G2 Scraper — Reviews, Products, Ratings & Competitors

Scrape G2.com reviews and product intelligence from $4.50 per 1,000 reviews. No login, no API key, no code, no proxies to configure — paste a product, a category, a search or a comparison URL and get clean rows.

One input field for everything. A product URL or slug, a category, a G2 search URL, a comparison URL, or just a search phrase — each entry is recognised automatically. No separate field per task.

$4.50 / 1,000 reviews · $0.012 per product profile · $3.00 / 1,000 listing rows · $0.007 per run. Free tier: new Apify users get $5 in platform credits — that's about 1,100 reviews at no cost.

Contents: What it does · Why use it · Data you get · Step by step · Past the 100-review limit · Recipes · Pricing · MCP · Legality · FAQ

What does this G2 Scraper do?

G2.com is the largest B2B software review platform. Its official API is enterprise-only — a sales call, a contract and a procurement cycle before you see a single row. This actor works as an unofficial G2 API: an HTTP endpoint you can call today, with no contract and no login, returning the same publicly visible review and product data as structured JSON.

Pick what you want in What to collect, paste where to start, and each mode returns exactly one record type:

Mode	Record type	What you get
Reviews	review	One row per review: full text of every G2 review question, rating, reviewer job title, industry, company size, verification badges
Product profiles	product	One row per product: rating, review count, categories, top pros & cons, pricing plans, seller, review breakdown, switching data
Listing only	search_result / category_product / comparison_product	The ranked product list from a category, a search or a comparison page
Alternatives & competitors	alternative	The competitor set G2 lists for a product, with ratings and review counts
All G2 categories	category	The full G2 category directory — no input needed

Why use this scraper?

• ✅ 26–31 fields per review — every G2 review question in full, not a truncated snippet
• ✅ 35 fields per product profile, including G2's own ranked top pros and cons
• ✅ Past G2's 100-review ceiling — the site itself never shows more than 10 pages per filter view; this actor slices and de-duplicates to go deeper
• ✅ One input field that accepts products, categories, searches, comparisons, slugs or plain phrases — mixed freely
• ✅ Two steps in one run — start from a search, get reviews for every product it finds
• ✅ One mode, one record type — your dataset is already a single clean table, not a mixed bag needing a filter
• ✅ Exact review breakdowns — counts by company size, reviewer role, industry, region and category
• ✅ Switching data — how many reviewers came from another tool, and where they went after
• ✅ Anti-bot handling and proxy rotation built in — nothing to configure
• ✅ Charge cap respected — set a maximum charge per run and the actor stops there instead of overrunning it

	G2's official API	Typical G2 scrapers	This actor
Access	Enterprise contract, sales call	Apify account	Apify account
Setup	Weeks of procurement	Minutes	Minutes
Input	API keys and docs	Usually one URL type per actor	Products, categories, searches and comparisons in one field
Reviews per product	Contract-dependent	Often capped at what one filter view shows	Sliced past the public 100-per-view ceiling
Review breakdowns by segment/industry/region	—	Rarely	✅ with exact counts
Switching data	—	Rarely	✅ counts in and out
Record types	—	Often mixed in one dataset	One type per run

What data can you extract?

Review fields

Field	Example
rating	4.5
title	Organized Team Communication with Powerful Search
likeBest	Full answer to "What do you like best?"
dislike	Full answer to "What do you dislike?"
problemsSolved	Which problems the product solves for them
recommendations	Advice to other buyers, when the reviewer left any
reviewerName	Diana C.
reviewerJobTitle	Lead Business Efficiency Architect
reviewerIndustry	Information Technology and Services
companySegment / companySize	Mid-Market / 51-1000 emp.
publishedDate / updatedDate	2026-07-29 / 2026-07-31
reviewSource	Organic, G2 invite
isValidatedReviewer / isCurrentUser / isIncentivized / isVideoReview	true / false
badges	["Current User", "Validated Reviewer", "Source: Organic"]
vendorResponse	The vendor's official reply, when present
disclaimer	Any G2 notice attached to the review
reviewId / reviewerId / url	Stable IDs and a direct link to the review
productId / productUuid / vendorId / productName	Join keys back to the product

