Capterra Reviews Scraper: Software Reviews, Pros, Cons, Ratings

From The Mine Works, makers of Threads Scraper and B2B Leads Finder, with over 140,000 runs across 170+ public actors.

Why choose this actor?

• Product links or just names. Paste https://www.capterra.com/p/135003/Slack/ or type Trello, and Capterra's own search finds the product. Our test run read 25 Slack reviews in 75 seconds, and a local run read 30 reviews from 3 products, one of them given by name, in 107 seconds. No Capterra account, no cookies.
• The whole review, split into columns. Every row has the overall rating, four sub ratings, likelihood to recommend, pros, cons and overall comments, the reviewer's job title, company size, industry and time used, and, when the reviewer gave them, the products they switched from and why. A full_text column joins the answers for an AI model.
• Charged only for reviews you keep. Reviews outside your date window, products Capterra does not have, refused pages and repeats are never charged; you pay per review delivered plus a flat $0.005 per run.

Part of The Mine Works Marketing, SEO and reviews family: Facebook Ad Library Scraper, Similarweb Scraper, Google Ads Transparency Scraper, Google News Scraper, Trustpilot Reviews Scraper, Google Trends Scraper.

Try it in one minute

Paste this into the JSON tab of the input page. It returns about 10 reviews of Slack in one to two minutes.

{
  "products": ["https://www.capterra.com/p/135003/Slack/"],
  "maxReviewsPerProduct": 10
}

You can name a product in three ways, in any mix: a capterra.com product link (https://www.capterra.com/p/135003/Slack/; any page of the product works, such as its reviews or pricing page), a regional Capterra link (https://www.capterra.co.uk/reviews/135003/slack, read from capterra.com, which holds the same reviews), or a product name (Trello), which Capterra's own product search turns into one product. Up to 200 products per run.

Apify's free plan includes $5 of credit every month, which covers about 2,450 reviews at this actor's Free plan price, counted for runs of 100 reviews with the $0.005 start fee.

Copy to your AI assistant

themineworks/capterra-software-reviews-scraper on Apify. Scrapes public Capterra software reviews for product links or product names, with no login, and returns one row per review with title, date, overall and four sub ratings, likelihood to recommend, pros, cons, overall comments, a joined full_text, the reviewer's name as Capterra shows it, job title, company size, industry and time used, switching data when given, and the product's name, id, rating, review total and vendor. Call ApifyClient("TOKEN").actor("themineworks/capterra-software-reviews-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items. Required: products (array of Capterra product links such as https://www.capterra.com/p/135003/Slack/ or product names such as "Trello"). Optional: maxReviewsPerProduct (default 100; 0 means every public review, up to 2,500 per product), sort (default "most_helpful"; also newest, oldest, highest_rated, lowest_rated, applied to each product's collected rows), publishedAfter (a date like 2026-08-01 or a period like "6 months"). Skip rows with _type "info"; the per product run summary is the key-value store record OUTPUT. Full spec: GET https://api.apify.com/v2/acts/themineworks~capterra-software-reviews-scraper/builds/default (Bearer TOKEN), which returns inputSchema and readme. Token: https://console.apify.com/account/integrations

Key features

• 42 fields per review when the reviewer filled everything in: review id, title and date, 6 ratings, 3 text answers plus full_text, 9 reviewer fields, 4 switching fields, 3 fields on how the review was collected, 7 product fields and 6 fields on where the row came from.
• Up to 200 products per run, up to 2,500 reviews each: Capterra shows 100 pages of 25 reviews to visitors who are not signed in, and maxReviewsPerProduct: 0 reads all of them.
• Date filter: publishedAfter takes a date (2026-08-01) or a period (30 days, 2 weeks, 6 months, 1 year). Older reviews are skipped and not charged.
• Five row orders: keep Capterra's Most helpful order, or have each product's rows ordered newest, oldest, highest rated or lowest rated first.
• Switching data: switched_from and switching_reasons (the products a reviewer used before and why they moved), alternatives_considered and chosen_reasons, when the reviewer gave them.
• A run summary you can check: the OUTPUT record lists every product's status, the product a name matched, pages read and refused, repeats skipped and reviews outside the date window.

