Software Reviews All-in-One Scraper — G2, Capterra, TrustRadius, SoftwareAdvice, GetApp

Scrape B2B software reviews across 5 platforms with one unified output. Built for SaaS competitive intelligence, sentiment analysis, M&A due diligence, and AI agents.

Auto-detects platform from URL. Returns a single consistent schema across G2, Capterra, TrustRadius, SoftwareAdvice, and GetApp — so you can join reviews across platforms with no data wrangling.

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Why this actor

Most software-reviews scrapers cover one platform. The few that bundle multiple platforms ship different schemas per source and break often. This actor:

• 5 platforms, one schema. Same field names mean same things across G2, Capterra, TrustRadius, SoftwareAdvice, GetApp.
• Auto platform detection. Paste any product URL. We figure out the rest.
• Cross-platform search. Pass searchQuery: "Slack" and platforms: ["g2","capterra","trustradius"] — get product cards from each.
• MCP-ready. Drop into Claude, GPT, or any MCP agent. Tool description and field semantics are written for LLMs first.
• Residential by default. G2 and Capterra block datacenter IPs aggressively. You get residential automatically.
• Graceful degradation. Partial reviews are still pushed. We never lose what we already have.

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What you get

Field	Type	Description
platform	string	g2 / capterra / trustradius / softwareadvice / getapp
recordType	string	review or product (summary card)
productName	string	Product name as listed on platform
productSlug	string	Platform-specific product slug
productUrl	string	Canonical product reviews URL
productRating	number	Aggregate rating (0-5)
productReviewCount	int	Total review count on platform
vendor	string	Vendor / publisher name
category	string	Primary platform category
rating	number	This review's rating
reviewTitle	string	Headline
reviewBody	string	Full review text
pros	string[]	Positive points
cons	string[]	Negative points
subRatings	object	easeOfUse, customerSupport, valueForMoney, features, easeOfSetup, likelihoodToRecommend
reviewer	object	name, title, companyName, companySize, industry, verified
reviewDate	string	ISO 8601 UTC
helpfulCount	int	Helpful votes
vendorResponse	string	Vendor reply, if any
alternativesConsidered	string[]	Other products the reviewer evaluated
switchedFrom	string	Product reviewer switched away from
scrapedAt	string	ISO 8601 UTC scrape time

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Quick start

1. Paste a URL — platform auto-detected

{
  "startUrls": [
    { "url": "https://www.g2.com/products/salesforce-sales-cloud/reviews" },
    { "url": "https://www.capterra.com/p/135003/Slack/reviews/" },
    { "url": "https://www.trustradius.com/products/notion/reviews" }
  ],
  "maxReviewsPerProduct": 100,
  "sortReviewsBy": "newest"
}

2. Search by product name across platforms

{
  "searchQuery": "HubSpot CRM",
  "platforms": ["g2", "capterra", "trustradius"],
  "maxProductsPerSearch": 5,
  "maxReviewsPerProduct": 50,
  "includeReviews": true
}

3. Just discover products (no reviews)

{
  "searchQuery": "project management software",
  "platforms": ["g2", "capterra", "trustradius", "softwareadvice", "getapp"],
  "maxProductsPerSearch": 20,
  "includeReviews": false
}

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Pricing — Pay Per Event

Event	Price
Actor start	$0.005
Review scraped	$0.007 per review with full metadata
Product found	$0.01 per product summary card (search mode)

Typical cost:

• 100 reviews from one G2 product: ~$0.71
• Cross-platform search "Slack" → 5 products × 3 platforms + 50 reviews each: ~$1.21
• 1,000 reviews from one product: ~$7.00

Pay-Per-Usage is also enabled if you prefer compute-based billing for very large jobs.

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How it works

The actor is HTTP-first. Each page is fetched without a headless browser, then parsed in three stages:

1. Embedded JSON (__NEXT_DATA__, __APOLLO_STATE__, JSON-LD) — most reliable, used when available.
2. JSON-LD Product/Review schema — preserved by SEO-conscious platforms.
3. HTML fallback selectors — defensive cascade with multiple selector strategies per platform.

All requests route through Apify residential proxies by default. Failed pages are retried with exponential backoff. Pagination is automatic.

Platform quirks handled

• G2 — multiple selector strategies ([itemprop="review"], paper paper--box, data-poison-target); Cloudflare-resilient session.
• Capterra — pros/cons section detection, sub-rating parsing (5 dimensions).
• TrustRadius — Next.js __NEXT_DATA__ JSON-first extraction; richer fields (alternatives considered, switched-from, ROI).
• SoftwareAdvice + GetApp — Gartner-family shared structure with per-platform routing.

