16 signals. Five pillars. One evidence-backed readiness score.
CEI separates readiness into the structural conditions AI systems need before they can recommend products accurately, then combines them into a single 0 to 100 Commerce Eligibility Index.
The conditions AI needs to read, compare, trust, and recommend.
Foundation
Is the catalog data clean and complete enough for AI to read?
Differentiation
Can AI tell products apart, or do they collapse into generic clusters?
Retrieval
Can AI find the right products for real shopping queries?
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?
The score is useful because the evidence is inspectable.
CEI combines signal scores into a 0 to 100 readiness score. Missing or unmeasurable signals are handled explicitly, not hidden as fake zeros.
High readiness across the measured signal set.
Usable foundation with meaningful improvement opportunities.
Catalog gaps are likely affecting AI discovery or accuracy.
Serious readiness gaps or insufficient evidence to score.
Get a readiness view for your own catalog.
A baseline CEI assessment turns the framework into a score, evidence, and a prioritized fix plan.
Request a CEI assessment