How AI shopping agents evaluate products

INTERVIEW

A conversation on product discovery | AI visibility | The future of ecommerce

AI is changing how shoppers discover and evaluate products. In this interview, Eric Sheinkop discusses how AI shopping agents assess product information, why some products are more likely to be recommended than others, and what brands can do today to improve visibility in an AI-driven shopping environment.

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Preview of AI product page audit report
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What We Score

One audit. Two ways your product page needs to perform.

Your product page is evaluated across human conversion readiness and AI retrieval readiness, giving you a clear view of how well it supports shoppers, search, and AI-driven product discovery.

Human Conversion Readiness

How well your product page helps shoppers decide.

Conversion OptimizationCTA clarity, pricing, offers, layout, and decision flow.
Content Quality and StrategyProduct education, benefits, use cases, FAQs, and shopper guidance.
Visual ExperienceImagery, video, layout, and how clearly the product is understood.
Social Proof and TrustReviews, ratings, expert validation, credibility, and confidence signals.
SEO and MetadataSearch visibility, product language, metadata, and content depth.
Technical and Mobile ReadinessPerformance, accessibility, mobile experience, and platform limitations.
Competitor BenchmarkingComparison clarity, differentiation, and category positioning.
Agentic Commerce Readiness

How well your product page can be understood, retrieved, and recommended by AI.

Structured TruthProduct attributes, claims, specs, and structured data quality.
Semantic ClarityHow clearly the page explains what the product is, who it is for, and when to choose it.
ExplainabilityThe reasoning behind why the product works and why it should be selected.
Multimodal GroundingImagery, video, demonstrations, and visual proof that support product understanding.
Execution Confidence SignalsExpert validation, reviews, proof points, policies, and credibility signals.
Machine Commerce SignalsSchema, transcripts, metadata, and machine-readable product reasoning.

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