Every engine that recommends products, tracked.
The engines are not interchangeable: ChatGPT's card behavior isn't Perplexity's citation tail, and Gemini's entity grounding isn't Copilot's Bing index. eCommerce Insights tracks each one per product, per query, so you optimize for the engines where your buyers actually are. Behavior notes on every page reflect mid-2026 and get updated as the engines move.
Eight engines, ordered by D2C relevance.
ChatGPT and Perplexity lead because that's where D2C shopping research concentrates today. Shopping-surface notes are as of mid-2026.
| Engine | Vendor | Shopping surface | Tracking |
|---|---|---|---|
| ChatGPT | OpenAI | ChatGPT Shopping cards, Instant Checkout (ACP), Operator | every plan |
| Perplexity | Perplexity | Perplexity Shopping, Buy with Pro, 3–7 cited sources | every plan |
| Google AI Overviews | AIO summaries, AI Mode, Shopping carousel via Merchant Center | every plan | |
| Gemini | Inline citations in app and Workspace; UCP in pilot | every plan | |
| Claude | Anthropic | Web-search citations, comparison Artifacts | every plan |
| Copilot | Microsoft | Bing-grounded answers in Copilot, Bing, and Edge | every plan |
| Rufus | Amazon | On-Amazon assistant, COSMO-graph grounding | on request |
| Sparky | Walmart | On-Walmart assistant across site and app | on request |
How each engine picks products — and what moves it.
ChatGPT
Shopping cards, Bing-grounded browsing, Operator. Schema completeness and recent reviews are the levers.
02Perplexity
Citation density is the game: your PDP plus the review sites Perplexity already trusts in your category.
03Google AI Overviews
AIO and AI Mode tracked separately from classic SERPs; Merchant Center feeds the carousel.
04Gemini
Entity clarity drives citations. Shares infrastructure with AI Overviews; behaves differently.
05Claude
Research-heavy buyers, editorial-weighted citations, comparison Artifacts.
06Copilot
Bing's index behind every answer. Usually fixed with 20 minutes of Bing Webmaster Tools.
07 · MarketplaceRufus
Amazon's assistant, scored through the COSMO relation graph. Pairs with the Amazon channel page.
08 · MarketplaceSparky
Walmart's assistant, tracked on request for Marketplace sellers. Secondary by design.
Grounding reference: OpenAI's ChatGPT search announcement describes URL-level grounding — the model most engine pages on this site extend with D2C-specific tracking detail.
Related pages.
How to rank products in ChatGPT
The pillar guide: engine-agnostic principles plus engine-specific tactics.
GuideSchema for AI search
Product schema completeness is the cheapest lever on almost every engine.
Free toolChatGPT visibility checker
Is this product in ChatGPT's answers right now? Check free.
Frequently asked questions
How do AI engines differ in how they cite products?
Meaningfully, and per engine. As of mid-2026, ChatGPT Shopping typically surfaces a small set of product cards and rewards structured data and recent reviews; Perplexity cites 3–7 sources per shopping answer and weights third-party review coverage heavily; Google AI Overviews draws on the Google index plus Merchant Center; Gemini leans on entity clarity; Claude skews toward editorial sources; Copilot grounds on Bing. The engines are tracked individually because the levers differ.
Which AI engine matters most for a D2C brand?
For most D2C brands, ChatGPT and Perplexity drive the largest AI-attributable consideration today, with Google AI Overviews growing fast on commerce queries. Gemini, Claude, and Copilot are smaller but cheap to cover since every plan tracks all six. Rufus and Sparky matter when Amazon or Walmart is a real channel for you.
Why aren't Rufus and Sparky on every plan?
They're marketplace engines that only apply to brands selling on Amazon or Walmart. Both are available on request and standard on the Agency & Enterprise tier; Amazon SKUs route through Rufus and COSMO scoring with Seller Central edit recommendations rather than schema advice you can't ship there.
Can I filter the dashboard to only the engines I care about?
Yes. Every dashboard and digest filters to one or more engines. The underlying scan still covers all six core engines, so re-enabling one later doesn't start from zero history.
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8 engines · per-product · per-query