Core Concept · AI Commerce Intelligence

WATCH AI RETRIEVE A STORE

Retrieval Intelligence is the process between a buyer's question and an AI recommendation. Scroll down and watch it run.

AI RETRIEVAL ENGINE
LIVE
Buyer query
"best vitamin C serum for sensitive skin under $60"
Discovering merchants...
82 candidates
Extracting commerce signals...
schema✓
price✓
availability✕
reviews✓
positioning?
Definition

What is Retrieval Intelligence?

Retrieval Intelligence
Retrieval Intelligence is the AI system capability to find, extract, evaluate, and synthesize ecommerce data from store pages, structured data files, and external sources to build accurate, confident product recommendations.

The AI does not randomly pick stores. It runs a structured extraction and evaluation process, reading every available signal to determine which store best answers the buyer query with the highest confidence. Stores with high AI Commerce Scores have structured their data so this process can extract it cleanly.

How it works

Follow the retrieval

Every buyer question starts a funnel. Most candidate stores are filtered out at every step. Watch how many survive to the final recommendation.

Buyer
"best eco skincare for sensitive skin"
↓
DISCOVERY
1,247 stores
↓
EXTRACTION
312 signals
↓
VERIFICATION
87 sources
↓
INTENT MATCH
41 matches
↓
RECOMMEND
8 selected
Open the black box

Why did AI keep this store?

Two real candidates, same query, same category. One got recommended. One got excluded. Here is exactly why.

CANDIDATE #017RETRIEVED
Lumine Skincare
Vitamin C Serum · $48
Product schema✓
Price✓
Availability✓
Reviews✓
Semantic clarity✓
External authority△
Intent match✓
Retrieval confidence
87%
Why retrieved
  • ✓ Exact product match
  • ✓ Price verified
  • ✓ Sensitive-skin positioning
  • ✓ Machine-readable product data
  • △ Limited external authority
CANDIDATE #018EXCLUDED
Lumine Competitor
Vitamin C Serum · price unconfirmed
Product schema✕
PriceJS
Availability?
Reviewsiframe
Semantic clarity△
External authorityLOW
Intent matchLOW
Retrieval confidence
31%
Why not
  • ✕ Price locked behind JavaScript rendering
  • ✕ No product schema found
  • ✕ Reviews hidden inside an iframe
  • ✕ Generic positioning, no intent match
  • ✕ No external authority signals
Same category. Same buyer. Different retrieval outcome.
How different AI systems retrieve

How AI gets its data

Not all AI shopping systems retrieve the same way. Click a node to see what feeds it.

MEMORY
ChatGPT, Claude
LIVE WEB
Perplexity, Bing AI
HYBRID
Google AI Mode
Data source stream
ChatGPT retrieves from training data built months in advance. Brand entity, press mentions, Reddit discussion, and schema markup from past crawls all feed this. Changes are slow to reflect.
brand entity press mentions Reddit discussion historical schema
Perplexity crawls the web in real time at query submission. Current page content, live external citations, and fresh schema data all matter. Changes reflect within days.
HTML content schema markup price availability citations
Google AI Mode blends training data with live search index signals. Schema markup, organic authority, and structured commerce data all contribute. Both SEO and GEO signals matter.
training data search index organic authority structured commerce data
Why this matters for your strategy: Improving Perplexity visibility is faster because it reads real-time data. Improving ChatGPT visibility takes longer because it requires building brand entity in training data. Knowing which system your buyers use most tells you where to focus first.
FAQ

Retrieval Intelligence: common questions

What is Retrieval Intelligence in AI commerce?
Retrieval Intelligence is the AI system capability to find, extract, evaluate, and synthesize ecommerce data from store pages, structured data files, and external sources to build shopping recommendations. It is the underlying process that determines whether your store gets discovered, read, verified, and recommended when buyers ask AI shopping agents for product recommendations.
How do I optimize my store for AI Retrieval Intelligence?
Optimizing for Retrieval Intelligence means making each step of the pipeline easier. For Discovery: ensure your store is indexed and has an llms.txt file. For Extraction: add JSON-LD schema and ensure prices and policies are in server-rendered HTML. For Verification: build Reddit presence and press coverage. For Intent Matching: write specific buyer-intent-aligned positioning. For Recommendation Scoring: fix the factors with the highest failure rates first.
What data can AI retrieval systems actually read?
AI retrieval systems read JSON-LD schema markup, server-rendered HTML text including prices and policies, heading hierarchy, image alt text, and files like llms.txt. They cannot reliably read JavaScript-rendered content, content in iframes, PDFs, or content behind login walls. Anything AI cannot read registers as missing data, which lowers recommendation confidence.
Your store is already being retrieved.
The question is: what does AI retrieve?
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Related
AI ExtractabilityCan AI actually read your signals? AI Structured SignalsThe technical foundation AI needs Human View vs AI ViewSee the retrieval gap visually AI Commerce ScoreHow retrieval quality is measured AI Commerce IntelligenceHow to build for AI retrieval VocabularyEvery AI Commerce term defined