# Google Play Reviews Scraper & Release Regression Monitor (`herazur/google-play-reviews-regression-monitor`) Actor

Catch broken Android releases before ratings collapse. Monitor Google Play reviews by app version and request market for rating drops, complaint spikes, and regressions.

- **URL**: https://apify.com/herazur/google-play-reviews-regression-monitor.md
- **Developed by:** [Furkan Toluç](https://apify.com/herazur) (community)
- **Categories:** Developer tools, Marketing, Automation
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.50 / 1,000 app market checkeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Google Play Reviews Scraper & Release Regression Monitor

> Catch broken Android releases before ratings collapse.

Monitor Google Play reviews by app version and request market for rating drops, complaint spikes, and regressions. Scrape recent public reviews for one-off analysis, or schedule the Actor to track app versions and Google Play request contexts, surface only new feedback, and flag rating drops, 1–2 star spikes, crash/login/payment complaints, and multi-signal release regressions.

**Built for release decisions.** Get review records plus deterministic incidents, version analytics, explicit review-scope metadata, and stateful change detection without a browser or paid AI API.

### See the value in one run

Keep the prefilled Spotify input (one US/English market, 50 reviews, `onlyChanges: false`) and click **Start** to get recent reviews, a market summary, and a version comparison. The first successful run also creates a baseline; scheduled runs with `onlyChanges: true` then return only new reviews and newly active incidents. One app across US, GB, and DE request markets uses three `app_market_checked` events.

After scope validation, a review-derived incident is explicitly unscoped while retaining the `gl` request context:

```json
{
  "recordType": "INCIDENT",
  "eventType": "VERSION_REGRESSION",
  "severity": "HIGH",
  "appId": "com.spotify.music",
  "appName": "Spotify",
  "country": null,
  "requestedCountry": "us",
  "reviewScope": "UNSCOPED_PUBLIC_FEED",
  "language": "en",
  "version": "9.1.78.2218",
  "previousMetric": 0.2222222222222222,
  "currentMetric": 0.3333333333333333,
  "delta": 0.1111111111111111,
  "increasePercent": 50,
  "evidence": {
    "previousVersion": "9.1.76.2055"
  },
  "detectedAt": "2026-08-29T10:47:31.325Z"
}
```

### Who it is for

- Mobile developers and QA teams checking whether a production release escaped with defects.
- Product managers monitoring post-release feedback across Google Play request contexts without assuming reviewer residence.
- ASO agencies and mobile publishers monitoring app portfolios.
- Competitive-intelligence teams tracking the release quality of other public Android apps.

### What it detects

#### Release monitoring

`VERSION_REGRESSION`, `NEGATIVE_REVIEW_SPIKE`, `RATING_REGRESSION`, and the combined `RELEASE_REGRESSION` identify meaningful deterioration with minimum-sample guards.

#### Explicit review scope

Google Play's public review RPC accepts `gl`, but `gl` alone did not reliably isolate review feeds in validation. Review-derived records therefore use `country: null`, preserve the request as `requestedCountry`, and report `reviewScope: UNSCOPED_PUBLIC_FEED`. `COUNTRY_COMPARISON` and `COUNTRY_REGRESSION` are disabled. Identical feeds and incident keys returned through multiple requested countries are emitted only once, and `REVIEW_SCOPE_NOTICE` explains the limitation.

#### Crash, login, payment, and update complaints

English reviews are classified with transparent phrase dictionaries into:

- `CRASH_COMPLAINT`
- `LOGIN_COMPLAINT`
- `PAYMENT_COMPLAINT`
- `PERFORMANCE_COMPLAINT`
- `UPDATE_REGRESSION`
- `FEATURE_BROKEN`
- `UI_UX_COMPLAINT`
- `ADS_COMPLAINT`
- `NOTIFICATION_COMPLAINT`

Resolution phrases such as “fixed”, “resolved”, and “works now” suppress obvious false positives. No LLM, embedding service, or paid AI key is involved.

### Example input

```json
{
  "apps": [
    { "appId": "com.spotify.music", "name": "Spotify" }
  ],
  "countries": ["us", "gb", "de"],
  "languages": ["en"],
  "maxReviewsPerAppCountry": 100,
  "onlyChanges": true,
  "detectRegressions": true,
  "compareVersions": true,
  "minimumReviewsForRegression": 5,
  "negativeRatingThreshold": 2,
  "regressionThresholdPercent": 50,
  "includeReviewText": true
}
```

`appId` is the Android package ID from the Google Play URL. The Actor validates malformed IDs, two-letter country/language codes, thresholds, and impossible sample-size settings before making requests.

### First run and scheduled runs

The first successful run for each app × country × language creates a baseline in the named `google-play-regression-monitor-state-v1` Key-Value Store, which is retained across scheduled Actor runs. Its `MARKET_SUMMARY` contains `baselineRun: true`; historical reviews are not called new regressions. With `onlyChanges: true`, the baseline emits summary/comparison records but does not dump the initial review window.

