G2 Reviews Scraper - Software Reviews, Ratings & Product Data

What does G2 Reviews Scraper do?

G2 Reviews Scraper extracts software reviews from g2.com and turns a product URL, a product name, a G2 search term or a G2 category into structured rows: one row per review with the title, star rating, what the reviewer likes, dislikes and the problems the product solves for them, every other answer, the reviewer's role, company size and industry, and the publication date. It can also deliver one row per product: G2 rating, review count and categories, and, on request, the full G2 profile (vendor, description, star distribution, pros and cons themes, review counts per segment, role, industry and region, pricing plans and comparisons). Built for product marketers, competitive-intelligence teams, analysts, investors and AI pipelines.

G2 scraper · G2 reviews API alternative · G2 Crowd review export · G2.com software review data

• The newest reviews first: ask for 100 reviews and you get the 100 most recent ones that match your filters, not 25 of each star level
• G2's own review filters, applied by G2: star rating, company size segment, reviewer role, region, industry (all 149 G2 industries), G2 category and G2's own keyword search inside the reviews, in any combination, plus a date window
• Full histories: set Max reviews per product to 0 and the actor walks G2's filters until every review it can reach is read: 138 of 138 PhantomBuster reviews, 663 of 669 Apify reviews (measured)
• Many products per run: paste product URLs, slugs, G2 ids or exact names, a search term or a category; each product is read once
• Coverage on every product: G2's own review count next to what was read and delivered, in RUN_SUMMARY and on product rows
• Monitor mode: schedule it and receive only reviews published since the last run; optional webhook at the end of each run
• No login, cookies, API key or proxy: reads G2's public review feed; a product page profile is read through Apify's Unblocker only when you ask for it
• Export anywhere: JSON, CSV, Excel, XML; API, schedules, webhooks, Make, Zapier, n8n, Google Sheets, MCP

What data can you get from G2?

🔗 Review id and link (`reviewUrl`)	📝 Review title	📅 Published date
⭐ Star rating, 0-5 in half stars	👍 What the reviewer likes best (`likes`)	👎 What they dislike (`dislikes`)
🧩 Problems solved and benefits	💡 Recommendations to others	📚 Every question and answer (`answers`)
👤 Reviewer name (first name + initial)	🕶️ Verified anonymous reviewer flag	💼 Role on the product (User, Administrator ...)
🏭 Reviewer industry	🏢 Company size (e.g. 51-200 employees)	🌍 Region and market segment (when filtered)
📦 Product name, slug, G2 rating, review count	🗂️ G2 categories	✅ Reviews delivered and whether all were read
🏷️ Vendor, seller, description, logo	📊 Star distribution, pros and cons themes with mention counts	🧮 Review counts per segment, role, category, industry, region
💲 Pricing plans the vendor lists	🌐 Languages, integrations count	🆚 G2 comparison pages

How to scrape G2 reviews with G2 Reviews Scraper

1. Create a free Apify account (it comes with monthly free credit).
2. Open G2 Reviews Scraper and paste one or more G2 product URLs (or slugs such as hubspot-sales-hub, or exact product names such as Postman), a search term or a category.
3. Pick any filters: stars, company size, role, region, industry, keyword, date window.
4. Set Max reviews per product (0 = every review the feed reaches) and switch on Product rows or Product details if you also want product data.
5. Click Start, then download the dataset as JSON, CSV or Excel, or read it through the API.

