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

Software Reviews Scraper is an Apify Actor for analysts, marketers, operators, and AI agents that need one normalized way to collect B2B software reviews across G2, Capterra, TrustRadius, SoftwareAdvice, and GetApp. It accepts either startUrls for a known product or reviews page, or searchQuery for cross-platform product discovery. Each dataset record represents one review or one product summary card, and the unified output includes platform, product identity, rating details, review text, reviewer firmographics, helpful votes, vendor replies, and scrape timestamps so downstream workflows can compare sources with a consistent schema. This Actor is usable through Apify MCP.

Best fit and connected workflows

This Actor routes well into workflows that need public software-review data in one schema across multiple review sites.

• Direct review collection from a known product page when you already have a G2, Capterra, TrustRadius, SoftwareAdvice, or GetApp URL.
• Cross-platform discovery when you start from a product name and want matching product cards by platform.
• Review-level analysis for sentiment, feature feedback, competitive research, and reviewer context.
• Product-card output for discovery workflows that only need name, rating, review count, vendor, category, and URL.
• Agent workflows through Apify MCP where a tool needs structured review rows or product rows with clear provenance.

Practical scenario

Rina, a SaaS analyst, starts with a TrustRadius reviews URL for Slack and passes it in startUrls. She keeps includeReviews enabled and leaves sorting on newest. The dataset returns platform, productName, rating, reviewTitle, reviewer, reviewDate, and reviewUrl, along with reviewBody, pros, cons, subRatings, and vendorResponse when the platform provides them. Rina uses the reviewer firmographics and review text to group recurring themes, then exports the dataset for a competitive briefing.

Input fields

Field	Type	Purpose
startUrls	array	Product or reviews URLs from G2, Capterra, TrustRadius, SoftwareAdvice, or GetApp. Platform is auto-detected from the domain.
searchQuery	string	Product name to search across enabled platforms.
platforms	array	Platforms used in search mode: g2, capterra, trustradius, softwareadvice, getapp.
maxReviewsPerProduct	integer	Hard cap on reviews scraped per product across all pages.
maxProductsPerSearch	integer	Hard cap on products returned by each search per platform.
includeReviews	boolean	When enabled, scrapes individual reviews. When disabled, returns product summary cards.
sortReviewsBy	string	Review order, either newest or helpful.
proxyConfiguration	object	Apify Proxy settings, with residential routing prefilled by default.
debug	boolean	Dumps the first page of each product to the key-value store for selector diagnostics.

Focused JSON input example

{
  "searchQuery": "Slack",
  "platforms": ["g2", "capterra", "trustradius"],
  "maxProductsPerSearch": 5,
  "maxReviewsPerProduct": 25,
  "includeReviews": true,
  "sortReviewsBy": "newest",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  },
  "debug": false
}

Output fields

Field	Type	Purpose
platform	string	Source platform.
recordType	string	review or product.
productName	string	Product name as listed on the platform.
productSlug	string	Platform-specific product slug.
productUrl	string	Canonical product URL on the platform.
productRating	number or null	Aggregate product rating.
productReviewCount	integer or null	Total review count on the platform.
vendor	string or null	Vendor or company name.
category	string or null	Primary platform category.
rating	number or null	Review star rating.
reviewTitle	string or null	Review headline.
reviewBody	string or null	Full review text.
pros	array	Positive points listed in the review.
cons	array	Negative points listed in the review.
subRatings	object or null	Platform sub-ratings such as ease of use or customer support.
reviewer	object or null	Reviewer firmographics.
reviewDate	string or null	ISO 8601 UTC review publication date.
reviewUrl	string or null	Direct review URL when available.
helpfulCount	integer or null	Number of users who marked the review helpful.
vendorResponse	string or null	Vendor reply to the review, if any.
alternativesConsidered	array	Other products the reviewer considered.
switchedFrom	string or null	Product the reviewer switched away from.
scrapedAt	string	ISO 8601 UTC scrape timestamp.

Illustrative JSON output record

{
  "platform": "trustradius",
  "recordType": "review",
  "productName": "Slack",
  "productSlug": "slack",
  "productUrl": "https://www.trustradius.com/products/slack/reviews",
  "productRating": 4.5,
  "productReviewCount": 1200,
  "vendor": "Slack Technologies",
  "category": "Team Collaboration",
  "rating": 4,
  "reviewTitle": "Easy to use for daily communication",
  "reviewBody": "The interface is straightforward and helps keep project conversations organized.",
  "pros": ["Simple channels", "Fast search"],
  "cons": ["Can get noisy"],
  "subRatings": {
    "easeOfUse": 5,
    "customerSupport": 4
  },
  "reviewer": {
    "name": "Alex",
    "title": "Operations Manager",
    "companyName": "Example Co",
    "companySize": "51-200",
    "industry": "Software",
    "verified": true
  },
  "reviewDate": "2025-01-15T00:00:00.000Z",
  "reviewUrl": "https://www.trustradius.com/reviews/example",
  "helpfulCount": 12,
  "vendorResponse": "Thanks for the feedback.",
  "alternativesConsidered": ["Microsoft Teams", "Google Chat"],
  "switchedFrom": "Email",
  "scrapedAt": "2025-01-20T12:00:00.000Z"
}

