G2 Reviews Scraper

Extract authentic user reviews from any product page on G2.com — the world's largest software marketplace. This Actor scrapes review titles, ratings, pros/cons, author metadata, and more, delivering structured JSON data ready for analysis, dashboards, or competitive research.

Runs on the Apify platform with automatic proxy rotation, scheduling, and API access — no infrastructure to manage.

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What does G2 Reviews Scraper do?

The G2 Reviews Scraper visits any G2 product reviews page (like https://www.g2.com/products/slack/reviews), parses every review card on the page using BeautifulSoup — a fast, lightweight HTML parser — and extracts structured data fields including the reviewer's name, star rating, review title, full review body, the "pros" and "cons" sections, review date, verified status, company size, and industry. It automatically paginates through multiple pages using G2's ?page=N URL parameter, stopping when it has collected the number of reviews you specify.

Each review is pushed to the Apify dataset, where you can export it as JSON, CSV, Excel, HTML, or XML — or consume it programmatically via the Apify API.

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Why use G2 Reviews Scraper?

Competitive Intelligence

Monitor how users talk about competing products. Track rating trends over time, identify common complaints, and find features users wish existed. Export review data into a spreadsheet or BI tool for side-by-side comparison.

Market Research

Aggregate reviews across multiple product categories to understand what buyers value most — pricing, ease of use, customer support, integrations. The structured data (pros/cons lists, star ratings, company size) makes quantitative analysis straightforward.

Product Management

Feed real user feedback into your product roadmap. Pull verified reviews for your own product to surface recurring themes in what users like and dislike, then share summarized insights with your engineering and design teams.

Lead Generation & Sales Intelligence

Combine reviewer metadata (company size, industry, verified status) with review content to qualify leads. A reviewer who works at an enterprise company and complains about a competitor's lack of a specific feature is a warm lead for your product.

Content Marketing & SEO

Use G2 review excerpts (properly attributed) in case studies, testimonial pages, or social proof sections. The structured format makes it easy to filter for the best quotes by rating or topic.

Academic & Data Science Research

Build datasets of software reviews for sentiment analysis, topic modeling (LDA), or training NLP classifiers. Each review comes with a 1–5 numeric rating — a built-in label for supervised learning.

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How to use G2 Reviews Scraper

1. Find Product Reviews URL

Go to G2.com, search for the product you're interested in, and navigate to its Reviews tab. Copy the full URL from your browser's address bar. It should look like:

https://www.g2.com/products/slack/reviews

2. Configure the Actor

Open the Input tab in Apify Console (or use test-input.json for local runs). Fill in:

• Product Reviews URL — paste the URL from step 1
• Max Reviews — how many reviews to collect (the first 10 are free, then PPE pricing kicks in)
• Minimum Rating — filter out reviews below a star threshold
• Sort Order — newest, most helpful, highest rated, or lowest rated first

3. Run and Export

Click Run (or run locally with apify run --input-file=test-input.json). When the Actor finishes, open the Output tab to browse the scraped reviews in a table. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

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Input

Field	Type	Required	Default	Description
product_url	string	✅	—	Full G2 reviews URL
max_results	integer	❌	25	Max reviews to scrape (1–500)
min_rating	integer	❌	0	Minimum star rating filter (1–5, 0 = no filter)
sort	string	❌	newest	Sort order: newest, most_helpful, highest, lowest
proxyConfiguration	object	❌	Apify RESIDENTIAL	Proxy settings

Example input

{
  "product_url": "https://www.g2.com/products/slack/reviews",
  "max_results": 25,
  "min_rating": 4,
  "sort": "most_helpful"
}

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Output

Each item in the dataset represents one review with the following fields:

{
  "author": "John D.",
  "rating": 4.5,
  "title": "Great for team communication",
  "body": "Slack has transformed how our distributed team communicates...",
  "pros": "Easy to use, great integrations, fast search",
  "cons": "Can be distracting with too many channels",
  "date": "Mar 15, 2025",
  "is_verified": true,
  "company_size": "Mid-Market",
  "industry": "Technology"
}

Data table

Field	Type	Description
author	string	Reviewer display name
rating	number	Star rating (1.0 – 5.0, supports half-stars)
title	string	Review headline
body	string	Full review text
pros	string	What the reviewer liked best
cons	string	What the reviewer disliked or suggested improving
date	string	Publication date
is_verified	boolean	Whether G2 verified the reviewer
company_size	string	Company size category (if available)
industry	string	Reviewer's industry (if available)

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Pricing / Cost estimation

How much does it cost to scrape G2 reviews?

• The first 10 reviews per run are free — no charges applied
• Each additional review beyond 10 incurs a $0.005 PPE (Pay Per Event) charge under the event name result
• A separate $0.00005 charge for apify-actor-start is applied once per run

Example: Scraping 100 reviews costs approximately $0.45 (90 paid reviews × $0.005 + $0.00005 start fee).

Apify's free tier includes $5 of monthly Platform Usage credits for new users — enough to scrape thousands of reviews before hitting any charges.

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Tips & Advanced Options

Proxy Configuration

G2 may block or throttle scrapers that send many requests from the same IP. This Actor defaults to Apify's residential proxy (RESIDENTIAL group), which rotates through real user IPs to avoid detection. If you have your own proxy pool, update the proxyConfiguration field in the input.

Sort Order for Efficient Scraping

If you only need the most recent reviews, use sort: "newest" (default). This gives you the freshest data first and lets you stop early with a smaller result set.

Filtering by Rating

Set min_rating: 4 to collect only positive reviews, or min_rating: 1 to exclude the small number of one-star ratings. Zero means no filter — you get everything.

Rate Limiting and Delays

The BeautifulSoupCrawler handles polite crawling automatically with configurable concurrency, retries, and backoff. G2's pages are static HTML, so no browser overhead is needed — this keeps runs fast and cost-effective.

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FAQ, Disclaimers, and Support

Is scraping G2 legal?

Web scraping of publicly available data (information visible to any website visitor without logging in) is generally legal in most jurisdictions. However, you should review G2's Terms of Service and robots.txt before running this Actor at scale. This Actor is designed for research, competitive analysis, and personal use — always respect the target website's terms.

Does G2 block scrapers?

G2 employs anti-bot protections including Cloudflare challenge pages and rate limiting. Residential proxies are strongly recommended for runs that scrape more than ~50 reviews. The Actor handles 403/429 errors gracefully and will not continue if the page is completely blocked.

What if a field is empty?

Some reviews may not include all metadata fields (e.g., company size or industry). Empty fields are returned as empty strings. The actor skips review cards that contain no meaningful content (less than 50 characters of text).

Can I scrape multiple products in one run?

Not directly. Run the Actor once per product URL. You can automate multiple runs via the Apify API, then merge the datasets programmatically.

Known limitations

• G2 sometimes changes its CSS class names (React CSS modules). The Actor uses multiple fallback selectors per field to stay resilient, but a major layout change may require updating the selectors.
• Reviews behind a login wall (private products) cannot be scraped.
• The Actor does not resolve JavaScript-rendered content — it relies on server-rendered HTML that G2 serves on the first load.

Need help or a custom solution?

Open an issue on the GitHub repository or contact Apify support for custom Actor development, enterprise crawling pipelines, or integration into your existing data stack.