On later runs, the Actor:

1. Loads the last good market state.
2. Fetches newest reviews first and deduplicates native Google review IDs.
3. Stops pagination after 25 consecutive known IDs or the configured review limit.
4. Merges the result into a bounded recent history window.
5. Calculates rating, negative-rate, version, country, and complaint metrics.
6. Writes new reviews, newly active incidents, and comparison records.
7. Commits state only after extraction, validation, analytics, and Dataset writes succeed.

If a regression stays active, it is not repeated every run. If it resolves and later returns, it can be emitted again.

### Output records

The default Dataset contains typed records:

- `REVIEW` — a newly discovered review (or fetched review when `onlyChanges: false`). A new rating at or below the threshold has `eventType: NEW_NEGATIVE_REVIEW`.
- `INCIDENT` — a deterministic regression or release-health event.
- `MARKET_SUMMARY` — baseline flag, fetched/new counts, recent rating metrics, missing-version counts, and store rating.
- `VERSION_COMPARISON` — per-version sample size, average rating, negative rate, and signal rates.
- `REVIEW_SCOPE_NOTICE` — requested countries, duplicate-feed evidence, and why country comparison is unavailable.
- `MARKET_ERROR` — an isolated, actionable failure that did not modify that market’s state.

Example incident:

```json
{
  "recordType": "INCIDENT",
  "eventType": "RELEASE_REGRESSION",
  "severity": "CRITICAL",
  "appId": "com.example.app",
  "country": "us",
  "language": "en",
  "version": "8.4.1",
  "evidence": {
    "previousVersion": "8.4.0",
    "previousNegativeRate": 0.08,
    "currentNegativeRate": 0.42,
    "previousAverageRating": 4.4,
    "currentAverageRating": 2.9,
    "topComplaintSpikes": [
      { "signal": "CRASH_COMPLAINT", "previousRate": 0.02, "currentRate": 0.27 }
    ]
  }
}
```

The `OUTPUT` Key-Value Store record summarizes successes/failures, fetched/new reviews, missing versions, incident counts, top new-review signals, requests, runtime, and memory.

### Regression heuristic

Rate regressions require all of the following:

- both compared groups meet `minimumReviewsForRegression`;
- the relative increase meets `regressionThresholdPercent` (50% by default);
- the absolute increase is at least 10 percentage points.

A rating regression additionally requires a drop of at least 0.5 stars. A `RELEASE_REGRESSION` requires at least two version indicators: negative-rate regression, rating deterioration, or a complaint spike. These rules are deterministic and intentionally conservative.

### Extraction approach

The Actor wraps [`@mradex77/google-play-scraper`](https://github.com/MrAdex77/google-play-scraper) behind its own Google Play adapter. The maintained library uses Google Play’s public HTTP `batchexecute` review endpoint and public app details page; it does not launch Chromium or require a Google account. Its responses are runtime-validated and pagination-token cycles are detected. The Actor adds its own normalization, stable fallback hashing, capped retry/backoff with jitter, per-market isolation, response-integrity guards, deduplication, early stopping, and state commits.

Requests use a shared two-requests-per-second limiter. HTTP 408/429/5xx, rate-limit, network, blocked, and timeout failures receive at most four attempts with capped exponential backoff. Exhausted failures create `MARKET_ERROR` and preserve the prior state.

### Country and language semantics

`country` is the Google Play `gl` request market. It is **not verified reviewer residence**. Google decides which localized review selection a signed-out caller sees, and caller IP can also affect regional availability. Country result sets can overlap, differ, or occasionally be identical. The Actor preserves market context and never claims it proves where a reviewer lives.

In the August 29, 2026 live validation from one Turkish egress IP, `hl=en` returned 99.5–100% overlap between US, GB, and DE for Spotify and 100% for Signal. This proves that `gl` alone did not provide reliable country isolation in that environment. A country-matched proxy/egress may be needed when strict geographic differentiation is a business requirement.

`language` is the Google Play `hl` request language. It influences the returned/localized selection but is not a guaranteed detected language for every review. Star/rating analytics work in every language. Semantic complaint classification is currently English-only; other review records have `signalClassificationSupported: false`.

### Version limitations

Google Play frequently exposes the app version associated with a review, but not for every review. Missing versions remain `null`; they are never inferred. Overall and country analytics include those reviews, while version analytics use only reviews with a public version. `reviewsWithVersion` and `reviewsWithoutVersion` make coverage visible.

The store’s displayed “current version” may be “Varies with device”. In that case it is stored as `null`, and `NEW_APP_VERSION` is not generated.

### Completeness and pagination limitations

Google Play review feeds are ranked/localized public snapshots, not an official complete historical archive. New reviews can change ordering between requests, continuation tokens may expire, and the same review can appear in overlapping pages. The Actor aggressively deduplicates and optimizes recurring monitoring, but does not promise complete historical coverage.

An app page that exists but produces an empty or malformed review response is treated as a failure—not a successful zero—so broken extraction cannot silently replace a good baseline.