⬇️ Input

Parameter	Type	What it does
products	list	Product or reviews URLs (https://www.g2.com/products/slack/reviews), slugs (hubspot-sales-hub), G2 numeric ids (3437) or exact product names (Postman)
searchTerms	list	Words for G2's product search (web scraping): the best matches, up to 10 per term
categories	list	G2 category URLs or slugs (https://www.g2.com/categories/crm): the products G2 ranks first, up to 15
maxProductsPerSource	number	Products each search term or category adds (default 10, 1-15)
scrapeReviews	switch	One row per review (default on); off = product rows only
includeProducts	switch	One product row per product: name, rating, review count, categories, reviews delivered (default off)
productDetails	switch	Product rows also carry the G2 profile (default off; one Unblocker page per product)
starRatings	multi-select	5, 4, 3, 2, 1 (G2's buckets: 5 = 4.5-5 stars, 4 = 3.5-4, 3 = 2.5-3, 2 = 1.5-2, 1 = 0-1)
companySizes	multi-select	small_business (50 or fewer employees), mid_market (51-1,000), enterprise (more than 1,000)
reviewerRoles	multi-select	User, Administrator, Executive sponsor, Internal consultant, Consultant, Agency, Industry analyst, Tech writer
regions	multi-select	North America, Europe, Asia, Latin America, Middle East, Africa, ANZ
industries	list	G2 industry names or ids, e.g. Computer Software, Financial Services, Hospital & Health Care
keyword	text	G2's own search inside the review answers, e.g. pricing
reviewCategoryIds	list	Reviews written for these G2 categories of the product, by G2 category id (listed on a product row with details)
reviewsNewerThan / reviewsOlderThan	text	A date (2026-01-31) or an age (30 days, 6 months)
maxReviewsPerProduct	number	The newest N reviews per product (default 100; 0 = every review the feed reaches)
maxItems	number	Reviews across the run (default 1,000; 0 = no cap)
maxRequestsPerProduct	number	G2 feed calls per product (default 400); raise it for the full history of products with thousands of reviews
monitorMode, monitorKey	switch, text	Deliver only reviews published since earlier runs (memory in a named key-value store)
webhookUrl	text	POST a JSON summary (reviews per product + dataset link) when the run ends
maxConcurrency, proxyConfiguration	advanced	Feed calls in parallel (default 6); optional proxy (not needed)

Input JSON

{
  "products": ["https://www.g2.com/products/hubspot-sales-hub/reviews", "Postman"],
  "starRatings": ["1", "2", "3"],
  "companySizes": ["enterprise"],
  "industries": ["Financial Services", "Computer Software"],
  "reviewsNewerThan": "1 year",
  "maxReviewsPerProduct": 200,
  "includeProducts": true
}

Let G2 filter before you do

Stars, company size, role, region, industry, category and the keyword are sent to G2, so only matching reviews are read. Values in a list are combined with OR (stars 1, 2 and 3 = any of them); different filters combine with AND. The date window is checked on each review: with Reviews newer than, the actor stops reading once it is past the date.

Paste products the way you have them

Product pages, reviews pages, slugs and G2 ids all work, and an old slug or alias (hubspot) is followed to the product it now points to (hubspot-marketing-hub). A product name must match G2's name exactly (Postman); when it does not, RUN_SUMMARY lists the closest products so you can paste the right URL. The same product given twice is read once.

How "every review" works

G2 publishes the newest 25 reviews of any combination of its review filters. For more, the actor reads the product filter by filter: star level, then industry groups, then region, company size and role, splitting only the combinations that still hold 25 or more, always the one that limits the newest reviews first. Products with a few hundred reviews come out complete; on products with thousands the walk reaches most of them and RUN_SUMMARY says how many (see Limits).

⬆️ Output

Each review is one row ("type": "review"); product rows have "type": "product". A real review row (Slack, read 2026-10-16; the answers shortened here):

{
  "type": "review",
  "reviewId": "13800348",
  "reviewUrl": "https://www.g2.com/products/slack/reviews/slack-review-13800348",
  "title": "Clean, Intuitive Slack with Powerful Integrations for Remote Teamwork",
  "rating": 5,
  "publishedAt": "2026-10-16T18:02:06.000Z",
  "reviewerName": null,
  "reviewerAnonymous": true,
  "reviewerRole": "User",
  "reviewerIndustry": "Legal Services",
  "companySize": "11-50 employees",
  "likes": "I use Slack every day at work. Our team is fully remote and spread across a few countries ...",
  "dislikes": "My biggest frustration is search. When I'm trying to track down something from a few months ago ...",
  "problemsSolved": "Being a remote team spread across different countries, our biggest challenge is keeping everyone aligned ...",
  "answers": [{ "question": "What do you like best about Slack?", "answer": "I use Slack every day at work. ..." }],
  "productSlug": "slack",
  "productName": "Slack",
  "productRating": 4.5,
  "productReviewCount": 39944
}