Product profile fields

Ratings and volume: rating, reviewCount, totalReviews, bestRating, worstRating. Positioning: categories, breadcrumbs, topPros, topCons, tagline, metaDescription. Commercial: pricingPlans (name, price, billing unit), entryPrice, sellerName, sellerUrl, integrationsCount. Breakdowns with exact counts: byCompanySegment, byReviewerRole, byIndustry, byRegion, byCategory. Switching: switchedFrom, switchedTo with review counts per option. Identity: slug, name, url, productId, productUuid, vendorId, imageUrl, operatingSystem.

Listing fields

position, name, slug, url, rating, reviewCount, bestFor (G2's editorial one-liner in category tables), plus sourceUrl, sourceTitle and the query or category the row came from.

How to scrape G2 step by step

1. Sign in to Apify — new accounts get $5 in free monthly credits, enough for roughly 1,100 reviews.
2. Open the actor and choose What to collect (Reviews, Product profiles, Listing, Alternatives, or All categories).
3. Paste your targets into the single input field — slack, https://www.g2.com/categories/crm, https://www.g2.com/search?query=bank, or just project management.
4. Optionally set Max reviews per product, a sort order, and filters for star rating, company size, reviewer role or region.
5. Click Start. Rows appear while the run is still going.
6. Export from the Dataset tab as JSON, CSV, Excel, XML or JSONL — or pull it through the API.

How to get more than 100 reviews per product

G2's own website only ever shows 10 pages — 100 reviews — for any single filter view. Page 11 returns the same rows as page 10. Most scrapers inherit that ceiling silently and simply stop.

This actor works around it: when you ask for more than a single view can give, it collects reviews in slices along G2's own filter axes — star rating, company size, reviewer role, then region — and de-duplicates every row by review ID. Ask for 500 or 5,000 and you get 500 or 5,000 distinct reviews.

Nothing to configure — just set Max reviews per product. Set it to 0 to take everything a product has (Slack alone has over 39,000).

One input field, any starting point

You never pick a different field per task. Paste anything into targets — mix types freely, one per line:

You paste	Recognised as
https://www.g2.com/products/slack/reviews or slack	a product
https://www.g2.com/categories/crm or crm	a category
https://www.g2.com/search?query=bank or project management	a search
https://www.g2.com/compare/slack-vs-microsoft-teams or slack,microsoft-teams	a comparison

Two steps in one run

Because the mode says what you want and the input says where to start, chaining is automatic. Ask for reviews but start from a search, and the actor walks the listing itself, then collects reviews for every product it found:

{
  "scrapeType": "reviews",
  "targets": ["https://www.g2.com/search?query=bank"],
  "maxProductsToFollow": 10,
  "maxReviewsPerProduct": 200
}

The listing is used to find products, and its rows are not added to your dataset — so you are never billed for rows you did not ask for. When the product list itself is what you want, use the Listing mode.

Input parameters

Parameter	Type	Default	Description
scrapeType	select	reviews	What to collect: reviews, product_profile, listing, alternatives, categories_directory
targets	array	—	Products, categories, searches, comparisons, slugs or plain phrases — mixed freely
maxProductsToFollow	integer	10	How many products to scrape from a listing. 0 = no limit
maxReviewsPerProduct	integer	100	Review cap per product. 0 = every review available
sortBy	select	most_recent	most_recent, most_helpful, highest_rated, lowest_rated
stars	array	all	Keep only selected star ratings (5…1)
companySegments	array	all	Small-Business, Mid-Market, Enterprise
reviewerRoles	array	all	User, Administrator, Executive Sponsor, Internal Consultant, Consultant, Agency, Industry Analyst / Tech Writer
regions	array	all	North America, Asia, Europe, Latin America, Middle East, Africa, ANZ
maxItems	integer	0	Hard cap on total records for the run
maxListingPages	integer	1	Pages to walk in a category listing (~20–30 products each)
proxyConfiguration	proxy	Residential US	Proxy used for the run

