> ## Documentation Index
> Fetch the complete documentation index at: https://citdhq.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Shopping Modes

> How AI assistants respond differently to different types of buyer intent — Carousel vs Research mode.

AI shopping results do not respond the same way to every query. Depending on buyer intent, they usually fall into two broad modes: **Carousel** and **Research**.

Understanding shopping modes helps you interpret prompt-level data and understand what kind of content is helping competitors win.

```mermaid theme={null}
flowchart LR
    Q[Buyer query] --> I{Intent}
    I -->|Purchase-intent<br/>e.g. best trail shoes under 150| C[Carousel mode<br/>Product grid · 3-6 cards]
    I -->|Research-intent<br/>e.g. what to look for in trail shoes| R[Research mode<br/>Long-form buyer guide]
    C --> W1[Win = Position 1-3<br/>Strong product data]
    R --> W2[Win = Named as top pick<br/>Authority and coverage]
```

## 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 wants options fast.

**Example query:** *"best trail running shoes under \$150"*

**What it means for ranking:** Position matters enormously here. Position 1 gets the most attention, and being absent 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. Sometimes called "long-form" or "deep research" mode.

**When it happens:** Comparison, feature-specific, and research queries where the buyer is still evaluating.

**Example query:** *"what should I look for in trail running shoes for technical terrain?"*

**What it means for ranking:** Presence matters more than exact order. Being cited in a trusted research response builds authority 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.

## Why it matters

A prompt's shopping mode tells you *what kind of influence* your ranking has.

| 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](/features/prompts) shows the mode for each query. Filter by mode to understand where your visibility gaps are most costly.

<Tip>
  If your Carousel visibility is low, start with [product data enrichment](/features/enrichment). If your Research visibility is low, focus on [sources](/features/sources) — the third-party sites and publications the AI cites when building buyer guides.
</Tip>

## Next steps

<CardGroup cols={2}>
  <Card title="Filter prompts by mode" icon="sliders" href="/features/prompts">
    Use the Prompt Workspace to filter and compare Carousel vs Research performance.
  </Card>

  <Card title="Improve product data" icon="package" href="/features/enrichment">
    Better product data lifts Carousel rankings.
  </Card>

  <Card title="Track your cited sources" icon="link" href="/features/sources">
    See which sites the AI cites — and how to get coverage there.
  </Card>

  <Card title="Understand intent types" icon="message-question" href="/concepts/prompts">
    Intent types determine which shopping mode a prompt triggers.
  </Card>
</CardGroup>
