Capterra Product Reviews Scraper: Reviews by Slug

Pull Capterra.com product reviews via the public reviews page. One row per review: title, body, rating, reviewer role and industry, posted date, pros, cons. Specify product slugs + per-product cap.

How to use

Pass one or more Capterra product paths in the form productId/slug. Find these in the Capterra URL: capterra.com/p/135003/Slack/reviews/ → path is 135003/Slack.

Input shape

{
  "products": [
    "135003/Slack",
    "164800/Notion",
    "188405/Figma"
  ],
  "maxReviewsPerProduct": 50
}

Field	Type	Default	Description
products	string[]	Slack / Notion / Figma	Capterra product paths in form productId/slug
maxReviewsPerProduct	integer	50	Cap reviews collected per product (reads up to 5 pages per product)

Example output row

{
  "reviewId": "12345678",
  "product": "135003/Slack",
  "title": "Best team communication tool out there",
  "body": "We've been using Slack for 3 years across 4 departments...",
  "rating": 4.5,
  "reviewerRole": "Product Manager",
  "reviewerIndustry": "Computer Software",
  "postedAt": "2024-11-15",
  "pros": "Integrations, search, channels keep conversations organized",
  "cons": "Gets expensive at scale; notification overload without discipline"
}

Reviewer names are not included; e-mail addresses and phone numbers inside review text are replaced with [email removed] / [phone removed].

Pricing

Pay per event. Price per 1,000 events:

Event	Base price	Bronze	Silver	Gold
Result	$1.00	$0.90	$0.80	$0.70

Bronze, Silver and Gold are the discounts Apify gives users of its paid plans. The Pricing tab always shows the current prices.

Buyer

• Competitor intelligence and win/loss analysis across SaaS categories
• Monitoring your own product's review sentiment over time
• Sales enablement: surfacing competitor weaknesses by reviewing cons at scale
• Market research: aggregating reviewer roles and industries to identify target segments
• Benchmarking rating trends across competing products

Run it through the API

Python, with the apify-client package:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("v0iddo/capterra-product-reviews").call(run_input={"products": ["135003/Slack", "164800/Notion", "188405/Figma"], "maxReviewsPerProduct": 20})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript, with the apify-client package:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('v0iddo/capterra-product-reviews').call({"products": ["135003/Slack", "164800/Notion", "188405/Figma"], "maxReviewsPerProduct": 20});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call that waits for the run and returns the rows (for runs that finish within 5 minutes):

curl -X POST "https://api.apify.com/v2/acts/v0iddo~capterra-product-reviews/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"products": ["135003/Slack", "164800/Notion", "188405/Figma"], "maxReviewsPerProduct": 20}'

Use it from an agent (MCP)

Claude, Cursor, VS Code and other MCP clients can call this actor as a tool through the Apify MCP server. Add it to the client's MCP configuration:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=v0iddo/capterra-product-reviews",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

FAQ

Do I need an account, cookies or an API key?

No. The actor reads public data without logging in. You only need an Apify account to start it.

How many results can one run return?

Set maxReviewsPerProduct to the number you need. Large jobs can also be split into several runs or scheduled.

How am I charged?

Pay per event, at the prices on the Pricing tab for your Apify plan (the Pricing section of this page lists them). The platform usage of the run is included in those prices, and your spending limit for a run is always respected.

Why did my run return no results?

The status message and the log of the run say why: usually nothing matched the input, or the source did not answer for a moment. Check the input against the example above and run it again.

Can I run it on a schedule?

Yes. Save your input as a task and add a schedule in the Apify Console (daily, hourly or with a cron expression). Each run gets its own dataset, so you keep a history.

Which formats can I export?

JSON, CSV, Excel, XML, HTML table and RSS from the Output tab or the API. Integrations send the rows to Google Sheets, Slack, Make, Zapier, n8n or a webhook.

Is collecting this data allowed?

The actor collects data that the source publishes openly, without a login. Public data can still be personal data under laws such as the GDPR, and sources have their own terms: make sure your use of the data follows the rules that apply to you.

What happens when the source changes?

An automated test runs the actor every day on the example input and checks the rows, not only that the run finished. When a check fails, the actor is repaired and rebuilt; the build history on this page shows each update.

Something is missing or wrong. Where do I report it?

Open an issue on the Issues tab of this actor with the run link. Requests for a new field are welcome too.

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Source

Capterra serves React / Next.js pages. Review content is embedded in the __NEXT_DATA__ JSON blob within each product review page:

https://www.capterra.com/p/{productId}/{slug}/reviews/?page=N

Pages are scraped with a real Chrome User-Agent and Accept-Language: en-US. Pagination stops when the reviews array is empty or after 5 pages. If a product slug returns 404, it is logged and skipped without failing the run.