Ready-to-paste input recipes

Latest reviews for two products

{
  "scrapeType": "reviews",
  "targets": ["https://www.g2.com/products/slack/reviews", "notion"],
  "maxReviewsPerProduct": 500,
  "sortBy": "most_recent"
}

Mine complaints from enterprise buyers

{
  "scrapeType": "reviews",
  "targets": ["salesforce-crm"],
  "stars": ["1", "2"],
  "companySegments": ["Enterprise"],
  "sortBy": "lowest_rated",
  "maxReviewsPerProduct": 200
}

Profiles of the top 20 CRM products

{
  "scrapeType": "product_profile",
  "targets": ["crm"],
  "maxProductsToFollow": 20
}

Reviews for everything a keyword search returns

{
  "scrapeType": "reviews",
  "targets": ["https://www.g2.com/search?query=customer support"],
  "maxProductsToFollow": 15,
  "maxReviewsPerProduct": 100
}

Admin-only reviews from North America

{
  "scrapeType": "reviews",
  "targets": ["hubspot-sales-hub"],
  "reviewerRoles": ["Administrator"],
  "regions": ["North America"],
  "maxReviewsPerProduct": 300
}

Competitor set for a product

{
  "scrapeType": "alternatives",
  "targets": ["slack", "microsoft-teams"]
}

The whole G2 category directory

{ "scrapeType": "categories_directory" }

Output examples

Review row

{
  "type": "review",
  "reviewId": 13183206,
  "url": "https://www.g2.com/products/slack/reviews/slack-review-13183206",
  "rating": 5.0,
  "title": "Organized Team Communication with Powerful Search, Integrations, and Slack AI Summaries",
  "likeBest": "Honestly, the channel organization is what keeps things from falling apart...",
  "dislike": "The notification system drives me crazy. I've spent way too much time...",
  "problemsSolved": "Before Slack, keeping my team aligned was a nightmare...",
  "reviewerName": "Diana C.",
  "reviewerJobTitle": "Lead Business Efficiency Architect",
  "reviewerIndustry": "Information Technology and Services",
  "companySegment": "Mid-Market",
  "companySize": "51-1000 emp.",
  "publishedDate": "2026-07-29",
  "updatedDate": "2026-07-31",
  "reviewSource": "Organic",
  "isValidatedReviewer": true,
  "isCurrentUser": true,
  "badges": ["Current User", "Validated Reviewer", "Source: Organic"],
  "productName": "Slack",
  "productSlug": "slack"
}

Product row

{
  "type": "product",
  "name": "Slack",
  "rating": 4.5,
  "reviewCount": 39229,
  "entryPrice": "$0.00",
  "pricingPlans": [
    { "name": "Free", "price": "$0.00" },
    { "name": "Standard", "price": "$6.67", "unit": "per active user, per month (billed annually)" },
    { "name": "Plus", "price": "$12.50", "unit": "per active user, per month (billed annually)" },
    { "name": "Enterprise Grid", "price": "Contact Us" }
  ],
  "topPros": ["Ease of Use", "Team Collaboration", "Communication", "Integrations", "Features"],
  "topCons": ["Notification Issues", "Missing Features", "Limited Features", "Overwhelming Experience"],
  "categories": ["Business Instant Messaging", "Work Management", "Project Collaboration"],
  "sellerName": "Salesforce",
  "integrationsCount": 460,
  "byCompanySegment": [
    { "value": "Small Business (50 or fewer emp.)", "reviewCount": 15911 },
    { "value": "Mid-Market (51-1000 emp.)", "reviewCount": 15801 },
    { "value": "Enterprise ( >1000 emp.)", "reviewCount": 7155 }
  ],
  "byIndustry": [{ "value": "Computer Software", "reviewCount": 5973 }],
  "byRegion": [{ "value": "North America", "reviewCount": 27240 }],
  "switchedFrom": [{ "label": "Product A", "reviewCount": 346 }],
  "tagline": "All your team's communication, wherever you go."
}

Listing row

{
  "type": "category_product",
  "position": 2,
  "slug": "slack",
  "name": "Slack",
  "url": "https://www.g2.com/products/slack/reviews",
  "rating": 4.5,
  "reviewCount": 39229,
  "bestFor": "Channel-based messaging with deep integrations",
  "sourceTitle": "Best Business Instant Messaging Software"
}

How much does it cost to scrape G2?