How to use it

Basic: one product

{
  "products": ["https://www.capterra.com/p/135003/Slack/"],
  "maxReviewsPerProduct": 100
}

Several products at once, links and names mixed

Two products are read at a time. A product given twice (as a link and as a name, say) is read once, and a review is never delivered twice in a run.

{
  "products": [
    "https://www.capterra.com/p/135003/Slack/",
    "Trello",
    "https://www.capterra.com/p/171143/CompanyCam/"
  ],
  "maxReviewsPerProduct": 50
}

This year's reviews of a competitor, newest first

Set a date window and the newest order. Reviews written before the date are skipped and not charged.

{
  "products": ["Trello"],
  "maxReviewsPerProduct": 0,
  "publishedAfter": "2026-01-01",
  "sort": "newest"
}

Complaints first, for a battle card

Collect a product's reviews with the lowest ratings first; the cons column holds each complaint in the reviewer's words, and reviewer_company_size and reviewer_industry tell you who is unhappy.

{
  "products": ["https://www.capterra.com/p/211559/Trello/"],
  "maxReviewsPerProduct": 500,
  "sort": "lowest_rated"
}

Why buyers leave a product

Run the product that wins customers and keep the rows where switched_from names the product they left; switching_reasons says why. In our Slack test, 5 of 25 reviews named the tool they switched from, among them Microsoft Teams, Google Chat and Discord.

{
  "products": ["https://www.capterra.com/p/135003/Slack/"],
  "maxReviewsPerProduct": 1000
}

Quarterly competitor digest on a schedule

Schedule this every three months in Apify (Console, this actor, Schedules) to collect what was written about your rivals since the last digest. Windows of a few months work well; very short windows do not (see the FAQ on the date filter).

{
  "products": ["Trello", "https://www.capterra.com/p/135003/Slack/"],
  "maxReviewsPerProduct": 0,
  "publishedAfter": "3 months",
  "sort": "newest"
}

Input parameters

Parameter	Type	Default	What it does
products	array of strings	none (required)	Capterra product links or product names, one per line. Any page of a product works (reviews, pricing, alternatives). Regional links such as capterra.co.uk/reviews/135003/slack are read from capterra.com. GetApp and Software Advice links are skipped with a warning. Up to 200.
maxReviewsPerProduct	integer	100	Most reviews to return per product (0 to 2,500). 0 means every review Capterra shows publicly, up to 2,500 per product.
sort	string	most_helpful	most_helpful keeps Capterra's own order. newest, oldest, highest_rated and lowest_rated order each product's collected rows that way; those rows are saved when the product is finished.
publishedAfter	string	empty	Only reviews written on or after this date: 2026-08-01, or a period such as 30 days, 2 weeks, 6 months, 1 year. Empty means no date filter.

products must have at least one usable line; otherwise the run stops at once with an info row that says what to add.

What data do you get?

One row per review. A field the reviewer left blank is left out of that row rather than filled with null, with one exception: a sub rating the reviewer skipped comes back as 0.

The review: review_id (Capterra's number for the review, as text), title, date (when it was written, YYYY-MM-DD), rating_overall, rating_ease_of_use, rating_customer_service, rating_features and rating_value_for_money (1 to 5; 0 means not rated), likelihood_to_recommend (0 to 10), pros, cons, comments (the reviewer's overall comments) and full_text (all the answers in one labelled text, ready for an AI model).

The reviewer, as Capterra shows them: reviewer_name (first name and initial, or Verified Reviewer when the reviewer chose to stay anonymous, in which case reviewer_anonymous is true), reviewer_job_title, reviewer_company_size, reviewer_industry, reviewer_time_used, and how Capterra checked them: reviewer_validated, reviewer_linkedin_verified and reviewer_validations (for example LinkedIn, BusinessEmail, ProofOfLink). No photos and no profile links.

How the review was collected: incentive (NoIncentive or NominalGift in our tests), review_source (Capterra's own sentence, such as "No Incentive Offered: This review was submitted organically.") and review_source_code.

