B2B Review Intelligence Scraper

Extract and analyze customer reviews from Trustpilot, G2, and Capterra at scale. Get sentiment analysis, rating breakdowns, and actionable insights for competitive intelligence and market research.

What is B2B Review Intelligence Scraper?

B2B Review Intelligence Scraper is a professional web scraping tool designed for businesses, product managers, and market researchers who need comprehensive review data from major B2B platforms. Instead of manually collecting reviews from Trustpilot, G2, and Capterra, this actor automates the entire process and provides structured, analysis-ready data.

The scraper is ideal for competitive intelligence teams tracking competitor performance, product managers researching customer pain points, marketing teams extracting testimonials, and sales teams identifying competitor weaknesses. It supports batch processing of multiple companies, automatic sentiment classification, and extraction of pros/cons from reviews where available.

Unlike manual review collection or simple scraping tools, this actor aggregates data across multiple platforms, calculates average ratings, identifies sentiment trends, and extracts the most mentioned pros and cons using keyword frequency analysis. The output is structured for immediate integration with business intelligence tools, CRM systems, or custom analytics pipelines.

Output Data Fields

All output data is structured per company with aggregated metrics and individual review details.

Field	Type	Description
companyName	String	Company name as provided in input
averageRating	Number	Average star rating across all reviews (0-5 scale, rounded to 2 decimals)
totalReviews	Integer	Total number of reviews scraped across all platforms
platforms	Array of Strings	List of platforms where reviews were found (e.g., ["trustpilot", "g2"])
sentimentBreakdown	Object	Count of positive, neutral, and negative reviews
sentimentBreakdown.positive	Integer	Number of reviews with rating 4 stars or higher
sentimentBreakdown.neutral	Integer	Number of reviews with rating exactly 3 stars
sentimentBreakdown.negative	Integer	Number of reviews with rating below 3 stars
topPros	Array of Strings	Top 5 most mentioned keywords from pros sections (word frequency analysis)
topCons	Array of Strings	Top 5 most mentioned keywords from cons sections (word frequency analysis)
reviews	Array of Objects	Full list of individual review objects (see below)
reviews[].companyName	String	Company being reviewed
reviews[].platform	String	Review platform source (trustpilot, g2, or capterra)
reviews[].reviewerName	String	Name of the person who wrote the review (or "Anonymous")
reviews[].rating	Number	Star rating on a 1-5 scale
reviews[].title	String	Review headline or title
reviews[].text	String	Full text content of the review
reviews[].date	String or Null	Review date in ISO 8601 format when available
reviews[].pros	String or Null	Pros mentioned in the review (G2 and Capterra support this field)
reviews[].cons	String or Null	Cons mentioned in the review (G2 and Capterra support this field)
reviews[].recommendsProduct	Boolean	Whether the reviewer recommends the product (true if rating >= 4)

Tutorial: How to Scrape B2B Reviews in 7 Steps

Step 1: Create an Apify Account

Sign up for a free Apify account at apify.com. The free tier includes enough compute units to test the actor and scrape reviews for several companies.

Step 2: Open the B2B Review Intelligence Scraper

Navigate to the Apify Store and search for "B2B Review Intelligence Scraper" by lanky_quantifier, or use the direct actor link. Click "Try for free" to add it to your account.

Step 3: Configure Company Names

In the input form, add the companies you want to analyze. You can use company names (e.g., "slack") or domains (e.g., "asana.com"). The actor will automatically construct review URLs for each platform.

Step 4: Select Review Platforms

Choose which platforms to scrape from the dropdown: Trustpilot, G2, and Capterra are available. You can select all three or focus on specific platforms depending on your needs.

Step 5: Set Maximum Reviews Per Company

Configure how many reviews to collect per company per platform. For quick analysis, use 20-30 reviews. For comprehensive research, use 100-150 reviews. The maximum is 200 reviews per company per platform.

Step 6: Start the Actor

Click "Start" to begin scraping. The actor will open each platform in a browser, extract reviews, and aggregate the data. Typical run time is 2-5 minutes for 3 companies with 50 reviews each.

Step 7: Download or Export Results

Once complete, view results directly in the Apify Console or export to JSON, CSV, Excel, or connect via API. Use the data for competitive analysis, customer research, or business intelligence dashboards.

Input Parameters

Configure the scraper behavior using these parameters:

Parameter	Type	Required	Default	Description
companies	Array of Strings	Yes	None	List of company names or domains to scrape reviews for. Examples: ["slack", "asana.com", "monday", "notion"]
platforms	Array of Strings	No	["trustpilot", "capterra", "g2"]	Review platforms to scrape. Available options: "trustpilot", "capterra", "g2". You can select one, two, or all three platforms.
maxReviewsPerCompany	Integer	No	50	Maximum number of reviews to scrape per company per platform. Minimum value is 1, maximum is 200. Higher values increase run time and compute costs.
proxyUrl	String	No	None	Optional custom proxy URL in format http://username:password@proxy.com:port. If not provided, Apify's residential proxies will be used automatically.