Pay only for the records you receive.

Event	Price
Actor start	$0.007 per run
Review	$0.0045
Product profile	$0.012
Listing item (search / category / comparison)	$0.003
Alternative / competitor	$0.003
Category	$0.001

Worked examples, with the arithmetic shown:

Task	Cost
100 reviews for one product	$0.007 + 100 × $0.0045 = $0.46
1,000 reviews for one product	$0.007 + 1,000 × $0.0045 = $4.51
10,000 reviews	$0.007 + 10,000 × $0.0045 = $45.01
100 product profiles	$0.007 + 100 × $0.012 = $1.21
25 products from a search listing	$0.007 + 25 × $0.003 = $0.08
The full G2 category directory	under $0.50

On the free plan, Apify's $5 monthly credit covers roughly 1,100 reviews, 400 product profiles or 1,600 listing rows — enough to evaluate the actor properly before paying anything.

The price is all-in: there is nothing extra to buy on top, and you are never charged for a target that returns no data. Set Maximum charge per run in the actor's options and the run stops when it reaches your cap rather than overrunning it.

Integrations

Because this runs on Apify, the output plugs into the tools you already use — no glue code:

• Google Sheets — auto-export every run's dataset into a sheet.
• Slack / Microsoft Teams — alert on new one- and two-star reviews for your product or a competitor's.
• Make and Zapier — push reviews into a CRM, a warehouse or a ticketing system.
• n8n — self-hosted workflows over the same dataset.
• Webhooks — fire your own endpoint the moment a run finishes.
• API clients — official Python and JavaScript clients, plus plain REST.
• Schedules — run daily or weekly and diff on reviewId to catch only what is new.

Use with AI agents (MCP)

Every Apify actor is reachable through the Apify MCP server, so an AI assistant can run this scraper as a tool. Add it to Claude Desktop, Cursor or VS Code:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=pro100chok/g2-scraper"
    }
  }
}

Then just ask:

"Pull the 200 most recent G2 reviews of Notion, keep only the one- and two-star ones from enterprise reviewers, and summarise the recurring complaints."

Copy to your AI assistant

Paste this block into ChatGPT, Claude or Cursor to have it write the integration for you:

Apify actor `pro100chok/g2-scraper` scrapes G2.com.
Call it: ApifyClient(token).actor("pro100chok/g2-scraper").call(run_input={...})
Input: scrapeType ("reviews" | "product_profile" | "listing" | "alternatives" | "categories_directory"),
targets (array of G2 URLs, product/category slugs, or search phrases),
maxReviewsPerProduct (int), maxProductsToFollow (int),
sortBy ("most_recent" | "most_helpful" | "highest_rated" | "lowest_rated"),
stars (["5".."1"]), companySegments (["Small-Business","Mid-Market","Enterprise"]),
reviewerRoles, regions, maxItems.
Each mode returns one record type, discriminated by the `type` field.
Full schema: GET https://api.apify.com/v2/acts/pro100chok~g2-scraper/builds/default
Get a token at https://console.apify.com/settings/integrations

Popular use cases

• Competitive intelligence — pull a competitor's one- and two-star reviews with stars and sortBy: lowest_rated, then mine dislike for the objections your sales team keeps hearing.
• Win/loss research — switchedFrom and switchedTo show how many reviewers arrived from another tool and how many left.
• Product management — topCons gives G2's own ranked complaint themes; problemsSolved explains what users actually hired the product to do.
• Market research — byIndustry, byCompanySegment and byRegion reveal which segments a product really serves, with exact counts.
• Sales enablement — build battlecards from topPros, topCons, pricingPlans and the competitor set in one run.
• Investor due diligence — track rating and review volume across a category over time with a scheduled run.
• AI and RAG pipelines — full review text with reviewer role, industry and company size makes clean, well-labelled chunks.
• Lead research — category and search listings give you the ranked vendor landscape with ratings and review counts.

