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Shopping analytics

The shopping analytics home — summary tiles, a trend, a top-30 product leaderboard, the most recent carousels, and a CSV export of your AI shelf presence.

The shopping analytics home is where you read your AI shelf at a glance: who wins, how your presence is moving, and which specific carousels drove it.

What it does

The home surface brings together:

  • Four summary tiles,
  • a trend of your shopping presence over time,
  • a top-30 product leaderboard,
  • the 40 most recent carousels, and
  • a CSV export.

How to use it

  • Read the leaderboard for who wins the shelf.
  • Read the Engine coverage strip to know which engines the numbers come from — a count, "not sampled", or "awaiting vendor data" per engine. See Engine coverage.
  • Read the trend for how your presence moves.
  • Read the recent carousels to audit specific shelves — each is a captured carousel you can inspect.
  • Use the CSV export at /api/export/shopping to pull the underlying data.

How it's computed

  • Metrics run over a 7-day window; the leaderboard shows the top 30 products.
  • On a day where a carousel appeared but your product did not, share and win rate are an honest 0 (a measured zero), while average slot stays null — there is no average of nothing. This mirrors the null-is-not-zero rule in how MentionFlow handles missing data.
  • A shopping-gap recommendation fires when there were ≥3 carousels and you had zero own placements — a clear signal that a shelf exists and you are absent from it.

Limits

  • Not plan-gated.
  • Live workspaces only — the demo shows labelled sample data.
  • Sources: ChatGPT, Google AI Overviews, Google AI Mode, and Copilot collect today; Perplexity and Gemini are wired but awaiting vendor payloads — see Engine coverage.
  • CSV export is served at /api/export/shopping.

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