Switching data, when the reviewer gave it: switched_from and switching_reasons, alternatives_considered and chosen_reasons.

The product: product_name, product_id, product_url, product_rating (Capterra's average), product_reviews_total, product_category (not shown for every product) and vendor_name.

Where it came from: source_site (the site the review was written on; Capterra shares reviews with GetApp and Software Advice, and every row in our tests said Capterra), page, position (the review's place in Capterra's order for that product), source_url, input (your line, as typed) and scraped_at.

A last dataset row with _type: "info" says how many reviews were delivered, or why none were; it is never charged. The run's key-value store also holds an OUTPUT record with, for every product, its status (ok, not_found, no_reviews, none_in_date_window, blocked, duplicate and so on), the stop_reason, the product a name matched, pages_read, pages_failed, duplicates_skipped and outside_date_window.

Stable fields for automations

These fields were present in every row of our test runs (55 reviews of Slack, Trello and CompanyCam, read on 29 September and 1 October 2026):

Field	What it holds
review_id	Capterra's review number, as text; use it as your key
product_name	The product's name on Capterra
product_id	Capterra's product number
title	The review's headline
date	When the review was written, YYYY-MM-DD
rating_overall	Overall rating, 1 to 5
likelihood_to_recommend	0 to 10
pros	What the reviewer liked
full_text	All answers in one labelled text
reviewer_name	First name and initial, or Verified Reviewer
reviewer_anonymous	true when the reviewer is anonymous
source_site	The site the review was written on
product_reviews_total	Capterra's review count for the product
source_url	The reviews page the row was read from
scraped_at	When the row was read, ISO 8601

These names will not change. New fields may be added, never renamed or removed.

Output examples

Real rows, trimmed for length (long texts end with ...; reviewer names are shortened to initials here, while the actor returns them as Capterra shows them).

A Slack review from our Apify test run on 1 October 2026. The reviewer skipped two sub ratings, which come back as 0, and named the tool they left:

{
  "review_id": "7155348",
  "product_name": "Slack",
  "product_id": "135003",
  "title": "Powerful communication and work management tool",
  "date": "2026-05-22",
  "rating_overall": 4,
  "rating_ease_of_use": 3,
  "rating_customer_service": 0,
  "rating_features": 5,
  "rating_value_for_money": 0,
  "likelihood_to_recommend": 8,
  "pros": "Slack is a powerful tool for both work management and communication...",
  "cons": "Slack has a steep learning curve compared to other platforms (less intuitive in my opinion)...",
  "reviewer_name": "A. F.",
  "reviewer_job_title": "Head of Quality",
  "reviewer_company_size": "1-10 employees",
  "reviewer_industry": "Information Technology and Services",
  "reviewer_time_used": "6-12 months",
  "reviewer_anonymous": false,
  "reviewer_validations": ["ProofOfLink"],
  "incentive": "NominalGift",
  "review_source_code": "NGC",
  "switched_from": ["Microsoft Teams"],
  "switching_reasons": "I went to a new company that uses Slack instead of Teams.",
  "source_site": "Capterra",
  "product_rating": 4.7,
  "product_reviews_total": 24212,
  "product_category": "Team Communication",
  "vendor_name": "Slack",
  "page": 1,
  "position": 11,
  "source_url": "https://www.capterra.com/p/135003/Slack/reviews/",
  "input": "https://www.capterra.com/p/135003/Slack/",
  "scraped_at": "2026-10-01T08:55:30.338Z"
}

A Trello review found by typing the name Trello (local run, 29 September 2026); the reviewer is anonymous:

{
  "review_id": "7210258",
  "product_name": "Trello",
  "product_id": "211559",
  "title": "Notes Organization on Steroids",
  "date": "2026-09-07",
  "rating_overall": 4,
  "likelihood_to_recommend": 8,
  "pros": "Trello is a easy tool to organize and a take your notes on...",
  "cons": "I wish Trello was easier to move notes around on...",
  "reviewer_name": "Verified Reviewer",
  "reviewer_job_title": "Teacher",
  "reviewer_company_size": "201-500 employees",
  "reviewer_industry": "Education Management",
  "reviewer_anonymous": true,
  "reviewer_linkedin_verified": true,
  "incentive": "NominalGift",
  "product_reviews_total": 23622,
  "vendor_name": "Atlassian",
  "input": "Trello"
}

