Machine Truth for the AI Shelf

AI is evaluating your product catalog right now.

Are you prepared?

The Commerce Eligibility Index™ (CEI) is a 0–100 score measuring whether AI shopping agents can find, understand, trust, and recommend your products. It turns the findings into evidence, fix queues, and governance your teams can act on. Get recommended by more AI assistants, more often, and you grow revenue where buying is moving fastest.

16Readiness signals
5Operating pillars
0–100Commerce Eligibility Index
Sample CEI ScorecardPARTIALLY READY
68/100
Commerce Eligibility Index
Foundation68
Differentiation54
Retrieval61
Integrity74
Authority58
SKU-4471: 3 of 7 required attributes missing · retrieval miss on 2 of 5 shopping queries
The shelf has moved

The front door to commerce is now an AI agent.

Product catalogs were built for human browsing, not machine reasoning. When an assistant has to choose what to recommend, ambiguous data gets the product ignored, misrepresented, or left off the shelf entirely.

The old path
User → Search → Website → Product
The new path
User → AI Agent → Recommendation
What you get

Get recommended. Win the traffic. Protect the revenue you can't see.

CEI is analytical on purpose. The payoff is plain: when AI can find, trust, and recommend your catalog, you reach the fastest-growing, highest-intent channel in commerce, grow sales there ahead of competitors, and stop losing the ones you never see.

Get recommended by AI

When ChatGPT, Claude, Gemini, and Perplexity can confirm your products fit, you make the shortlist instead of your competitor.

Win the high-intent traffic

AI-referred shoppers convert 31% better and spend more per visit (Adobe Analytics, 2026). CEI helps you capture them before the click.

Protect the revenue you can't see

Most AI losses are invisible: the shopper never lands on your site. CEI surfaces the pre-click leakage and the fixes to recover it.

The CEI Framework

Five pillars AI systems need before they can recommend.

CEI separates readiness into the structural conditions that decide whether your catalog is legible to machines, scored across 16 evidence-backed signals.

Foundation

Is the catalog data clean and complete enough for AI to read?

Differentiation

Can AI tell your products apart, or do they blur together?

Retrieval

Can AI find the right product for a realistic shopping query?

Integrity

Are the claims in your catalog internally consistent and verifiable?

Authority

Does the broader internet give AI reasons to trust and cite your brand?

A closed loop for catalog readiness

Diagnose. Activate. Protect.

Start with an evidence-backed baseline, turn findings into fix artifacts your teams can apply, then gate new catalog updates so quality never drifts backward.

CEI Diagnose™
Measure the gap
  • Commerce Eligibility Index score
  • Five-pillar, 16-signal breakdown
  • Competitive benchmark
  • Executive report + technical evidence
10–14 business days
CEI Activate™
Generate the fixes
  • Structured data and JSON-LD
  • Attribute gap files
  • Terminology standardization map
  • Description and alt-text queues
2–6 weeks
CEI Protect™
Prevent regression
  • Brand quality profile
  • Pre-publish validation gate
  • Pass, warn, or fail status
  • Publish decision guidance
Ongoing, per PDP
Who it is for

Built for the people accountable for AI-era discoverability.

CDOs, CMOs, and heads of ecommerce who own the number, and the merchandising, product-data and PIM, and agency teams who act on the findings. Today that is mostly retailers and consumer brands; the same readiness gap is opening across more categories as AI-mediated discovery expands.

Every claim has receipts

This is not an SEO audit. It is an AI readiness diagnostic.

Every score points to something your team can inspect: product-level evidence, signal breakdowns, and a prioritized fix queue mapped to owners. Measure, do not guess.

Executive scorecard

Readiness band, drivers, risk themes, and the next decision for leadership.

Signal receipts

Evidence-backed product findings that explain exactly why the score moved.

Fix queue

Attribute, copy, evidence, and governance work mapped to likely owners.

Turn your catalog into machine truth

See exactly what AI systems understand about your catalog.

A baseline CEI assessment turns catalog readiness into an executive scorecard, product-level evidence, and prioritized fix queues.

Request a CEI assessment