A product row carries productName, productSlug, rating, reviewCount, categories, via and position (where it came from), reviewsDelivered and allReviewsRead. With Product details it adds productId, vendorId, vendor, seller, description, logoUrl, starDistributionPct, prosThemes, consThemes, themeMentions, reviewFacets (review counts with the filter id for every company segment, role, category, industry and region), pricingPlans, languages, integrationsCount, compareWith and categoryPath. HubSpot Sales Hub on 2026-10-16: 4.4 from 14,364 reviews, 67% five-star, top pro theme "Ease of Use" (1,215 mentions), 8,612 reviews from small businesses.

Fields and how often they are filled

Measured 2026-10-16 on three runs: Slack's 20 and 100 newest reviews and all 138 PhantomBuster reviews.

Field	Filled
review id, link, title, stars, date, role, likes, dislikes, problems solved, all answers, product name, rating, review count	100%
company size	70-93%
reviewer name (G2 shows first name + initial; the rest are verified anonymous reviewers)	64-74%
reviewer industry (every anonymous reviewer; named reviewers when you filter by one industry)	20-36%
recommendations to others (G2 stopped asking it; older reviews)	0-9%
region, market segment	100% when you filter by one region or segment, else only where the walk split by them
product rows (rating feed)	100%; product details 100% on pages that open, pricing plans only where the vendor lists prices

G2's per-review sub-ratings, NPS, "validated" or "incentivized" badges and helpful votes are not in G2's public review feed, so they are not columns.

How can I use G2 review data?

• 🎯 Product marketing: what buyers praise and criticise, by company size, industry and role, for messaging and battlecards
• 🥊 Competitive intelligence: a competitor's lowest-rated reviews from enterprises, with what they dislike and what they switched for
• 🧩 Feature gaps: mine dislikes across a whole category with the keyword filter (integrations, pricing, support)
• 📊 Market research: ratings, review counts, star distributions and pros/cons themes for the top products of a category
• 💬 Customer success: monitor your own product daily and catch new low ratings
• 🤖 AI and LLM pipelines: clean plain-text answers for summarisation, sentiment and feature-request mining

How much does it cost to scrape G2?

Pay per result, no start fee:

Event	Price	When
Review	$0.000045 per review ($0.045 per 1,000)	every review row
Product row	$0.00009 per product ($0.09 per 1,000)	every product row from the rating feed
Product row with G2 profile	$0.0027 per product	every product row with Product details on (instead of the product row)

Run	Cost
20 reviews (the prefilled demo)	$0.0009
100 reviews	$0.0045
1,000 reviews	$0.045
10 products from a category, rows only	$0.0009
10 products with the G2 profile	$0.027

Filtered-out reviews, duplicates and reviews a monitor run has already delivered are not delivered and not charged. The free monthly credit on an Apify account covers tens of thousands of reviews.

Integrations, API, scheduling and MCP

Run it on a schedule (every morning, for example) with monitor mode to receive only new reviews, and set Webhook URL to get a summary in Slack, Discord, Zapier, Make or n8n when each run ends. Send results to Google Sheets or any app through Apify integrations. Call it from your code with the Python or JavaScript client, or connect AI assistants through the MCP server.

More review scrapers

• 🧾 Capterra Reviews Scraper — Capterra software reviews with sub-ratings and vendor replies
• 🧭 TrustRadius Reviews Scraper — TrustRadius reviews with pros, cons, ROI and feature ratings
• 📱 App Store Reviews Scraper — iOS app reviews with developer replies, many countries
• 🤖 Google Play Reviews Scraper — Android app reviews, replies and versions
• 🏢 Clutch.co Agency Scraper — B2B agencies with ratings and reviews
• 🧳 Tripadvisor Reviews Scraper — hotel, restaurant and attraction reviews

All our actors: apify.com/scrapersdelight.

