Capterra Scraper

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Capterra Scraper ◄── you are here

Capterra Scraper is a dedicated Capterra reviews scraper: scrape Capterra reviews into structured JSON — overall and 5 sub-ratings, pros/cons, vendor replies, reviewer job title / company size / industry, and an LLM-ready markdown field. Paste product URLs, numeric IDs, or search / category inputs. Run incremental monitor so scheduled jobs emit only new reviews, unanswered replies, and rating deltas. Download JSON, CSV, or Excel from the dataset. A practical Capterra API alternative — call from Python, Node.js, cURL, or Apify MCP.

Best for: SaaS competitive intel, win-loss research, review-response ops, product ops, PMM monitoring, and JSON/CSV pipelines.

Capterra (SaaS listings)	Trustpilot (consumer reputation)	Glassdoor (employer intel)
Capterra Scraper ◄── you are here	Trustpilot Scraper	Glassdoor Scraper

When to use this Actor

• You need a Capterra scraper / Capterra reviews scraper for one or many products as JSON, CSV, or Excel
• You want search + reviews + vendor replies in one Actor instead of a single-URL dump
• You schedule new-review monitoring with webhooks instead of re-downloading full histories
• You want a Capterra API alternative from Python, Node.js, or an MCP / AI assistant
• You map a Capterra category or search first, then pull reviews for the shortlist

When not to use this Actor

• Consumer Trustpilot reviews — use Trustpilot Scraper
• Employer reviews / salaries / jobs — use Glassdoor Scraper
• Capterra vendor portal, authenticated dashboards, or writing reviews — public pages only
• Five-site mashups (G2 + Capterra + GetApp + … in one run) — this Actor is Capterra-only

Modes

Mode	What it does
reviews	Product reviews (optional product profile + alternatives)
products	Search or category catalog rows
monitor	Named KV watermarks; emit only new reviews, unanswered vendor replies, and rating/count deltas

Key features

• Search + reviews + vendor replies + monitor in one dedicated Capterra Actor
• Bulk URLs, slugs, and numeric product IDs per run
• Typed dataset rows — product, review, alternative, monitor_event
• Five sub-ratings — ease of use, customer support, functionality, value for money, plus recommendation score
• Vendor replies as { date, text } with onlyUnanswered filter
• Star / date / keyword filters — publishedAfter accepts 2026-08-01 or 7 days
• Incremental monitor — named KV watermarks, early-stop, Slack/Discord/Telegram alerts
• LLM-ready markdownContent per review (omit with compact mode)
• HTTP + US residential — no Capterra login

Input

Parameter	Description
mode	reviews / products / monitor
startUrls / productSlugs / productIds	Review pages, slugs, or IDs (135003)
searchQuery / categorySlug	Catalog discovery (products mode)
maxReviews / maxProducts / maxItems	Caps
sortOrder	newest / helpful / highest / lowest
starRatings / publishedAfter / reviewSearchQuery	Filters
includeVendorReplies / onlyUnanswered	Vendor-reply controls
includeProductProfile / includeAlternatives	Extra row kinds
monitorStoreName / monitorBaselineOnly / earlyStopAfterKnown	Monitor KV
webhookUrl / Telegram fields	Alerts
proxyConfiguration	Use Apify Residential (US)

Example — recent Slack reviews

{
  "mode": "reviews",
  "startUrls": [{ "url": "https://www.capterra.com/p/135003/Slack/reviews/" }],
  "maxReviews": 100,
  "sortOrder": "newest",
  "includeProductProfile": true,
  "includeVendorReplies": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Example — only 1–2 star reviews without a vendor reply

{
  "mode": "reviews",
  "productIds": ["135003"],
  "sortOrder": "lowest",
  "starRatings": ["1", "2"],
  "onlyUnanswered": true,
  "publishedAfter": "30 days",
  "maxReviews": 200
}

Example — monitor baseline then schedule

{
  "mode": "monitor",
  "startUrls": [
    { "url": "https://www.capterra.com/p/135003/Slack/" },
    { "url": "https://www.capterra.com/p/152373/HubSpot-CRM/" }
  ],
  "monitorStoreName": "capterra-reviews-monitor",
  "monitorBaselineOnly": true,
  "earlyStopAfterKnown": 5,
  "notifyOnNewReviews": true,
  "notifyOnUnansweredOnly": true
}

After the baseline run, set monitorBaselineOnly to false. Schedule hourly or daily — later runs emit only new reviews and rating/count deltas.

Example — category / search catalog

{
  "mode": "products",
  "searchQuery": "CRM",
  "maxProducts": 50
}

Output

Each dataset row has a type field: product, review, alternative, or monitor_event.

