Every score should point to something your team can inspect.
This is not an SEO audit. It is an AI readiness diagnostic. Every CEI finding connects to product-level evidence, signal breakdowns, and a prioritized fix queue mapped to owners.
A delivery package built for executives, owners, and operators.
A leadership-ready view of the CEI score, readiness band, competitive context, commercial risk, and prioritized recommendations.
Signal-level data, product-level findings, crawler diagnostics, retrieval results, and source evidence.
A prioritized plan mapping each fix to business impact, owner, effort, and expected readiness improvement.
Structured data recommendations, attribute files, terminology maps, and content briefs when Activate is in scope.
Representative findings from a CEI assessment.
A high-share category is missing material, fit, size, compatibility, or use-case attributes across many SKUs.
Multiple products use boilerplate descriptions, making them difficult for AI to distinguish.
Realistic shopping queries surface the wrong product because constraints are missing or inconsistent.
What one fixable gap looks like, end to end.
A worked illustration of how a single finding moves from diagnosis to measurable readiness.
"best waterproof hiking boots under $150 with a wide fit"
A large share of otherwise-eligible products are missing width or waterproof attributes, so AI cannot confirm they meet the constraint and leaves them off the shortlist.
Targeted PIM attribute fills plus JSON-LD enhancement on the affected product pages, delivered as ready-to-apply artifacts.
Those products become eligible for constraint-based AI queries they were previously excluded from, and the change is re-scored against the baseline.
Request a sample scorecard and product-level evidence view.
See how a CEI assessment moves from executive scorecard to operator-ready fix queue.
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