Capterra Reviews Scraper

Scrapes verified user reviews from any Capterra product page and returns structured data. Each record includes review text, overall star rating, sub-category scores (ease of use, features, value for money, customer service), reviewer job title and industry, pros, cons, and the product the reviewer switched from.

Capterra reviews show up in buying decisions and analyst reports. If you're keeping tabs on a product — yours or a competitor's — checking the page manually doesn't scale. This actor handles pagination and URL normalization automatically. Give it a URL and a review count, and it does the rest.

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Why people use this

Some use it to monitor their own product. Run it on a schedule, route new reviews to Slack or a spreadsheet, and you stop finding out about problems weeks after they were posted.

Some use it for competitor research. Pull reviews for two or three competing products, look at what changed over the last quarter, and you get a clearer picture than any analyst summary.

Some run it specifically to find cons from 1-3 star reviews and route those directly into a feature backlog. Real complaints from paying users are better input than most internal feedback sessions.

Some need review text in bulk for NLP or sentiment analysis and don't want to scrape it by hand.

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What it collects

For each review, the actor returns:

Field	Description
softwareName	Name of the software product
reviewerName	Reviewer name or initials
reviewerTitle	Job title of the reviewer
reviewerIndustry	Industry or company type
usageDuration	How long they have used the software
reviewTitle	Headline of the review
reviewDate	Date the review was submitted
overallRating	Overall star rating out of 5
easeOfUse	Ease of use score out of 5
customerService	Customer service score out of 5
features	Features score out of 5
valueForMoney	Value for money score out of 5
likelihoodToRecommend	Score out of 10
reviewText	Full body text of the review
pros	Positive points from the reviewer
cons	Negative points from the reviewer
switchedFrom	Previous software the reviewer left
pageUrl	Source page URL
scrapedAt	ISO 8601 timestamp of collection

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Input

Field	Required	Default	Description
startUrl	Yes	—	Capterra product or reviews page URL
maxItems	No	25	Maximum reviews to collect (up to 1,000)
requestTimeoutSecs	No	30	Per-request timeout in seconds

URL formats accepted

The actor accepts any of these — /reviews/ is added automatically if the path is missing:

https://www.capterra.com/p/150854/Apify/reviews/
https://www.capterra.com/p/150854/Apify/reviews
https://www.capterra.com/p/150854/Apify

Only URLs from capterra.com are accepted. Anything else fails with a clear error message.

Pagination

Each Capterra page shows 25 reviews. The actor calculates how many pages it needs and fetches them in order.

• maxItems: 25 — 1 page (default)
• maxItems: 100 — 4 pages
• maxItems: 250 — 10 pages
• maxItems: 1000 — up to 40 pages (stops when no more reviews exist)

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Example input

{
  "startUrl": "https://www.capterra.com/p/150854/Apify/reviews/",
  "maxItems": 50
}

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Example output

{
  "softwareName": "Apify",
  "reviewerName": "Saif R.",
  "reviewerTitle": "Founder",
  "reviewerIndustry": "Computer Software",
  "usageDuration": "1-2 years",
  "reviewTitle": "Apify saved us tons of time.",
  "reviewDate": "February 28, 2026",
  "overallRating": 5.0,
  "easeOfUse": 4.0,
  "customerService": 5.0,
  "features": 4.0,
  "valueForMoney": 5.0,
  "likelihoodToRecommend": 10.0,
  "reviewText": "We plugged Apify into our backend to pull Google Maps reviews for businesses on our platform. Took maybe a day to get the API integration working, which was faster than I expected.",
  "pros": "The API is dead simple. You send a request, you get structured JSON back. No need to manage proxies, headless browsers, or parsing logic.",
  "cons": "Some of the actors in the store aren't great. I tried a couple that had bad documentation.",
  "switchedFrom": "ScrapingBee",
  "pageUrl": "https://www.capterra.com/p/150854/Apify/reviews/",
  "scrapedAt": "2026-04-18T12:00:00+00:00"
}

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Running on a schedule

To track new reviews automatically, use Apify's scheduler:

1. Open the actor in Apify Console
2. Go to Schedules and create a new schedule
3. Set a cron expression — 0 8 * * 1 runs every Monday at 8am
4. Connect the output to a webhook, Google Sheets integration, or a downstream dataset

Your team gets updated review data without anyone running the actor by hand.

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Screenshots

Sample output data in the Apify dataset view

Sample output data in the Apify dataset view

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Notes

• Reviews with short text may not have pros or cons sections. Those fields will be null.
• The switchedFrom field is only populated if the reviewer mentioned a previous product.
• Setting maxItems higher than the actual review count is fine — the actor stops when pages run out.
• The actor only processes capterra.com URLs. Paste any product page URL and it adds /reviews/ automatically.