Example Input

{
  "companies": [
    "slack",
    "asana",
    "monday.com",
    "notion"
  ],
  "platforms": [
    "trustpilot",
    "g2",
    "capterra"
  ],
  "maxReviewsPerCompany": 75
}

Example Output

{
  "companyName": "slack",
  "averageRating": 4.28,
  "totalReviews": 142,
  "platforms": [
    "trustpilot",
    "g2",
    "capterra"
  ],
  "sentimentBreakdown": {
    "positive": 112,
    "neutral": 18,
    "negative": 12
  },
  "topPros": [
    "integration",
    "communication",
    "interface",
    "channels",
    "notifications"
  ],
  "topCons": [
    "pricing",
    "performance",
    "notifications",
    "mobile",
    "search"
  ],
  "reviews": [
    {
      "companyName": "slack",
      "platform": "trustpilot",
      "reviewerName": "Michael Thompson",
      "rating": 5,
      "title": "Essential tool for remote teams",
      "text": "Slack has completely transformed how our distributed team collaborates. The ability to organize conversations into channels keeps everything structured and searchable. Integrations with tools like GitHub, Jira, and Google Drive save us hours every week. The mobile app works flawlessly, and notifications are highly customizable. After two years of daily use, I cannot imagine working without it.",
      "date": "2024-11-22T14:35:00Z",
      "pros": null,
      "cons": null,
      "recommendsProduct": true
    },
    {
      "companyName": "slack",
      "platform": "g2",
      "reviewerName": "Jennifer Martinez",
      "rating": 4,
      "title": "Powerful but pricey",
      "text": "Slack offers excellent features for team communication and project management. The search functionality and threading make it easy to track conversations. However, the pricing can be steep for larger teams, and performance occasionally lags with heavy usage.",
      "date": "2024-10-18T09:12:00Z",
      "pros": "Intuitive interface, extensive integrations, excellent search, customizable notifications, reliable uptime",
      "cons": "High cost for premium tiers, occasional performance issues, mobile app less feature-rich, steep learning curve for advanced features",
      "recommendsProduct": true
    },
    {
      "companyName": "slack",
      "platform": "capterra",
      "reviewerName": "David Chen",
      "rating": 3,
      "title": "Good but not perfect",
      "text": "Slack is a solid communication platform with many useful features. It works well for day-to-day messaging and has good third-party integrations. That said, the notification management can be overwhelming, and the pricing structure is not ideal for small businesses.",
      "date": "2024-09-05T16:45:00Z",
      "pros": "Easy to set up, good integrations, organized channels",
      "cons": "Expensive for small teams, notification overload, limited free tier",
      "recommendsProduct": false
    }
  ]
}

Legal and Terms of Service

This actor is designed to extract publicly available review data from Trustpilot, G2, and Capterra for legitimate business purposes such as competitive intelligence, market research, and customer sentiment analysis. Users are responsible for ensuring their use of this actor complies with all applicable laws, regulations, and the terms of service of the scraped platforms.

Web scraping of publicly accessible data is generally legal under US law, as established in cases like hiQ Labs v. LinkedIn. However, users should review the specific terms of service for each platform and ensure compliance with data protection regulations such as GDPR and CCPA. This actor does not extract personal contact information beyond publicly displayed reviewer names. Use the scraped data responsibly and ethically, and do not republish review content without proper attribution or in violation of copyright laws.

Pricing and Compute Units

The cost to run this actor depends on the number of companies, platforms, and reviews per company. Pricing is based on Apify compute units, which are consumed during the scraping process.

Typical consumption rates:

• 1 company, 50 reviews per platform, 3 platforms: approximately 0.02-0.04 compute units (about $0.002-0.004 USD)
• 5 companies, 100 reviews per platform, 3 platforms: approximately 0.15-0.25 compute units (about $0.015-0.025 USD)
• 20 companies, 150 reviews per platform, 3 platforms: approximately 0.8-1.2 compute units (about $0.08-0.12 USD)

The Apify free tier includes $5 worth of compute units per month, sufficient for scraping dozens of companies. Paid plans start at $49/month with significantly higher limits. Platform-specific anti-bot measures may increase compute usage due to retries or longer page load times. For large-scale scraping operations, consider running the actor during off-peak hours or using Apify's scheduled runs feature to spread the load.

Frequently Asked Questions

How accurate is the sentiment analysis?

The sentiment classification is based on star ratings: 4+ stars are positive, 3 stars are neutral, and below 3 stars are negative. This method provides approximately 85-90% accuracy for general sentiment. For more nuanced analysis, use the raw review text with external NLP tools.

Can I scrape reviews in languages other than English?

Yes, the actor extracts review text in any language displayed on the platform. However, the keyword extraction for top pros and cons currently works best with English text. Multi-language support for keyword analysis may be added in future versions.

What happens if a company is not found on a platform?

The actor will log a message indicating the company was not found and continue scraping other platforms. Failed requests do not stop the overall scraping process, ensuring you still get data from available platforms.

How often can I run this actor without being blocked?

The actor uses residential proxies and browser fingerprinting to minimize detection. For best results, space runs at least 1-2 hours apart for the same companies. Scraping 5-10 companies per run is generally safe. Very large batches (50+ companies) should be split across multiple runs.

Can I integrate this actor with my own tools?

Absolutely. Apify provides REST API access, webhooks, and integrations with Zapier, Make, and other automation platforms. You can also export data to Google Sheets, BigQuery, or download it programmatically via the Apify API client libraries for JavaScript, Python, and other languages.

Related Actors

Explore other scrapers by lanky_quantifier for comprehensive business intelligence:

• Google Maps Contact Info Scraper - Extract business contact details, addresses, and phone numbers from Google Maps for lead generation and market research
• Amazon Product Review Scraper - Collect customer reviews, ratings, and product sentiment from Amazon listings for e-commerce competitive analysis
• LinkedIn Company Scraper - Gather company profiles, employee counts, and business information from LinkedIn for B2B prospecting and market intelligence
• Reddit Thread Scraper - Extract discussions, comments, and sentiment from Reddit threads for brand monitoring and trend analysis
• Twitter Profile Scraper - Collect tweets, follower metrics, and engagement data from Twitter profiles for social media analytics

For questions, support, or custom scraping solutions, contact the actor developer through Apify or visit the actor's GitHub repository for documentation and updates.