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Use cases

Competitive intelligence

Pull all reviews of a competitor product. Tag pros/cons. Identify churn signals (low sub-ratings on Customer Support correlate with cancellations).

Sentiment over time

Run weekly. Group by month → track sentiment drift. Spot launches that broke things.

M&A due diligence

Before acquiring a SaaS company, scrape all their reviews — across all 5 platforms. Look for fraud (review bombing, suspicious 5-star clusters), category leadership, and reviewer firmographics.

Product roadmap input

Mine cons[] across competitors → identify common pain points → prioritize them in your roadmap.

AI agent: "Compare CRMs for me"

MCP agent calls this actor with searchQuery: "CRM for small business", platforms: ["g2","capterra"], includeReviews: true. Agent gets unified data, summarizes pros/cons across products.

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Code examples

Apify API (Node.js)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });

const run = await client.actor('khadinakbar/software-reviews-all-in-one-scraper').call({
  startUrls: [{ url: 'https://www.g2.com/products/salesforce-sales-cloud/reviews' }],
  maxReviewsPerProduct: 200,
  sortReviewsBy: 'helpful',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")

run = client.actor("khadinakbar/software-reviews-all-in-one-scraper").call(run_input={
    "searchQuery": "Salesforce",
    "platforms": ["g2", "capterra", "trustradius"],
    "maxReviewsPerProduct": 50,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["platform"], item["productName"], item["rating"])

MCP (Claude, GPT, etc.)

Add Apify MCP to your client. Tool will appear as apify--software-reviews-all-in-one-scraper. Call it directly:

{
  "tool": "apify--software-reviews-all-in-one-scraper",
  "input": {
    "searchQuery": "Notion",
    "platforms": ["g2", "capterra", "trustradius"],
    "maxReviewsPerProduct": 30
  }
}

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FAQ

Why residential proxies? G2 and Capterra both deploy Cloudflare with bot management. Datacenter IPs get blocked within 5 requests. Residential pricing is built into the PPE so you don't pay extra.

What if my product isn't found by search? Search relies on each platform's own search results. If a product is missing, find it directly on the platform and paste the URL into startUrls. The actor auto-detects which platform it belongs to.

Can I scrape ALL reviews for a product? Yes — set maxReviewsPerProduct: 5000. The scraper paginates until exhausted or the cap is hit. Note: large products (Slack, Salesforce) have 10K-20K reviews and full scrapes cost real money. Test with smaller caps first.

Does it work for non-English reviews? Yes. Unicode is preserved. Platforms with locale subdomains (e.g., capterra.co.uk, capterra.com.au) are also detected.

What does verified: true mean? The platform marked the reviewer as a verified business user (LinkedIn-verified on G2, employer-domain verified on Capterra). Not all reviews are verified.

Can I get TrustRadius alternatives considered and ROI? Yes — TrustRadius reviews include alternativesConsidered[] and switchedFrom. These fields will be null/empty on other platforms that don't capture them.

Why are some sub-rating fields missing? Each platform exposes a different set of sub-ratings. G2 has 6, Capterra has 4-5, TrustRadius reports a recommendation score, SoftwareAdvice has 4. Fields not provided by the platform are null.

What happens if a platform blocks me mid-run? Per-product errors are isolated. The scraper continues with the next URL or platform. Already-extracted reviews are kept in the dataset.

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Legal & ethics

This actor scrapes publicly available software reviews — the same data any person browsing G2/Capterra/TrustRadius/SoftwareAdvice/GetApp can see. Use cases supported:

• Competitive research and market intelligence
• Sentiment analysis and trend detection
• Academic, journalistic, and industry research
• M&A and investment due diligence

You are responsible for complying with each platform's Terms of Service and applicable law in your jurisdiction (including data-protection law like GDPR/CCPA when processing personal data). Do not use this actor to harass reviewers, impersonate them, manipulate ratings, or republish identifiable personal data without lawful basis. The author is not affiliated with G2, Capterra, TrustRadius, SoftwareAdvice, GetApp, or Gartner.

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Related actors

• amazon-reviews-scraper — consumer product reviews
• producthunt-scraper-pro — Product Hunt launches and reviews
• clutch-scraper — agency reviews
• brand-sentiment-analyzer — sentiment over time
• b2b-lead-finder-enrichment — enrich vendor info with B2B contact data

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Changelog

v1.0 — 2026-05-29

• Initial release
• 5 platforms supported (G2, Capterra, TrustRadius, SoftwareAdvice, GetApp)
• Unified review schema across all platforms
• Auto platform detection from URL
• Cross-platform search mode
• HTTP-first extraction with JSON-LD + __NEXT_DATA__ parsing