# Software Reviews Scraper: Capterra, Google Play, App Store (`arcadium/software-reviews`) Actor Reviews of a software product from Capterra, Google Play and the App Store in one dataset and one row shape, by name or URL; $1.79 per 1,000 reviews. Free summary row per product, Software Advice optional. Verified name matching, only-new mode, no reviewer names. - **URL**: https://apify.com/arcadium/software-reviews.md - **Developed by:** [Arcadium Data](https://apify.com/arcadium) (community) - **Categories:** Automation, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.16 / 1,000 reviews 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 ## Software Reviews Scraper: Capterra, Google Play, App Store Type a product name like "Slack" or paste a mix of links and get its reviews from Capterra (and optionally Software Advice), Google Play and the App Store in one dataset, one row shape: rating, title, text, pros, cons, date, the reviewer's role and company size where the site has them. $1.79 per 1,000 reviews on the free plan, and you pay only for the rows you get. **Why this actor** - One name, every source: the actor finds the product on each site and checks the match, with a free summary row per product showing each source's rating and review count. - Links are sorted to the right source by host, so a mixed list is one input. - Only reviews of mobile apps? Use the App Reviews Scraper at $0.10 per 1,000 instead. - Reviewer names, photos, emails and phone numbers are never collected. Free error rows with a machine-readable `code` (`not_found`, `blocked`, `unavailable`...), so an agent knows whether to retry. Built by Arcadium Data: public data, dated and agent-ready, never personal data. ### Use with AI agents Returns reviews of one software product from Capterra, Google Play and the App Store in one dataset, found by product name or URL. Agents can call it through the Apify MCP server (`https://mcp.apify.com`, open source as `apify/actors-mcp-server`) as `arcadium/software-reviews`: the input schema is read from the actor, the result is a dataset of JSON rows. Input example (minimal): ```json { "products": [ "Slack" ], "maxReviewsPerSource": 20 } ``` What comes back: one `review` row per review (charged), a free `summary` row per product with the rating each source shows and how sure the name match is, free `coverage` rows (stated total vs delivered) and a free `error` row for an input that could not be read. Filter on the `rowType` field. An input that fails is reported, not hidden (`includeErrorRows`, on by default): the error row carries `rowType: "error"`, a `code` (`invalid_input`, `not_found`, `blocked`, `unavailable`, `filter_unsupported` or `no_match`), a `message` and the `input` it is about. Retry on `blocked` and `unavailable` later; do not retry the other codes with the same input. Cost of the call above: at most 60 reviews at $1.79 per 1,000 plus the $0.001 start fee is about $0.11 on the free plan; paid plans pay less. Free rows are never charged. ### What you get | Field | What it holds | | --- | --- | | `platform` | `capterra`, `softwareadvice`, `googleplay` or `appstore`. | | `reviewId` | The platform's own ID with a platform prefix. Stable between runs, so weekly exports can be deduped. | | `date` | Review date, ISO format. | | `title`, `text`, `pros`, `cons` | What the reviewer wrote. Pros and cons exist on Capterra and Software Advice only. | | `ratingOverall` | Overall rating (1 to 5). | | `ratings` | Sub-ratings (ease of use, support, value and so on) where the platform has them. | | `reviewerRole`, `reviewerIndustry`, `reviewerCompanySize` | Business context from Capterra and Software Advice. Empty for app stores. | | `vendorResponse` | The vendor's public reply, when there is one. | | `product` | Name, rating, review count, category, vendor and website of the product on that platform. | | `extras.inputProduct` | The name you searched for, so you can group rows when you pass several products. | Company size always uses one set of labels, whatever the source: `Self-employed`, `1-10 employees`, `11-50 employees`, `51-200 employees`, `201-500 employees`, `501-1000 employees`, `1001-5000 employees`, `5001-10000 employees`, `10001+ employees`. Output example (a review, shortened): ```json { "rowType": "review", "platform": "googleplay", "reviewId": "GooglePlay___a1b2c3d4-0000-0000-0000-000000000000", "productName": "Slack", "date": "2026-10-14", "title": null, "text": "Notifications are finally reliable on my phone.", "ratingOverall": 4, "reviewerCompanySize": null, "extras": { "inputProduct": "Slack" } } ``` Sample summary row (free): ```json { "rowType": "summary", "input": "Slack", "inputType": "name", "vendor": "Slack Technologies", "matchConfidence": { "capterra": "high", "googleplay": "high", "appstore": "high" }, "sources": { "googleplay": { "name": "Slack", "rating": 4.2, "reviewCount": 150000, "status": "ok", "reviewsPushed": 100 } } } ``` ### Input ```json { "products": ["Slack", "Asana"], "maxReviewsPerSource": 100 } ``` | Field | What it does | | --- | --- | | `products` | Product names to look up in every chosen source. | | `startUrls` | Capterra, Software Advice, GetApp, Google Play or App Store links. Each goes to its own source by host. A Play package id or an App Store id works too. | | `sources` | Which sources to search for names. Default: `capterra`, `googleplay`, `appstore`. Add `softwareadvice` if you want it as a separate source. | | `maxReviewsPerSource` | Cap per product and source. Default 100. | | `sort` | `recent` (default) or `helpful`. | | `appCountry`, `language` | Storefront country for the app stores, and review language for Google Play. | | `dateFrom` | Only reviews on or after this date. | | `onlyNewReviews`, `stateKey` | Return only reviews that earlier runs with the same key did not deliver. | | `includeSummaryRows`, `includeErrorRows` | Free extra rows. Both on by default. | | `includeCoverageRows` | On by default. One free row per source with `"rowType": "coverage"`: the review total the site states, how many were delivered, why the run stopped and whether anything is missing (`shortfall`). Never charged. | | `markEdited` | On by default, with `onlyNewReviews`. Reviews seen before whose text changed in the last 7 days are delivered again with `extras.changeType` set to `edited` (charged like a new review). New ones carry `new`. | ### How names are matched - **Capterra and Software Advice.