Field	Description
type	Row kind
productId / productSlug / productName	Capterra product identity
reviewId / globalReviewId	Stable review id (Capterra___7155735)
overallRating	1–5 overall score (number, not a string)
easeOfUse / customerSupport / functionality / valueForMoney	Sub-ratings
recommendationScore	0–10 likelihood to recommend
date	Publish date (YYYY-MM-DD)
title / generalComments	Headline and overall text
pros / cons	Pros / cons when present
vendorResponse	{ date, text } when the vendor replied
hasVendorReply	Boolean for unanswered filters
reviewerName / jobTitle / companySize / industry	Firmographics
alternativeProducts / switchedProducts	Switch-graph mentions
markdownContent	LLM-ready block (omit with compact)

{
  "type": "review",
  "reviewId": "Capterra___7155735",
  "productId": "135003",
  "productSlug": "Slack",
  "productName": "Slack",
  "overallRating": 5.0,
  "easeOfUse": 5.0,
  "customerSupport": 5.0,
  "functionality": 5.0,
  "valueForMoney": 4.0,
  "recommendationScore": 9.0,
  "date": "2026-05-23",
  "title": "Slack ain’t slacking in the features",
  "pros": "Ease of use and value for money for team chat.",
  "cons": "Huddles and screen sharing trail Zoom/Teams.",
  "hasVendorReply": false,
  "vendorResponse": null,
  "reviewerName": "Verified Reviewer",
  "jobTitle": null,
  "companySize": "51–200 Employees",
  "industry": "Computer Hardware"
}

Use cases

Use case	What you get
Competitor battlecards	Pros/cons + switch mentions on your product and rivals
Review-response ops	onlyUnanswered + monitor alerts when a vendor reply is missing
Detractor mining	1–2★ sort + negative-only webhooks
Win-loss research	Firmographics (role, size, industry) and chosen/switching reasons
RAG / LLM pipelines	markdownContent chunks with product/rating metadata
Scheduled monitoring	Only new reviews after a KV baseline
Category mapping	Top products in a Capterra search/category before a review pull

Integration examples

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('crawloop/capterra-scraper').call({
  mode: 'reviews',
  startUrls: [{ url: 'https://www.capterra.com/p/135003/Slack/reviews/' }],
  maxReviews: 100,
  sortOrder: 'newest',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient(token="YOUR_APIFY_TOKEN")
run = client.actor("crawloop/capterra-scraper").call(
    run_input={
        "mode": "reviews",
        "productIds": ["135003"],
        "maxReviews": 200,
        "sortOrder": "helpful",
        "includeVendorReplies": True,
    }
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("title"), item.get("overallRating"), item.get("hasVendorReply"))

cURL

curl -X POST \
  "https://api.apify.com/v2/acts/crawloop~capterra-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"products","searchQuery":"CRM","maxProducts":25}'

MCP and AI assistants

Use this Actor from AI tools via Apify MCP. Connect your Apify account, then call crawloop/capterra-scraper.

Example prompts:

• "Run Capterra Scraper for Slack, max 50 newest reviews, and return overallRating, pros, cons, and vendorResponse as JSON"
• "Scrape 1- and 2-star HubSpot Capterra reviews from the last 30 days that have no vendor reply, then summarize complaints"
• "Chain Capterra Scraper for Slack then Trustpilot Scraper for slack.com and compare B2B vs consumer sentiment"

Suite next step

After a Capterra pull, run Trustpilot Scraper on the same vendor domain for consumer reputation, or Glassdoor Scraper for employer-brand context on the vendor.

FAQ

How do I scrape Capterra reviews?

Paste product review URLs, numeric IDs, or slugs, set mode to reviews, and run. Results land in the default dataset. Use the Python / Node.js / cURL snippets above, or call Capterra Scraper from an MCP / AI assistant.

Do I need a Capterra login or official API key?

No. The Actor reads public product and review pages only — a Capterra API alternative, not the vendor portal.

Can I scrape Capterra reviews with Python or Node.js?

Yes. Use the Apify client snippets above, or call the Actor from an MCP / AI assistant.

Does it export JSON / CSV / Excel?

Yes. Every run writes a dataset you can download as JSON, CSV, or Excel from the run, or pull via API / integrations / MCP.

Why residential proxies?

Capterra sits behind Cloudflare. Datacenter IPs usually get a challenge page. Use Apify Residential (US).

How is this different from other Capterra scrapers?

One Actor for search, bulk products, vendor replies, unanswered filters, and incremental monitor — not a single-URL dump and not a five-site mashup.

Can I scrape a whole Capterra category?

Yes — mode=products with categorySlug or searchQuery, then feed the IDs back in reviews mode.

Does monitor mode re-download the full history every run?

No. After a baseline, later runs emit new reviews and rating/count deltas and can stop early once known reviews appear.

Does slug case matter?

On capterra.com, /p/135003/Slack/ is the canonical product path. The Actor also accepts regional /software/{id}/{slug} URLs.

Related Actors

• Trustpilot Scraper
• Glassdoor Scraper