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

# Digital shelf

> Measure your product visibility in category listings

## Use case

Digital shelf tracking lets you:

* Track per-category shelf position
* Analyze visibility across the categories a product appears in
* Optimize e-commerce SEO

## Implementation

### 1. Analyze per-category positions

Each snapshot carries a `positions` array — one entry per category the product appears in, with its rank on that category's listing. Use the `/v1/snapshots` endpoint:

```python theme={null}
import requests

API_KEY = "rx_YOUR_API_KEY"
EAN = "3401351277399"

response = requests.get(
    f"https://api.rxradar.xyz/v1/snapshots?gtin={EAN}",
    headers={"Authorization": f"Bearer {API_KEY}"}
)

data = response.json()

# Inspect every per-category position
for s in data["data"]:
    for pos in s["positions"]:
        print(f"{s['network']} · {pos['category']}: rank {pos['rank']} (page {pos['page']})")
```

### 2. Visibility report

```python theme={null}
def visibility_report(gtin):
    """Per-category visibility for a product."""
    response = requests.get(
        f"https://api.rxradar.xyz/v1/snapshots?gtin={gtin}",
        headers={"Authorization": f"Bearer {API_KEY}"}
    )
    data = response.json()

    # Flatten every (network, category) position across the snapshots.
    positions = [
        {**pos, "network": s["network"]}
        for s in data["data"]
        for pos in s["positions"]
    ]

    report = {
        "categories_tracked": len(positions),
        "first_page": sum(1 for p in positions if p["page"] == 1),
        "top_3": sum(1 for p in positions if p["rank"] <= 3),
        "avg_position": (sum(p["rank"] for p in positions) / len(positions)) if positions else 0,
    }
    return report

# Example
report = visibility_report("3401351277399")
print(f"Categories tracked: {report['categories_tracked']}")
print(f"On first page: {report['first_page']}")
print(f"Top 3: {report['top_3']}")
print(f"Average position: {report['avg_position']:.1f}")
```

### 3. Compare against competitors

```python theme={null}
def compare_visibility(ean_list):
    """Compare per-category visibility across multiple products"""
    import pandas as pd

    results = []
    for gtin in ean_list:
        response = requests.get(
            f"https://api.rxradar.xyz/v1/snapshots?gtin={gtin}",
            headers={"Authorization": f"Bearer {API_KEY}"}
        )
        data = response.json()

        positions = [pos for s in data["data"] for pos in s["positions"]]
        ranks = [p["rank"] for p in positions]
        first_page = sum(1 for p in positions if p["page"] == 1)

        results.append({
            "gtin": gtin,
            "avg_position": sum(ranks) / len(ranks) if ranks else None,
            "first_page_count": first_page,
            "categories_tracked": len(positions),
        })

    return pd.DataFrame(results)

# Compare your products vs competitors
eans = ["3401351277399", "3540550014944"]
comparison = compare_visibility(eans)
print(comparison)
```

## Endpoints used

<CardGroup cols={2}>
  <Card title="GET /v1/snapshots" href="/api-reference/snapshots/list">
    Snapshots with per-category positions
  </Card>

  <Card title="GET /v1/products/{id}/snapshots" href="/api-reference/products/snapshots">
    Position history
  </Card>
</CardGroup>