Limits and empty runs

• G2's public review feed carries the newest 25 reviews of a filter combination; the actor combines G2's filters to go further. Measured on a direct connection: Slack's 100 newest reviews in 27 feed calls (11 s), HubSpot Sales Hub's in 39 (15 s), Postman's in 91 (40 s); every one of PhantomBuster's 138 reviews in 24 calls (12 s); 663 of Apify's 669 in 158 calls (78 s); 1,000 of lemlist's 2,433 in 285 calls (2 min).
• On products with thousands of reviews, some combinations still hold 25+ reviews after every G2 filter is applied; older reviews inside them are out of the feed's reach. A breadth-first walk of the whole history read 84% of lemlist (2,433) and 73% of Postman (1,796); RUN_SUMMARY reports coveragePct against G2's own count on unfiltered runs.
• Reviews come newest first in G2's own order, which follows the published date closely (a few reviews sit days off it).
• Categories and product profiles are read through Apify's Unblocker, about 30-50 s per page. When a product page cannot be opened, the product row carries the rating-feed fields and is charged as a plain product row; the reason is in RUN_SUMMARY.
• When G2 refuses a connection, the actor moves by itself to proxies; nothing refused is ever delivered or charged.
• An empty run (nothing matches) costs nothing. RUN_SUMMARY lists, per product, G2's review count, reviews read and delivered, whether every review was read, why the walk stopped, products that do not exist and inputs it could not resolve.

❓ FAQ

How much does G2 Reviews Scraper cost?

$0.045 per 1,000 reviews and $0.09 per 1,000 product rows; product rows with the G2 profile are $0.0027 each. There is no start fee, and nothing is charged for an empty run.

How many reviews can G2 Reviews Scraper get?

Every review of the product that G2's public feed reaches for your filters: complete histories on products with a few hundred reviews, most of the history on larger ones. Set Max reviews per product to 0 for the full history; the run reports G2's own count next to what it delivered.

Does G2 Reviews Scraper return the newest reviews?

Yes. Reviews are delivered newest first, and a capped run (for example 100 per product) returns the newest 100 that match your filters.

Can G2 Reviews Scraper monitor new reviews?

Yes. Turn on Monitor mode and schedule the run. Each run delivers only reviews published since the reviews earlier runs delivered, and the webhook can post a summary when it ends.

Can G2 Reviews Scraper filter by industry, company size or role?

Yes, and G2 applies those filters itself: star rating, company size segment, reviewer role, region, all 149 G2 industries, G2 category and a keyword inside the reviews, plus your own date window.

Does G2 Reviews Scraper need a login, cookies or an API key?

No. It reads G2's public review feed with no account, cookie or API key, and needs no proxy.

Can G2 Reviews Scraper get product data such as ratings, pros and cons and pricing?

Yes. Product rows give the G2 rating, review count and categories for every product; Product details adds the vendor, description, star distribution, pros and cons themes with mention counts, review counts per segment, role, industry and region, pricing plans and comparisons. Turn Scrape reviews off to get product rows only, for example for the top products of a category.

Can I use G2 Reviews Scraper with the Apify API?

Yes. Start runs and read datasets with the Apify API or its Python and JavaScript clients; every input above is a JSON key.

Can AI agents use G2 Reviews Scraper through MCP?

Yes. Add it to the Apify MCP server and let your assistant pull G2 reviews as plain-text rows.

Why did G2 Reviews Scraper return no results?

Usually the filters exclude everything, or a product name did not match exactly. Open RUN_SUMMARY: it shows reviews read and delivered per product, products not found, and the closest names for inputs it could not resolve.

Why are some reviewer names empty in G2 Reviews Scraper?

G2 shows many reviewers as "Verified User" without a name (26-36% of reviews in our runs). For those, reviewerAnonymous is true and G2 prints their industry instead.

Is it legal to scrape G2 reviews?

The actor reads review data that is public and needs no login, and collects only what G2 already publishes. How you may store and use that data depends on your jurisdiction and on G2's terms, so check both before running at scale. This is not legal advice.

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