** Capterra has no search we can use, so a name is searched on Software Advice and accepted only when the product name matches exactly. Both sites show the same review corpus (the IDs are the same `Capterra___`), so you get the Capterra reviews. These rows say `platform: softwareadvice`. If you want rows read from Capterra itself, pass the Capterra link in `startUrls`. - **Google Play and App Store.** The best search hits are checked: the app name must equal the product name, or the developer must match the vendor and the name must contain the product. If nothing passes, you get a free `no_match` row for that source instead of the wrong app's reviews. - **Failover.** If a Capterra link cannot be read, the same product is read from Software Advice automatically. - **No double charging.** When Software Advice is also selected, reviews already delivered from another source are dropped and not charged. ### Use it from an AI assistant Paste this into your assistant to run the actor for you: ```text Use the Apify actor "software-reviews" to collect reviews. Input: {"products":[""],"maxReviewsPerSource":100} Each dataset row has a rowType: "review", "summary" (one per product, ratings per source) or "error". Key review fields: platform, reviewId, date, title, text, ratingOverall. Run it, then compare what business buyers (capterra/softwareadvice) and app users (googleplay/appstore) praise and complain about. Mention the review counts per source. ``` ### Use it from code Python: ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("arcadium/software-reviews").call(run_input={ "products": ["Slack"], "maxReviewsPerSource": 100, }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): if item["rowType"] == "review": print(item["platform"], item["date"], item["ratingOverall"]) ``` JavaScript: ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: '' }); const run = await client.actor('arcadium/software-reviews').call({ products: ['Slack'], maxReviewsPerSource: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items.filter((i) => i.rowType === 'review').length, 'reviews'); ``` ### Coming from zen-studio's Software Review scraper? These input names work as they are: `query` (one product name), `platforms` (`capterra` and `softwareadvice` are mapped to `sources`; `g2`, `trustradius`, `gartner` and `trustpilot` are not sources here), `maxResults` and `sort` (`most_recent`, `most_helpful`, `highest_rated`, `lowest_rated`; the two rating sorts fall back to recent). `starRatings` is not supported and is ignored. ### Pricing You pay per review delivered, at the price of your Apify plan. Summary rows, coverage rows, error rows and duplicates are free. | Apify plan | Per 1,000 reviews | | --- | --- | | Free | $1.79 | | Starter (Bronze) | $1.34 | | Scale (Silver) | $1.25 | | Business (Gold) | $1.16 | | Platinum | $1.16 | | Diamond | $1.16 | Plus a one-off $0.001 per GB of memory when a run starts. Set a maximum cost per run in the Apify run options and the actor stops before it goes over. ### Related actors and data - [Capterra Reviews Scraper: Pros, Cons, Company Size](https://apify.com/arcadium/capterra-reviews) - [TrustRadius Reviews Scraper: Pros, Cons, Reviewer Role](https://apify.com/arcadium/trustradius-reviews) - [App Reviews Scraper: iOS App Store and Google Play](https://apify.com/arcadium/app-reviews) - [Review Monitor: Negative Review Alerts and Rating Drift](https://apify.com/arcadium/reputation-monitor) - [Arcadium Data MCP Server](https://apify.com/arcadium/arcadium-mcp): AI agents can ask the same questions as tools (`search_reviews`, `review_snapshot`). ### Use cases - Buyer versus user view: compare what procurement-minded reviewers say with what app users say. - Competitor tracking: run weekly with `onlyNewReviews` and watch what changes. - Sentiment analysis: feed review text and ratings into your own model or spreadsheet. - Comparison pages: pull ratings and counts per source from the summary rows. ### Limitations - Public reviews only. Nothing behind a login or a paywall. - Pros, cons and reviewer role/industry exist only on Capterra and Software Advice. App store rows leave them empty. - Name search covers products Software Advice lists under exactly that name. If it is not found, pass the Capterra link directly. - App name matching is conservative on purpose. A product whose app has a different name or a different developer returns `no_match`; pass the app link in `startUrls` for those. - The App Store search checks the top result only. - Links are routed to one source each. To get all sources for one product, use its name. - Sorting is "most recent" or "most helpful". Rating and company size filters are not offered here. ### Privacy Reviewer names, profile photos, emails and phone numbers are never collected. You get the review and the context around it, not the person. ### FAQ **How fresh is the data?** It is read when you run the actor, so it matches what the sites show at that moment. **Can I get only new reviews since my last run?