Is it legal to scrape G2?

Scraping publicly available web pages is generally legal, and this actor only reads what any visitor can see on G2 — no login, no paywall, no private data. It does not attempt to access anything behind an account.

Review text and reviewer display names are personal data in some jurisdictions. If you store or process them, make sure you have a lawful basis under GDPR, CCPA or the equivalent local rules, and do not use the data to contact, profile or target individual reviewers. When in doubt, talk to your counsel.

Apify has a good primer on the topic: Is web scraping legal?

This is an independent tool. It is not affiliated with, endorsed by or sponsored by G2.com, Inc. All trademarks belong to their respective owners.

FAQ

Does G2 have a public API?

Not an open one. G2's official API is sold on enterprise terms — a sales conversation and a contract before access. This actor gives you the same publicly visible review and product data immediately, with no contract.

How many reviews can I scrape per product?

As many as the product has. G2's own site caps any single filter view at 100 reviews, and this actor goes past that by slicing along G2's filter axes and de-duplicating. Slack has over 39,000 reviews and all of them are reachable; use Max reviews per product to keep runs bounded.

Do I need proxies or an API key?

No. Proxy handling and anti-bot protection are built in, and residential US proxies are the default. You do not need a G2 account or any key.

Can I export G2 reviews to CSV or Excel?

Yes. Every run's dataset exports as CSV, Excel, JSON, XML or JSONL from the Apify Console, or through the API with ?format=csv.

Will I be charged for URLs that return nothing?

No. Charging is per delivered record, so a target with no reviews costs nothing beyond the run start.

Why do some reviews have no job title or industry?

Because the reviewer did not disclose it — those fields are optional on G2's form. Roughly a third of reviews omit the industry. Missing values are left out rather than filled with guesses, and reviews G2 publishes anonymously are flagged with reviewerIsAnonymous.

Can I get only new reviews since my last run?

Use sortBy: "most_recent" with a modest Max reviews per product, run it on a Schedule, and de-duplicate on reviewId. The actor does not keep state between runs, so the diff happens on your side.

Can I filter reviews by date?

There is no date filter. Sort by Most recent and stop at the volume you need — publishedDate and updatedDate are on every row for filtering afterwards.

Does it return the sub-ratings like Ease of Use?

No. G2 renders those only in its interactive interface, so they are not part of the output. What you do get is topPros and topCons — G2's own ranked strengths and complaints per product — plus the full text of every review answer.

Can I get the names of products people switched from?

You get the counts, not the names. G2 deliberately blurs the product names in its switching chart and only shows shares publicly, so switchedFrom and switchedTo carry review counts with placeholder labels.

What does one run return — reviews, products, or both?

Exactly what you asked for. Each mode returns a single record type, so your dataset is one clean table. If you want both reviews and profiles, run the actor twice.

My run returned fewer reviews than the product page shows. Why?

Filters narrow the pool — a star, segment, role or region filter reduces the count, and the review total shown in the actor's output reflects the filtered view. Also check Max reviews per product and Max items, which both cap the run.

Can I scrape a whole category instead of one product?

Yes. Paste a category URL or slug (crm) and pick Listing mode for the product list, or Reviews mode to walk the category and collect reviews for every product in it, bounded by Max products per listing.

How fresh is the data?

Every run fetches live pages — there is no cache. What you get is what G2 shows at that moment.

How fast is a run?

It depends on volume and on G2's response times, so no fixed throughput is promised. Rows stream into the dataset as they are parsed, so you can start using the output before the run finishes.

Feedback & support

Found a bug or need a field that is not in the output? Open an issue on the Issues tab of the actor page and include the run ID — that makes it fast to reproduce and fix. Feature requests for additional G2 pages are welcome.

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• Similarweb Scraper — traffic and audience data for the vendors you shortlist
• Semrush Scraper — keyword and competitor visibility data
• Ahrefs SEO Tools — backlinks and organic traffic estimates
• Meta Ads Library Scraper — what your competitors are advertising right now
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