How it works

This Actor uses an HTTP-first extraction flow. The live contract shows parsing of embedded JSON sources such as __NEXT_DATA__ and JSON-LD, with HTML fallback selectors when needed. Platform detection happens from the URL in direct-URL mode, and search mode returns matching products from the selected platforms. The dataset uses one unified schema for review rows and product rows, and the output schema also exposes runOutput, runSummary, JSON and CSV dataset links, and a Console dataset view.

Evergreen pricing

This Actor uses Pay per event pricing together with Apify platform usage. The charged events are:

• Actor Start
• Review scraped
• Product found

A simple event-count example: one started run, three product cards, and twenty reviews means one Actor Start event, three Product found events, and twenty Review scraped events. Open the live Pricing tab on the Actor page for the current rates and platform usage details.

Use with AI agents (MCP)

This Actor is available as an Apify Actor usable through Apify MCP. It gives agents a tool for discovering software products, collecting public reviews, and working with a unified dataset across G2, Capterra, TrustRadius, SoftwareAdvice, and GetApp.

Tool description: Scrape reviews or discover products across supported software review platforms with unified review and product-card output, plus dataset provenance and run summary records.

Actor identity: khadinakbar/software-reviews-all-in-one-scraper

Find Slack across G2, Capterra, and TrustRadius. Return product cards first, then collect reviews for the matched products. Keep the newest reviews and preserve the unified schema so I can compare platforms in one table.

When interpreting results, use recordType to separate review rows from product rows. platform identifies the source site, productUrl and reviewUrl provide provenance, reviewDate and scrapedAt support freshness checks, and reviewer provides firmographic context where the source exposes it. In search mode, maxProductsPerSearch controls how many products each platform returns, while maxReviewsPerProduct sets the per-product review cap. Pagination is handled by the Actor, and the event model supports cost-aware planning for agent workflows.

Apify API example

import { ApifyClient } from "apify-client";

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN,
});

const run = await client.actor("khadinakbar/software-reviews-all-in-one-scraper").call({
  searchQuery: "Notion",
  platforms: ["g2", "capterra", "trustradius"],
  maxProductsPerSearch: 3,
  maxReviewsPerProduct: 10,
  includeReviews: true,
  sortReviewsBy: "newest",
});

const { items } = await client.dataset(run.defaultDatasetId).listItems({
  clean: true,
});

console.log(items);

Best results and outcome guidance

Start with a known product reviews URL in startUrls when you already know the target page. Use searchQuery when you want cross-platform discovery by product name or category term. Set includeReviews: false for product-card discovery, then switch it on for review-level analysis. Keep maxReviewsPerProduct aligned with the amount of review evidence you actually need, and use sortReviewsBy to prioritize recent or helpful reviews. The live contract prefill for proxyConfiguration uses Apify residential proxies in the US, which fits the supported platforms.

Continue the workflow

• Then use Trustpilot Scraper — Company Profiles, Search & Categories to extend Software Reviews All-in-One Scraper — G2, Capterra, TrustRadius with a neighboring review and reputation research source when the brief calls for Trustpilot data.
• Then use Kununu Reviews Scraper — Employee Ratings & Feedback to extend Software Reviews All-in-One Scraper — G2, Capterra, TrustRadius with a neighboring review and reputation research source when the brief calls for Kununu data.

Design note

I found that the dataset contract clearly separates summary rows and review rows with recordType, while the output schema exposes both runOutput and runSummary alongside dataset links. That makes it straightforward to automate around terminal status while still keeping the row-level dataset unified.

FAQ

Can I scrape from a direct product page instead of searching?
Yes. Use startUrls with a product or reviews URL from one of the supported platforms.

Can I search by product name across platforms?
Yes. Use searchQuery, and optionally narrow the search with platforms.

What is the difference between includeReviews: true and false?
When enabled, the Actor returns review rows. When disabled, it returns product summary cards with fields like name, rating, review count, vendor, category, and URL.

How do I distinguish review rows from product rows in the dataset?
Check recordType. Use review for review rows and product for product summary cards.

Which fields are useful for provenance?
platform, productUrl, reviewUrl, reviewDate, and scrapedAt are the main provenance fields in the contract.

Can I sort by recency or helpfulness?
Yes. Set sortReviewsBy to newest or helpful.

Responsible use

Use this Actor for public review data collection, research, analysis, and automation in line with the terms and policies of the source platforms and applicable law. Reviewer identities, firmographics, and review text may be personal or sensitive in context, so handle them carefully before republishing or combining them with other sources. Keep usage aligned with legitimate business, research, or compliance workflows.