Carousel mode
In carousel mode, the AI returns a visual grid of product cards — typically 3–6 products with names, images, prices, and a brief description. This is the AI equivalent of a search results page. When it happens: Purchase-intent queries, where the buyer is ready to buy and wants options fast. Example query: “best trail running shoes under $150” What a win looks like: Position matters enormously here. Position 1 gets the most attention. Being absent from a carousel prompt is a meaningful miss. How to optimize: Strong product listings, structured data, accurate pricing, and review counts are the primary ranking signals in carousel responses.Research mode
In research mode, the AI returns a long-form buyer guide — a detailed text response that compares options, explains trade-offs, and makes a recommendation. This is sometimes called “deep research” mode. When it happens: Comparison, feature-research, and general-research queries, where the buyer is still evaluating. Example query: “what should I look for in trail running shoes for technical terrain?” What a win looks like: Presence is more important than position here. Being cited in a trusted research response builds brand authority and influences buyers earlier in the funnel. How to optimize: Authority signals matter most — third-party reviews, editorial coverage, and expert citations. Brands that are well-covered by authoritative sources rank well in research responses.Summary
| Mode | Buyer stage | Primary ranking signal | What a win looks like |
|---|---|---|---|
| Carousel | Ready to buy | Product data quality | Position 1–3 in a purchase query |
| Research | Still exploring | Brand authority & coverage | Named as a top recommendation in a buyer guide |
Your prompt table shows the mode for each query. Filter by mode to understand where your visibility gaps are most costly.