A one star CompanyCam review from the same local run, with the reviewer's reason for choosing the product:

{
  "review_id": "3035478",
  "product_name": "CompanyCam",
  "title": "Horrible customer service",
  "date": "2021-08-23",
  "rating_overall": 1,
  "likelihood_to_recommend": 0,
  "pros": "The features were exactly what we were looking for...",
  "cons": "Horrible customer service. When we had issues it was days before we received a response...",
  "reviewer_name": "S. M.",
  "reviewer_job_title": "Director",
  "reviewer_company_size": "51-200 employees",
  "reviewer_industry": "Construction",
  "chosen_reasons": "can't find another product, please provide recommendations",
  "product_reviews_total": 103
}

A Slack review from page 2, read by the actor's code from a saved Capterra page on 29 September 2026, with the alternatives the reviewer looked at:

{
  "review_id": "7182202",
  "product_name": "Slack",
  "title": "Effective Collaboration Platform for IT and Business Teams",
  "date": "2026-07-09",
  "rating_overall": 5,
  "reviewer_name": "D. R.",
  "reviewer_job_title": "Manager",
  "reviewer_company_size": "11-50 employees",
  "reviewer_validations": ["BusinessEmail", "ProofOfLink"],
  "alternatives_considered": ["Microsoft Teams"],
  "chosen_reasons": "Software productivity, performance and stability.",
  "page": 2,
  "position": 28,
  "source_url": "https://www.capterra.com/p/135003/Slack/reviews/?page=2"
}

Pricing

Pay per event: you pay for each review delivered to your dataset, plus a flat $0.005 per run whatever memory you choose.

Event	Free plan	Starter (Bronze)	Scale (Silver)	Business (Gold) and above
Review delivered (review-scraped), per review	$0.00199	$0.00179	$0.00159	$0.00139
Per 1,000 reviews	$1.99	$1.79	$1.59	$1.39
Run start (run-start), once per run	$0.005	$0.005	$0.005	$0.005

The start fee is our own flat run-start event, not Apify's per GB start event, so it stays $0.005 at any memory setting; it is charged once when the run starts, including a run whose input has no usable product. So 1,000 reviews cost 1,000 times the per review price of your plan, plus $0.005. Product search by name, the date filter, the product details on every row and the unblocking proxy are included. These prices have applied since 1 October 2026, and no price change is scheduled.

Never charged: products Capterra does not have, products with no reviews, pages Capterra refused, reviews outside your date window, a review or product given twice, and the info row. You can also cap a run's spend with Apify's "Max cost per run" setting; the actor stops delivering once the cap is reached and still writes its OUTPUT summary.

FAQ

What is Capterra?

Capterra (capterra.com) is one of the largest review sites for business software, run by Gartner. Reviewers rate a product overall and on ease of use, customer service, features and value for money, answer what they liked and disliked, and Capterra shows their job title, company size, industry and how long they used the product. Capterra shares its reviews with its sister sites GetApp and Software Advice.

How many reviews can I get?

Up to 2,500 per product, for up to 200 products in a run. Capterra shows 100 pages of 25 reviews to visitors who are not signed in, so a product with more reviews cannot be read in full this way: Slack had 24,212 reviews on Capterra on 1 October 2026, and the actor can read 2,500 of them. Set maxReviewsPerProduct to 0 to read everything that is public.

In what order do the reviews come?

Capterra lets only signed in visitors sort or filter reviews, and this actor never signs in, so it always reads a product's reviews in Capterra's public "Most helpful" order. The sort option reorders the rows the actor collected for each product; it cannot ask Capterra for a different set. To get recent reviews, use publishedAfter, or read every public review with 0.

How well does the date filter work?

