> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/marketing/appfollow/data-overview.md).

# Data Overview

Appfollow exposes data across five entities, covering app organization, review statistics, and rating performance. Here's what you can access through Coupler.io.

## Entities overview

| Entity          | What it contains                                                |
| --------------- | --------------------------------------------------------------- |
| Users           | Account-level user profiles in your Appfollow workspace         |
| App collections | Grouped sets of apps organized by custom or preset criteria     |
| App lists       | Individual lists of apps you're tracking in Appfollow           |
| Stat reviews    | Aggregated review counts, sentiment stats, and feedback metrics |
| Ratings         | Rating scores, historical trends, and distribution breakdowns   |

## Stat reviews

#### Review metrics

| Field                | Description                                   |
| -------------------- | --------------------------------------------- |
| Total reviews        | Total number of reviews collected for the app |
| Positive reviews     | Count of reviews with positive sentiment      |
| Negative reviews     | Count of reviews with negative sentiment      |
| Neutral reviews      | Count of reviews with neutral sentiment       |
| Average rating       | Mean rating derived from the review set       |
| Review response rate | Share of reviews that received a reply        |

#### Review dimensions

| Field    | Description                      |
| -------- | -------------------------------- |
| App ID   | Unique identifier for the app    |
| App name | Name of the tracked application  |
| Store    | App Store or Google Play         |
| Country  | Country or region of the reviews |
| Date     | Date of the review data snapshot |

## Ratings

#### Rating metrics

| Field          | Description                      |
| -------------- | -------------------------------- |
| Current rating | Latest overall rating score      |
| Rating count   | Total number of ratings received |
| 1-star count   | Number of 1-star ratings         |
| 2-star count   | Number of 2-star ratings         |
| 3-star count   | Number of 3-star ratings         |
| 4-star count   | Number of 4-star ratings         |
| 5-star count   | Number of 5-star ratings         |
| Rating delta   | Change in rating over a period   |

#### Rating dimensions

| Field    | Description                          |
| -------- | ------------------------------------ |
| App ID   | Unique identifier for the app        |
| App name | Name of the application              |
| Store    | App Store or Google Play             |
| Country  | Country or region of the rating data |
| Date     | Date of the rating snapshot          |

## App collections and app lists

#### Fields

| Field              | Description                      |
| ------------------ | -------------------------------- |
| Collection/List ID | Unique identifier                |
| Name               | Name of the collection or list   |
| App count          | Number of apps included          |
| Created at         | Timestamp of when it was created |
| Updated at         | Timestamp of the last update     |

## Common metric combinations

* **Ratings + Stat reviews** — Join on App ID to see how rating scores correlate with review volume and sentiment for each app.
* **App lists + Ratings** — Append ratings data across multiple app lists to compare performance by category or market.
* **Stat reviews over time** — Track review sentiment trends by pulling Stat reviews on a recurring schedule and appending historical snapshots.

## Use cases by role

{% tabs %}
{% tab title="Product & App teams" %}

* Monitor rating trends after each app release to catch regressions early
* Track review sentiment week-over-week to identify recurring user complaints
* Compare App Store vs. Google Play ratings side by side using the Store dimension
  {% endtab %}

{% tab title="Marketers" %}

* Pull app ratings into a Looker Studio dashboard to report on brand perception
* Use Stat reviews data to measure how campaigns affect user sentiment
* Send review summaries to ChatGPT or Claude for automated weekly reports
  {% endtab %}

{% tab title="Customer support" %}

* Track review response rate from Stat reviews to monitor team performance
* Identify spikes in negative reviews and correlate with support ticket volume
* Export review stats to Google Sheets for daily team standups
  {% endtab %}
  {% endtabs %}

## Platform-specific notes

* Stat reviews and Ratings data are store-specific — App Store and Google Play figures are reported separately
* Historical rating data availability depends on your Appfollow plan tier
* App collections and App lists are organizational entities — they don't contain review or rating metrics directly, but you can use their IDs to join with Ratings or Stat reviews
* User data reflects workspace members in Appfollow, not end users of your apps


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