Shopify App Reviews Scraper

Export public Shopify App Store reviews with star ratings, merchant feedback, visible developer replies and app-level rating metrics. Use app URLs or handles to collect review datasets for competitor research, app selection and product planning. Download JSON, CSV or Excel, or retrieve results through the API.

This scraper collects reviews of Shopify apps, not product reviews from individual Shopify shops. It does not maintain a review archive or calculate sentiment for you.

Quick start

1. Enter a Shopify App Store app URL or handle. Remove any prefilled app you do not want.
2. Start with twenty reviews and a small page limit. Optionally choose star ratings.
3. Click Start, then open the dataset to inspect or export your results.

{
  "appHandles": [
    "judgeme"
  ],
  "maxReviewsPerApp": 20,
  "maxPagesPerApp": 3,
  "sortBy": "newest",
  "locale": "en"
}

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose an example to start with a small, preconfigured input.

• Collect Shopify support-app feedback — Collect up to twenty public Helpdesk app reviews. Compare repeated snapshots in your own workflow.
• Compare Shopify review apps — Collect up to fifteen reviews each for Judge.me and Loox. Compare sentiment afterward in your own analysis.
• Analyze low-star app feedback — Collect up to twenty one- and two-star Judge.me reviews for complaint research.

What you get

• Review records: text, star rating, public date and review link.
• Merchant context: visible merchant name, country and time using the app.
• App context: app name, aggregate rating, review count and visible rating distribution.
• Developer replies: reply text when present. Reply dates are not currently extracted.
• Focused collection: app URLs or handles, star-rating filters, locale, sorting and per-app limits.

Who is it for?

• Shopify app developers researching merchant pain points and product ideas.
• Ecommerce agencies comparing app feedback before recommending tools.
• Product and support teams reviewing recurring complaints and public replies.
• Analysts and automation builders preparing structured review datasets for downstream analysis.

Repeated runs can supply snapshots for your workflow. Comparing snapshots, detecting new or removed reviews, alerts and sentiment analysis require your own processing.

Input settings

Setting	JSON key	What it does
App URLs	appUrls	Shopify App Store listing or review URLs.
App handles	appHandles	App identifiers such as judgeme. Combined with URLs and resume cursors.
Reviews per app	maxReviewsPerApp	From 1 to 1,000 saved reviews per app. Form default: 20.
Rating filter	ratings	Optional array of star-rating strings, such as ["1", "2"]. Empty includes all ratings.
Sort order	sortBy	newest, the default, or Shopify's relevance ordering.
Locale	locale	Optional Shopify locale, for example en or de. Form default: en.
Pages per app	maxPagesPerApp	From 1 to 200 review pages. Form default: 5.
Run time	maxRunSeconds	Shared time budget from 35 to 270 seconds. Default: 270.
Resume cursors	resumeCursors	Advanced app/page entries from PENDING_REVIEW_CURSORS.

Provide at least one valid app URL, handle or resume cursor. URLs and handles are combined, with duplicate app handles processed once. The form prefills Judge.me in both fields. Clear both when switching to another app.

For API calls that omit limits, the runtime uses fifty reviews per app and a page cap of one plus the review limit divided by ten, rounded up. Specify both limits explicitly for predictable inputs. Omitting locale leaves Shopify's default locale in use.

Input recipes

For low-star research, add a rating filter to your app handles:

{
  "appHandles": ["judgeme", "loox"],
  "maxReviewsPerApp": 20,
  "maxPagesPerApp": 5,
  "ratings": ["1", "2"],
  "sortBy": "newest",
  "locale": "en"
}

To resume unfinished work, copy the app/page cursors from PENDING_REVIEW_CURSORS into resumeCursors. Retain your filters and limits, and omit completed apps from appUrls and appHandles. Resume cursors do not provide cross-run duplicate detection.

Output data

Each dataset row represents a review. Missing visible details are null. developerReplyDate is always null in the current implementation. This synthetic shape-only example is not a real merchant review:

{
  "appHandle": "judgeme",
  "appName": null,
  "appUrl": "https://apps.shopify.com/judgeme",
  "reviewsUrl": "https://apps.shopify.com/judgeme/reviews?page=1&sort_by=newest&locale=en",
  "aggregateRating": null,
  "aggregateReviewCount": null,
  "ratingDistribution": {},
  "reviewId": "example-review-id",
  "reviewUrl": "https://apps.shopify.com/reviews/example-review-id",
  "rating": 5,
  "reviewText": "Example review text.",
  "reviewDate": null,
  "merchantName": null,
  "merchantCountry": null,
  "merchantUsage": null,
  "developerReplyText": null,
  "developerReplyDate": null,
  "pageNumber": 1,
  "scrapedAt": "2026-10-25T00:00:00.000Z"
}

Fields	Meaning
appHandle, appName, appUrl	App identifier, visible name and listing URL.
reviewsUrl, pageNumber	Source review page and its page number.
aggregateRating, aggregateReviewCount	App-level visible rating and review count, not counts for your filtered sample.
ratingDistribution	Visible counts keyed by star rating. May be empty.
reviewId, reviewUrl	Review identifier and share URL.
rating, reviewText, reviewDate	Star rating, text and displayed date text. Dates are not normalized.
merchantName, merchantCountry, merchantUsage	Visible merchant details and displayed usage duration.
developerReplyText, developerReplyDate	Visible reply text and an unpopulated reply-date field.
scrapedAt	Collection timestamp in ISO format.