It suits months, not days. Capterra's public order is not by date: on Slack, the first 50 reviews were all written in 2026 (February to September), yet only 2 of the 6 newest reviews were among them. So "this year" or "6 months" works well, while "the last 7 days" can miss most new reviews. A product stops once 3 pages in a row each hold fewer than 3 reviews inside your window, so a thin window does not read 100 pages for a handful of rows.

How long does a run take?

Capterra puts a Cloudflare check in front of every page, so pages come through Apify's unblocking proxy and take longer than plain web pages: 35 to 56 seconds in our first tests, and 67 seconds on our Apify test run. The actor keeps up to 4 pages in flight at once, so 1,000 reviews (40 pages) should take about 10 minutes. The default run timeout is 1 hour; raise it in the run options for very large runs. If a run reaches its timeout, the reviews already collected are saved and the OUTPUT summary is written.

Do I need a Capterra account, cookies or my own proxy?

No. The actor reads public pages only, never signs in, and uses Apify's unblocking proxy, which is included in the price. It reads robots.txt at the start of every run and only requests pages it allows: product reviews pages and the product search that Capterra's search box uses. It never opens Capterra's /search pages or any page that needs an account.

Can I give a product name instead of a link?

Yes. Type the name as Capterra lists it, for example Trello. An exact name match wins, then a matching slug, then Capterra's first suggestion. Use the product link when several products have similar names; the OUTPUT summary shows which product each name matched.

Does it work for GetApp and Software Advice?

Their links are not accepted. Because the three sites share reviews, give the Capterra link or the product name instead; source_site tells you where each review was written.

Why did a product return fewer reviews than I asked for?

The product has fewer public reviews, your date window left fewer, the same review was already delivered for another input, or a page was refused on every attempt (the first page gets three attempts, later pages two; a product stops after 3 refused pages in a row). The OUTPUT summary gives each product's status and stop_reason. Refused pages are not charged.

Does it include vendor replies or "advice to others"?

Not confirmed. None of the 100 reviews we checked on 29 September 2026 had a public vendor reply or an "advice to others" answer, so we have not seen the actor return either. If you need them, tell us on the Issues tab with a product that has them.

Can I run it on a schedule?

Yes. Save your input, then in Apify Console open this actor, go to Schedules and add one. The actor does not remember earlier runs, so use publishedAfter with a window of a few months and keep review_id as the key in your sheet or database to drop reviews you already have.

Can I use it from Claude, ChatGPT or another AI assistant?

Yes. Add it to Claude Code in one line with claude mcp add --transport http apify "https://mcp.apify.com/?tools=themineworks/capterra-software-reviews-scraper", or point any MCP client at https://mcp.apify.com/?tools=themineworks/capterra-software-reviews-scraper. Then ask, for example, "pull this year's Capterra reviews of Trello and list the top complaints". The "Copy to your AI assistant" block above gives a model everything it needs.

Is it legal to scrape Capterra reviews?

The actor collects public review data that Capterra's robots.txt allows crawlers to read, and it names reviewers only as Capterra itself displays them, with no photos or profile links. It is an independent tool, not affiliated with, endorsed by or sponsored by Capterra or Gartner; Capterra is a trademark of its owner. How you use the data is your responsibility: follow Capterra's terms and the data protection laws that apply to you, such as GDPR in Europe and CCPA in California, because reviewer names, job titles and companies are personal data.

Integrations

• Google Sheets, Excel, CSV, JSON: export the dataset from the run page, or link a Google Sheet with Apify's Google Sheets integration.
• Make, Zapier, n8n: use the Apify app to start a run and pick up the reviews when it finishes.
• Webhooks: get a call to your own endpoint when a run succeeds or fails.
• API: start runs and read results with the Apify API or the apify-client package for Python and JavaScript.
• MCP clients: Claude, ChatGPT, Cursor and other MCP clients can call the actor through Apify's MCP server.

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Support

Found a problem or need a field we do not return? Open an issue on the actor's Issues tab and we will answer there. To ask for a new source, email dmineworks@gmail.com.

Capterra Reviews Scraper turns Capterra product links or names into rows of public software reviews, with every rating, pros, cons, the reviewer's role and switching data, and no charge for anything outside your request.