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GEOly Function Description

Shopping

Shopping Operation Guide

The Shopping Analysis module helps teams understand how products appear in AI shopping recommendations and product-card style answers. Data is based on monitored AI responses and the selected topic, platform, and time range. It is not a real-time global ecommerce ranking.

I. Popular Product Monitoring

shopping 1

This section shows products that appeared in AI shopping cards within the configured monitoring scope.

1. Product Performance Metrics

  • Occurrences: Counts how often a product card appears in monitored responses.
  • Ranking Logic: Products are sorted by observed appearances in the sample. This is not an independent ecommerce popularity score.
  • Product Matching: Product links are used first when available; if a valid link is missing, the product title is used for matching.
  • Ratings & Review Counts: These values come from the product-card fields returned by the AI surface at collection time. GEOly does not independently generate the rating.
  • Data Completeness: If a product card does not include rating or review data, the interface may show the product without stars or review counts.
  • Statistical Scope: Only responses that produce shopping/product-card data are included in shopping-card counts.

II. Product Detail & Platform Attribution

shopping 2

Product detail views help identify where a product appeared and which platforms contributed to the observed shopping-card activity.

  • Platform Labels: Show platforms where the product appeared at least once in the selected monitoring sample.
  • Source Context: Use the detail view to review the query, platform, product metadata, and supporting answer context where available.
  • Interpretation: Platform attribution is sample-based. Do not treat it as a site-wide or market-wide sales statistic.

III. Shopping Keyword Insights

shopping 3

Shopping keyword insights show which prompts and user intents are more likely to trigger product-card answers.

1. User Intent Recognition

  • Demand Distribution: Groups shopping-triggering queries by themes such as accessories, comparison, purchase advice, use case, or product feature.
  • Intent Proportion: Helps identify what buyers are asking before AI recommends products.
  • Shopping Answer Ratio: Separates responses that include shopping/product-card content from ordinary text-only answers.
  • Optimization Use: Prioritize product pages, schema, FAQs, and comparison content around the query themes that repeatedly trigger shopping cards.

IV. Operational Notes

  • Use the top date and platform filters before comparing results.
  • Public shopping and topic-commerce data may depend on plan, topic coverage, locale, and platform availability.
  • If a query or platform has no shopping-card data, that means no eligible shopping response was collected for the selected scope.

Table of Contents

I. Popular Product Monitoring
1. Product Performance Metrics
II. Product Detail & Platform Attribution
III. Shopping Keyword Insights
1. User Intent Recognition
IV. Operational Notes