Playstore Reviews Scraper

Scrape Google Play Store app reviews into a clean, analysis-ready dataset you can filter, export, and send downstream.

Actor: https://apify.com/fetchcraftlabs/playstore-reviews-scraper

Last reviewed: April 21, 2026.

Quick answer

Use this actor when you need public Google Play reviews in a structured format instead of copying comments by hand. It is a good fit for product teams tracking app feedback, analysts building review dashboards, and operators watching for rating drops or complaint spikes.

At a glance:

Input: one or more Google Play app URLs or app IDs.
Output: structured review rows with rating, content, locale, app version, timestamps, and reviewer metadata.
Best for: recurring review exports, competitor review monitoring, and sentiment/theme analysis.
Not ideal for: private app data, reply management, or one-off manual checks where a spreadsheet export would be overkill.

What it does

The Playstore Reviews Scraper gathers fresh public feedback directly from Google Play Store listings. Provide the store URL (or app ID), choose how many reviews you need, and it returns items with review text, ratings, timestamps, locale, and reviewer metadata.

Each run can collect up to 25,000 records per app, which makes it practical for trend analysis instead of anecdotal review checking.

Who this is for

This actor is useful when the question is bigger than "what do the latest reviews say?"

Product teams: track bug reports, feature requests, and post-release sentiment.
Growth teams: compare review themes before and after campaigns or launches.
Support and operations: watch for low-rating spikes and cluster complaints by keyword.
Researchers and agencies: benchmark multiple apps, locales, or rating bands from one repeatable workflow.

What you get

Output area	What it includes	Why it matters
Review content	headline/body text, score, helpful votes	Analyze sentiment, complaints, and testimonials
Review context	locale, country, app version, timestamp	Segment feedback by market, release, or time period
Reviewer metadata	review/user identifiers returned by the source	De-duplicate and track recurring patterns
Export-ready structure	JSON/CSV dataset rows	Push into BI tools, Sheets, databases, or alerting workflows

Core benefits:

Complete review history: compare recent feedback with older reviews.
Structured fields: rating, headline/body text, user, app version, locale, date, and helpful votes.
Flexible slicing: scrape single apps, multiple locales, or a specific rating bucket.

Common use cases

Analytics & dashboards: monitor rating, volume, and top themes weekly.
Market & product research: benchmark competitor apps and discover feature requests.
Support & operations: alert on 1-star spikes and cluster issues by keyword.
Growth & marketing: find testimonials and track sentiment after campaigns.

When to use it vs. when not to

Use it when you need repeatable data collection from public Play Store reviews.

Use this actor when:

You want a structured export instead of manual copy/paste.
You need enough review volume to compare time periods, locales, or star ratings.
You plan to send the output into dashboards, spreadsheets, or downstream automation.

Look for another workflow when:

You need private account data or anything behind authentication.
You only need a handful of reviews and manual inspection is faster.
You need moderation, response management, or CRM actions rather than data extraction.

Typical workflow

Enter the Google Play Store URL (or app ID).
Set how many reviews to gather and optional filters (language, country, min rating).
Run the Actor and export results to JSON/CSV or pipe to your analytics stack.

Input and output overview

Step	What you set	Notes
1	`appUrls`	Accepts Play Store URLs or app IDs
2	`maxReviewsPerApp`	Controls how deep the export goes per app
3	`language` / `country`	Useful when you want locale-specific review sets
4	`reviewsSort` and `ratingFilter`	Helps focus on newest, most relevant, or rating-specific feedback

Inputs (high level)

Key inputs you’ll likely use:

appUrls: list of Play Store URLs (or app IDs).
maxReviewsPerApp: limit per app (min 1).
language / country: two-letter codes (e.g. en, us).
reviewsSort: NEWEST, RELEVANT, or RATING.
ratingFilter: return only a specific star rating (1–5).

Example input:

{
  "appUrls": ["https://play.google.com/store/apps/details?id=com.whatsapp"],
  "maxReviewsPerApp": 500,
  "language": "en",
  "country": "us",
  "reviewsSort": "NEWEST",
  "ratingFilter": ""
}

Output shape

Each dataset item includes fields like:

{
  "appId": "com.whatsapp",
  "appUrl": "https://play.google.com/store/apps/details?id=com.whatsapp",
  "language": "en",
  "country": "us",
  "reviewId": "…",
  "userName": "…",
  "score": 5,
  "content": "…",
  "thumbsUpCount": 12,
  "appVersion": "…",
  "at": "2025-10-10T00:47:17"
}

What the sample output tells you

The output contract is structured for downstream analysis, not just display:

appId and appUrl make the source app explicit.
language and country support locale-based filtering.
score, content, and thumbsUpCount make sentiment and issue clustering easier.
appVersion and at let you line up review trends against releases and dates.

If your next step is trend analysis, this shape is enough to build rating curves, keyword clusters, and release monitoring without additional cleanup.

Run it via API (JavaScript)

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client
  .actor("fetchcraftlabs/playstore-reviews-scraper")
  .call({ appUrls: ["https://play.google.com/store/apps/details?id=com.whatsapp"] });

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Limitations and notes

This page is intentionally scoped to the actor's public input/output contract.

The actor works with public Google Play review data, not private in-app analytics.
Review availability can vary by app, locale, and what is currently exposed on the source.
If you are budgeting large runs, re-check the live actor page for the latest pricing and store details before execution.
If your workflow depends on a specific field, validate one small test run first and confirm the dataset shape matches your downstream schema.

Pricing

Paid per event, from $0.07 / 1,000 results (Apify Store discounts apply).

FAQ

Is this actor good for competitor review analysis?

Yes. If you have competitor app URLs or app IDs, you can export their public reviews into the same structured format and compare themes, volume, and ratings across apps.

Can I filter only low-star or high-star reviews?

Yes. Use ratingFilter when you want a narrow slice such as only 1-star complaints or only 5-star reviews.

Can I collect reviews from different locales?

Yes. The language and country inputs help you target locale-specific review sets, which is useful when sentiment differs by market.

What should I validate before using this in production?

Run a smaller test first. Confirm the field set, locale behavior, record volume, and export format before wiring the dataset into dashboards, alerts, or reporting jobs.

Browse more published actors on /actors.
Need iOS review data too? See Apple App Store Reviews Scraper.
Questions about fit or implementation? Use the contact page.

Next steps

Schedule the Actor to refresh datasets weekly/monthly.
Connect outputs to Google Sheets, BigQuery, or your BI stack.
Share datasets across product, support, and marketing teams.

Playstore Reviews Scraper: Collect Google Play reviews at scale