### Privacy and compliance

Only public, signed-out Google Play data is requested. The Actor does not access private accounts, bypass authentication, or attempt to identify reviewers. Reviewer names can appear in output because Google publishes them, but persistent monitoring history removes review text, reviewer names, and developer-response text; state is for release metrics and deduplication, not user profiling.

### Pricing

The pay-per-event unit is `app_market_checked`: one successful app × country × language check, regardless of how many reviews it returns. On the Apify Free plan this costs **$0.005 per app market checked ($5 per 1,000)**. Paid Apify plans get lower prices: $0.0045 (Bronze), $0.004 (Silver), and $0.0035 (Gold and higher). Apify's standard Actor start event ($0.00005 per GB of run memory) also applies. Platform usage is included. Failed markets are not charged.

The Actor respects your maximum cost per run: before each market it checks that another `app_market_checked` event fits the remaining budget. When it does not, the run stops cleanly without fetching or delivering further markets, and `OUTPUT` reports `spendingLimitReached: true` and `marketsSkippedForSpendingLimit`.

No external secret or proxy is required for ordinary runs. Direct public HTTP is the default; Google may rate-limit large/high-frequency jobs, so keep schedules and market counts reasonable.

### Development

Requires Node.js 22.12 or newer.

```bash
npm install
npm run typecheck
npm test
npm run build
npm run live:smoke
```

Local Apify input belongs in `storage/key_value_stores/default/INPUT.json`. The smoke script tests Spotify and Signal against US, GB, and DE and performs an identical repeated request to report ID overlap.

The Apify SDK purges local default storage at process start unless configured otherwise. To validate state across two manual `npm start` invocations, set `CRAWLEE_PURGE_ON_START=0` for the second run. Hosted scheduled runs keep monitoring state in the named `google-play-regression-monitor-state-v1` Key-Value Store.

# Actor input Schema

## `apps` (type: `array`):

Google Play package IDs to monitor. name is an optional display label.

## `countries` (type: `array`):

Two-letter Google Play request markets. The public review endpoint may return the same global feed for different gl values; country comparisons are disabled without reliable country-matched egress.

## `languages` (type: `array`):

Two-letter languages used when requesting reviews. Semantic complaint classification currently supports English; rating analytics work for every language.

## `maxReviewsPerAppCountry` (type: `integer`):

Maximum recent reviews retained and analyzed for each app, country, and language combination.

## `onlyChanges` (type: `boolean`):

On: return only newly discovered reviews and newly active regression incidents rather than repeating known reviews. Off: return every fetched review in addition to summaries and incidents.

## `detectRegressions` (type: `boolean`):

Detect negative-review increases, rating deterioration, complaint spikes, and release regressions.

## `compareVersions` (type: `boolean`):

Analyze reviews by app version when Google Play exposes review-version information.

## `minimumReviewsForRegression` (type: `integer`):

Minimum sample size required in both compared groups before generating a regression.

## `negativeRatingThreshold` (type: `integer`):

Ratings at or below this number are negative.

## `regressionThresholdPercent` (type: `integer`):

Required relative rate increase. A 10 percentage-point absolute increase is also always required.

## `includeReviewText` (type: `boolean`):

Include public review text in Dataset review records. Text is never required for persistent reviewer profiling.

## Actor input object example

```json
{
  "apps": [
    {
      "appId": "com.spotify.music",
      "name": "Spotify"
    }
  ],
  "countries": [
    "us"
  ],
  "languages": [
    "en"
  ],
  "maxReviewsPerAppCountry": 50,
  "onlyChanges": false,
  "detectRegressions": true,
  "compareVersions": true,
  "minimumReviewsForRegression": 5,
  "negativeRatingThreshold": 2,
  "regressionThresholdPercent": 50,
  "includeReviewText": true
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "apps": [
        {
            "appId": "com.spotify.music",
            "name": "Spotify"
        }
    ],
    "countries": [
        "us"
    ],
    "languages": [
        "en"
    ],
    "maxReviewsPerAppCountry": 50,
    "onlyChanges": false
};

// Run the Actor and wait for it to finish
const run = await client.actor("herazur/google-play-reviews-regression-monitor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "apps": [{
            "appId": "com.spotify.music",
            "name": "Spotify",
        }],
    "countries": ["us"],
    "languages": ["en"],
    "maxReviewsPerAppCountry": 50,
    "onlyChanges": False,
}

# Run the Actor and wait for it to finish
run = client.actor("herazur/google-play-reviews-regression-monitor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "apps": [
    {
      "appId": "com.spotify.music",
      "name": "Spotify"
    }
  ],
  "countries": [
    "us"
  ],
  "languages": [
    "en"
  ],
  "maxReviewsPerAppCountry": 50,
  "onlyChanges": false
}' |
apify call herazur/google-play-reviews-regression-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,herazur/google-play-reviews-regression-monitor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/JRAuWaQmPowRIFwbB/builds/aMkyi5tyIPfC0RXhL/openapi.json