Use canonical, stable, redirect-light deep links that resolve directly to the product view without interstitials or forced login. Support iOS Universal Links and Android App Links to open the app when installed and the website when not.

4) Instrument assistant traffic with clear UTM conventions

Standardize on: utm_source=chatgpt, utm_medium=assistant, utm_campaign=[category-or-season], utm_content=[surface]-[model]-[placement], utm_term=[query-theme].
Capture an additional ai_click_id for deduping and multi-touch modeling. Store raw assistant query text when available and permitted by your privacy policy.
Align channel taxonomy so assistant surfaces roll up separately from search and social. Maintain a dictionary of allowed values for surface and model to keep reporting clean.

5) Prepare agent-safe checkout paths and policies

Make cart and order APIs idempotent to prevent duplicate orders during retries.
Use privacy-preserving bot defenses that work for agented flows, rather than visual-only challenges.
Offer the Payment Request API on web to shorten form fill and make totals transparent for shoppers arriving from assistants.
For future delegated purchasing, design for scoped access via OAuth 2.0 and explicit user consent before allowing third-party agents to act on a shopper’s behalf.

Implementation checklist

Content: Answer-first Q&A and comparison pages per top SKU and competitor set; one clear main Product per page.
Data: Offers include price, currency, availability, sale windows, and optional inventory level; include shipping details and return policies.
Freshness: RSS or Atom feeds with ETag and Last-Modified, plus push notifications via a hub.
Links: Universal Links and App Links enabled, no forced login on first click, minimal redirects.
Measurement: Adopt the UTM and ai_click_id conventions; add assistant as a distinct channel in reporting.
Checkout: Idempotency for cart and order endpoints; token-friendly bot defense; Payment Request API enabled; policy page clarifying agent-assisted orders.

For adjacent channels and surfaces, see our Perplexity Comet optimization playbook.

What to watch next

Share of referrals from assistants by retailer category and seasonality.
Assistant click-to-show and click-to-cart rates for your pages versus marketplace alternatives.
Stability and freshness scores: time from price or stock change to feed update to assistant reflection.
Conversion and AOV for assistant traffic compared to organic search.

Bottom line

With ChatGPT already driving a meaningful share of referrals for major retailers and in-app checkout on the horizon, the winners will ship answer-ready content, assistant-readable data, and resilient checkout. Start your AEO program now and instrument it to prove lift as assistant surfaces scale.