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

# Prospects & Demand Intelligence

> Opportunity scoring, heat map, CSV export for CRM.

Prospect endpoints combine readiness data (from scans) with demand signals (public intelligence, synthetic tests, AI search mentions, telemetry) to produce an **opportunity\_score** — the product of demand and readiness gap:

```
opportunity_score = demand_score × (1 − readiness_score / 100)
```

High opportunity = the merchant is getting agent interest *and* would benefit most from an agentic-commerce integration.

## GET /v1/scanner/prospects

**Scope required:** `read`   **Cost:** 0

Query parameters:

| Param             | Notes                                |
| ----------------- | ------------------------------------ |
| `category`        | `retail`, `saas`, `marketplace`, ... |
| `region`          | `latam`, `north_america`, ...        |
| `min_opportunity` | Minimum `opportunity_score` (0–100)  |
| `priority`        | `critical`, `high`, `medium`, `low`  |
| `limit`           | Default 50, max 200                  |

```bash theme={null}
curl -H "Authorization: Bearer $SCANNER_KEY" \
  "https://scanner.getsly.ai/v1/scanner/prospects?priority=critical&region=latam&limit=50"
```

Each prospect is a [`ProspectScore`](/scanner/data-model#prospect-score-from-prospects).

## GET /v1/scanner/prospects/heat-map

Category × region matrix: aggregate readiness, demand, opportunity, and top priority per cell.

**Scope required:** `read`   **Cost:** 0

```json theme={null}
{
  "data": [
    {
      "category": "retail",
      "region": "latam",
      "merchant_count": 82,
      "avg_readiness": 41,
      "avg_demand": 68,
      "avg_opportunity": 58,
      "top_priority": "high"
    },
    ...
  ]
}
```

Sort order is descending by `avg_opportunity`.

## GET /v1/scanner/prospects/export

CSV for CRM import. Same filters as `/prospects`.

**Scope required:** `read`   **Cost:** 0

```bash theme={null}
curl -H "Authorization: Bearer $SCANNER_KEY" \
  "https://scanner.getsly.ai/v1/scanner/prospects/export?priority=high&limit=500" \
  -o prospects.csv
```

Columns: domain, merchant name, category, region, readiness score, demand score, opportunity score, sales priority, and the four demand-sub-score components.

## Priority thresholds

| Opportunity score | Priority |
| ----------------- | -------- |
| > 80              | critical |
| 61 – 80           | high     |
| 41 – 60           | medium   |
| ≤ 40              | low      |

## Demand score composition

```
demand_score = 0.30 × public_intelligence
             + 0.25 × synthetic_test
             + 0.25 × observatory
             + 0.20 × telemetry
```

* **public\_intelligence** — matches against the demand\_intelligence data points for the merchant's category/region.
* **synthetic\_test** — weighted on how often agents fail at the merchant's checkout (more failures = more demand for an integration).
* **observatory** — AI search engine mentions (ChatGPT, Perplexity, Claude) and MCP-registry listings for the domain.
* **telemetry** — real agent checkout attempts observed in production traffic.