PR008 – Product Recommendation Engine

Overview

Assessment for product recommendation engine. Validates that recommendation blocks (e.g. "Recommended for you", "Frequently bought together") are present and functioning (links, data consistency).

Probability that AI systems use this signal: Crawlers and generative AI pipelines consume structured and visible page signals for training and inference. Assessment-specific signals (e.g. schema, canonicals, trust cues) affect how likely a page is indexed and surfaced. The probability that this assessment's signal influences AI behavior is high when the page is in a product or compliance context.

Impact on geo compliance: Passing this assessment supports geo compliance by ensuring machine-readable and visible content meet standards that reduce the risk of wrong locale, pricing, or trust in AI-generated answers. Failing can lead to non-compliant or misleading surfacing.

What We Check

• See implementation: recommendation section detection, link and data validation.
• Full logic: `src/domain/assessments/product_relationships/pr008_product_recommendation_engine.py`.

Pass / Fail and Score

• From execute().

How to Fix When It Fails

• Implement or fix recommendation sections; ensure recommendations are valid and linked.

Common Issues

• Missing recommendations; invalid or broken recommendation links.

Dependencies

None.

How to Verify

• Check recommendation blocks are present and functioning; validate links and data consistency.

Related Assessments

PR007 (related), PR009 (upsell).

Additional Resources

• Recommendation blocks ("Recommended for you", "Frequently bought together"): ensure links resolve and product data is consistent; optional schema.org Product isRelatedTo/isSimilarTo for recommended items.
• Related: PR007 (related products), PR009 (upsell).