** Yes. Turn on `onlyNewReviews` and keep the same `stateKey`. Change the key to start over. **A source returned nothing. Why?** Look at the `error` rows and at `STATS.sources` in the key-value store. `no_match` means no confident match for that name, which costs nothing. **Something looks wrong in the output. Who do I tell?** Open an issue on the actor page with the run link. We read them all. # Actor input Schema ## `products` (type: `array`): Software product names, e.g. Slack or Asana. Each name is looked up on Capterra / Software Advice and in the Google Play and App Store catalogs. An app is used only when it is confidently the same product; otherwise that source returns a free 'no_match' row. ## `startUrls` (type: `array`): Product pages from Capterra, Software Advice, GetApp, Google Play or the App Store. Each link is routed to its source by host. A Google Play package id (com.slack) or an App Store id (618783545) also works. Can be combined with product names. Example: https://www.capterra.com/p/135003/Slack/. ## `sources` (type: `array`): Which sources to search when you give product names. Capterra, Google Play and App Store are on by default. Software Advice shows largely the same reviews as Capterra, so it is opt-in; duplicates are dropped and never charged. Links in 'Start URLs' are always read, whatever is chosen here. Default: capterra, googleplay, appstore. ## `maxReviewsPerSource` (type: `integer`): Maximum number of reviews to collect from each source for each product (up to 50,000). Default: 100. ## `sort` (type: `string`): Most recent first, or most helpful first (each store's own relevance ranking). The names most_recent, most_helpful, highest_rated and lowest_rated from similar actors also work; the two rating sorts are not supported and use Most recent. ## `appCountry` (type: `string`): Two-letter storefront country for Google Play and the App Store, e.g. us, gb, de. Leave empty for us (or the country in an App Store link). ## `language` (type: `string`): Language of the Google Play reviews, e.g. en or pt-BR. ## `dateFrom` (type: `string`): Only keep reviews published on or after this date (YYYY-MM-DD, or a relative span such as 30 days or 2 months; empty = no filter). With 'Most recent' sorting, paging stops once reviews are older. ## `onlyNewReviews` (type: `boolean`): Return only reviews not delivered by earlier runs that used the same state key. Uses the 'Most recent' sort order. The state is kept in a named key-value store in your account (change the state key to start over). Skipped reviews are not charged. ## `stateKey` (type: `string`): Name of the incremental state used by 'Only new reviews' (letters, digits and dashes, up to 40 characters). Use different keys for independent schedules. Example: weekly-monitoring. ## `includeSummaryRows` (type: `boolean`): Add one row with rowType 'summary' (not charged) per product: the rating and review count each source shows, and how confident the match is. ## `includeErrorRows` (type: `boolean`): Add one row with rowType 'error' (not charged) for each input or source that could not be scraped, e.g. no confident app match. ## `includeCoverageRows` (type: `boolean`): Add one free row with rowType 'coverage' per product or source: the review total the site states, how many were delivered, why paging ended and whether anything is missing. Not charged. ## `markEdited` (type: `boolean`): With 'Only new reviews': also deliver reviews seen before whose text changed in the last 7 days, marked extras.changeType 'edited'. Edited reviews are charged like new ones. ## `maxRetries` (type: `integer`): How many times a failed request is retried before that source is skipped. ## `proxyConfiguration` (type: `object`): Optional. By default the actor automatically picks the cheapest working proxy. Set this only to force your own proxy setup. ## Actor input object example ```json { "products": [ "Slack" ], "sources": [ "capterra", "googleplay", "appstore" ], "maxReviewsPerSource": 20, "sort": "recent", "language": "en", "onlyNewReviews": false, "stateKey": "default", "includeSummaryRows": true, "includeErrorRows": true, "includeCoverageRows": true, "markEdited": true, "maxRetries": 3 } ``` # Actor output Schema ## `results` (type: `string`): All rows of this run in the default dataset. ## `view_overview` (type: `string`): No description ## `view_summary` (type: `string`): No description ## `view_errors` (type: `string`): No description ## `view_coverage` (type: `string`): No description ## `record_stats` (type: `string`): Requests, data volume, per-source counts and cost per result for this run. ## `record_product` (type: `string`): Product profiles (Capterra / Software Advice / app store listings) collected next to the reviews. # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "products": [ "Slack" ], "sources": [ "capterra", "googleplay", "appstore" ], "maxReviewsPerSource": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("arcadium/software-reviews").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "products": ["Slack"], "sources": [ "capterra", "googleplay", "appstore", ], "maxReviewsPerSource": 20, } # Run the Actor and wait for it to finish run = client.actor("arcadium/software-reviews").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 '{ "products": [ "Slack" ], "sources": [ "capterra", "googleplay", "appstore" ], "maxReviewsPerSource": 20 }' | apify call arcadium/software-reviews --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,arcadium/software-reviews" } } } ``` 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 ` 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/wTfjPNxq6yIVKDV15/builds/xeeyA2TtKQBrAifZl/openapi.json