The key-value store contains RUN_SUMMARY with saved counts, app errors and pending cursors. PENDING_REVIEW_CURSORS identifies unfinished app pages when the time budget interrupts collection. Completed reviews remain available for partial runs.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

This Actor uses pay-per-event pricing. The start event is charged once after valid app targets are resolved and collection begins. A run can incur this charge even when it saves no reviews.

The result event is charged for each review saved to the dataset. Failed requests, skipped duplicates and empty pages do not create review charges. Per-app review and page limits bound collection, but do not guarantee that many results.

See the live Pricing tab for current rates and discounts.

Tips for best results

• Start with one app. Inspect a small sample before collecting several apps.
• Focus your ratings. Use one- and two-star reviews for complaint research or five-star reviews for praise.
• Set both limits. Review and page limits apply to each app, while the time budget is shared across the run.
• Keep the review identifiers. Use them to compare repeated snapshots in your own workflow.
• Check the run summary. It identifies app failures and unfinished work when results are partial.

Limits and caveats

• Public Shopify App Store app reviews only. No Shopify shop product reviews, private account data or login credentials are needed.
• Only star ratings, sort order and locale are supported as review filters. There are no date, keyword, country, merchant-usage, text or reply-presence filters.
• Replies and merchant details depend on what the public page exposes. Reply dates are not extracted.
• Filtered views, missing reviews, access restrictions and the shared time budget can reduce output. There is no guaranteed complete historical archive.
• A page with no review elements ends collection for that app. No matching reviews can produce a successful empty dataset. If errors or pending work leave no saved reviews, the current runtime fails the run and records details in RUN_SUMMARY.
• This is an independent scraper, not an official Shopify API.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~shopify-app-reviews-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"appHandles":["judgeme"],"maxReviewsPerApp":20,"maxPagesPerApp":3,"sortBy":"newest","locale":"en"}'

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/shopify-app-reviews-scraper').call({
  "appHandles": [
    "judgeme"
  ],
  "maxReviewsPerApp": 20,
  "maxPagesPerApp": 3,
  "sortBy": "newest",
  "locale": "en"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/shopify-app-reviews-scraper').call(run_input={
  "appHandles": [
    "judgeme"
  ],
  "maxReviewsPerApp": 20,
  "maxPagesPerApp": 3,
  "sortBy": "newest",
  "locale": "en"
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

MCP and AI agents

You can ask your AI assistant to collect data with Shopify App Reviews Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Shopify App Reviews Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/shopify-app-reviews-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Shopify App Reviews Scraper by Fetch Cat, or give it the identifier fetch_cat/shopify-app-reviews-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• "Collect twenty recent Judge.me app reviews and summarize the main themes in the returned text."
• "Get one- and two-star reviews for Loox and group the merchant complaints by topic."
• "Collect fifteen reviews each for Judge.me and Loox, then compare the feedback and visible developer replies."

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

Can I export Shopify App Store reviews to CSV or Excel?

Yes. The dataset contains review records that you can export as CSV, Excel or JSON. The API and MCP examples retrieve the same structured results.

Does this scrape product reviews from Shopify shops?

No. It collects reviews of apps on Shopify App Store. For shop product-review platforms, use a scraper designed for that platform.

Can I filter by rating or review date?

Use ratings to select star ratings and sortBy to request newest-first or relevance ordering. Date, keyword, country, usage and reply-presence filters are not supported. Apply those analyses to returned data yourself where the relevant fields are present.

Why did I receive fewer reviews or no reviews?

An app or rating filter may have fewer public reviews than requested. Review and page limits, access restrictions and the time budget also affect output. Check RUN_SUMMARY for errors and unfinished work. Inaccessibility alone does not establish that an app is private or deleted.

Can I monitor app reviews automatically?

You can schedule repeated collection using Apify and compare the resulting snapshots in your own workflow. The scraper does not automatically detect new, changed or archived feedback, calculate sentiment or send alerts.

Do I need a Shopify login or API key?

No Shopify credentials are needed for public app-review pages. Calling the Actor through Apify's API or authenticated MCP requires Apify authentication.

How are empty results charged?

The start event can apply even when no reviews are saved. The result event applies only to saved review rows. See the live Pricing tab for current rates.

Related Actors

• Shopify App Store Scraper — Collect app listing details for review research.
• Shopify Products Scraper — Collect shop product catalog data instead of app feedback.
• Trustpilot Reviews Scraper — Research public business reviews alongside app feedback.
• Google Play Reviews Scraper — Research public Android app feedback.
• Apple App Store Reviews Scraper — Research public iOS app feedback.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