When a shopper asks ChatGPT "what's a heart-healthy weeknight dinner for four?", the products in the answer aren't picked from a search index. They're picked from whichever brand emitted conversational attributes the LLM could chunk, verify, and cite. Delectable AXP turns every retailer SKU into a cite-able entity — at parity with the brands that already buy this surface area at Amazon.
The Princeton/Georgia Tech KDD 2024 study quantified what every brand discovers eventually: AI answer engines don't crawl the page like Googlebot. They pull 40–60-word "chunks" of structured, machine-readable claims, and they cite whichever ones they can verify across sources. A product page written for human eyes returns nothing. A product entity emitted as conversational attributes returns citations.
Brand-voice paragraphs, hero images, bullet-list features. Indexable by Googlebot, ignored by RAG-based answer engines.
<!-- product page · marketing copy -->
<h1>Heart-Healthy Olive Oil</h1>
<p>Bring the taste of the
Mediterranean to your kitchen
with our premium cold-pressed
extra-virgin olive oil. Perfect
for drizzling, dipping, or
finishing your favorite dishes.</p>
<p>Available in 16oz and 25oz.</p>
Same product, emitted as MerchantListing JSON-LD plus conversational attribute feeds. Verifiable specs, pre-chunked Q&As, machine-readable variants.
// /.well-known/merchant payload { "@type": "MerchantListing", "name": "Extra-Virgin Olive Oil 25oz", "healthClaims": ["heart_healthy", "low_sat_fat"], "variant_option": { "size": ["16oz", "25oz"], "acidity_pct": 0.3 }, "question_and_answer": [{ "q": "Is it heart-healthy?", "a": "Yes — <3g sat fat / tbsp, FDA qualified." }] }
We don't invent these formats. They're the structured shapes Google's Merchant Center already accepts, the JSON-LD schemas every major search engine indexes, and the comparison-table shape LLMs prefer for matrixed reasoning. AXP emits all four, for every SKU, automatically — from the same Food HyperGraph that builds the Perfect Cart.
Authoritative product entity embedded as JSON-LD in the PDP. Captures price, availability, claims, certifications — the canonical machine-readable shape every major engine indexes.
Pre-chunked Q&A pairs — 40–60-word answers to the questions shoppers ask. Mimics the exact format LLMs cite from. Generated from FAQ data, support tickets, and Food HyperGraph relationships.
Structured variant matrices: size, pack count, dietary certification, regional sourcing. Lets the LLM filter "gluten-free under 10oz, sodium <140mg" without scraping prose.
Self-comparison tables on the PDP — this SKU vs three alternates — in the table shape LLMs prefer for matrixed reasoning. Includes private-label vs national-brand parity rows.
Six representative SKUs. Click one to see the conversational-attribute payload AXP emits, alongside a simulated ChatGPT response that cites the product when a shopper asks an unbranded query. Every cite is grounded in the structured payload — no hallucinations, no guesswork.
The retailer who indexes well for "best low-sodium pasta" on Google still loses the basket if ChatGPT, Perplexity, and Gemini don't cite their SKUs in the agentic answer. Tracking citation rate across major LLMs — Share of Model — is the new equivalent of share of voice for the agentic-checkout era.
The same AXP brain that builds the Perfect Cart for each retailer also publishes their cooperative-wide conversational-attribute manifest. Private label gets cite-able. Regional SKUs get discoverable. The middleman tax on agentic discovery disappears.