G2 Scraper

Scrape G2.com software reviews, products, analytics, comparisons, and discussions. Rich faceted filtering (primary region, review source, response type, sentiment themes, discount), facet-value discovery, 72 review fields, NLP sentiment themes, and switching intelligence. No proxy needed.

Why use this scraper?

• Scrape a product's full review history (maxReviewsPerProduct: 0 for no limit), no anti-bot bypass needed.
• Structured pros/cons/benefits parsed from each review.
• Per-dimension ratings: ease of use, setup, support, security, and more.
• NLP-extracted sentiment themes (what users love/hate).
• Competitive switching intelligence (what products users switched from and why).
• Faceted filtering: narrow reviews by primary region, review source, response type, loved/hated/switching themes, and discount.
• Facet-value discovery: list the valid values for any text facet before filtering.
• Analytics mode with aggregations, percentiles, and significant terms.
• Side-by-side product comparisons in a single request.
• Q&A discussion threads per product.

Use cases

• Compare competitors by sentiment, ratings, and switching patterns.
• Feed structured review data into NLP / AI pipelines.
• Track review trends over time for market research.
• Segment reviews by region, company size, review source, or sentiment theme.
• Find products by category, vendor, or keyword search.
• Search across all reviews for specific topics.

How to use

Scrape reviews for a product

{
  "products": ["https://www.g2.com/products/slack/reviews"]
}

Search for products and scrape their reviews

{
  "search": "project management",
  "maxProducts": 5,
  "maxReviewsPerProduct": 50
}

Browse a category

{
  "category": "CRM",
  "maxProducts": 10,
  "maxReviewsPerProduct": 20
}

Browse by vendor

{
  "vendor": "Salesforce",
  "maxProducts": 5,
  "maxReviewsPerProduct": 10
}

Compare products side-by-side

{
  "compare": ["slack", "clickup", "jira"]
}

Get analytics (no individual reviews)

{
  "products": ["slack"],
  "analytics": true
}

Global review search across all products

{
  "reviewSearch": "terrible customer support",
  "maxReviews": 50
}

Find similar reviews

{
  "similarTo": "The API was difficult to integrate and documentation was poor",
  "maxReviews": 20
}

Filter by date, rating, and company size

{
  "products": ["slack"],
  "dateFrom": "2025-01-01",
  "ratings": ["1", "2"],
  "companySegment": ["enterprise"],
  "maxReviewsPerProduct": 100
}

Filter by facets (region, source, themes)

{
  "products": ["slack"],
  "primaryRegions": ["Americas"],
  "sourceTypes": ["organic"],
  "responseTypes": ["video"],
  "maxReviewsPerProduct": 50
}

Discover valid facet values

Returns the distinct values for each facet to the metadata dataset, so you know what to pass to the facet filters above. No reviews are scraped in this mode.

{
  "enumFields": ["source_type", "response_type"]
}

Search within reviews with highlights

{
  "products": ["slack"],
  "reviewSearch": "customer support",
  "includeHighlights": true,
  "maxReviewsPerProduct": 20
}

Include Q&A discussions

{
  "products": ["slack"],
  "maxReviewsPerProduct": 10,
  "includeDiscussions": true
}

Input

Parameter	Type	Default	Description
products	string[]		Product URLs, slugs, or category URLs
search	string		Find products by keyword
category	string		Browse products by G2 category
vendor	string		Browse products by vendor name
compare	string[]		Compare products side-by-side (analytics)
maxProducts	number	10	Max products in search/category/vendor mode
sortBy	select	DATE_DESC	DATE_DESC, DATE_ASC, RATING_DESC, RATING_ASC, HELPFUL_DESC, G2_DEFAULT
ratings	string[]	["1","2","3","4","5"]	Filter by star rating; values "1"–"5"
maxReviewsPerProduct	number	20	Max reviews per product (0 = unlimited)
companySegment	string[]		small_business, mid_market, enterprise
dateFrom	string		ISO date, reviews from this date
dateTo	string		ISO date, reviews until this date
primaryRegions	select[]		Americas, Asia Pacific, EMEA
sourceTypes	string[]		Filter by how the review was collected; use enumFields to list valid values
responseTypes	string[]		Filter by review medium (e.g. text, video)
loveThemes	string[]		Filter by themes reviewers praised
hateThemes	string[]		Filter by themes reviewers criticized
switchingThemes	string[]		Filter by reasons reviewers switched products
discounts	string[]		Filter by reported discount
reviewSources	string[]		Filter by review source channel
reviewSearch	string		Search within review text. Alone = global search
similarTo	string		Find reviews similar to this text
reviewIds	string[]		Fetch specific reviews by ID
maxReviews	number	100	Max reviews for global/similar search
enumFields	select[]		Discover distinct values for facets; writes to the metadata dataset instead of scraping reviews
analytics	boolean	false	Return aggregation analytics instead of reviews
collapseByProduct	boolean	false	One review per product in global search
includeNonPublic	boolean	false	Include non-public/rejected reviews
includeDiscussions	boolean	false	Fetch Q&A discussion threads per product
includeHighlights	boolean	true	Highlight matching text in search results

At least one input mode is required (products, search, category, vendor, reviewSearch, similarTo, reviewIds, compare, enumFields, or analytics). Filters apply to all matched reviews.

Output

Datasets

Dataset	When	Content
reviews (default)	Most modes	Individual review records
products	Product-based modes	Product profiles
analytics	analytics or compare mode	Aggregation statistics
discussions	includeDiscussions: true	Q&A threads
metadata	enumFields mode	Distinct facet values

Review fields

{
  "id": "13038740",
  "productId": 3437,
  "productName": "Slack",
  "reviewUrl": "https://www.g2.com/products/slack/reviews/13038740",
  "title": "One-Click Integrations That Just Work for slack",
  "pros": "Integration with other apps has to be 1 click",
  "cons": "UI when you send the messages. The typing window should be adjustable",
  "benefits": "connect and chatting with the team One-Click Integrations That Just Work for slack",
  "rawText": "Integration with other apps has to be 1 click\nUI when you send the messages. The typing window should be adjustable\nconnect and chatting with the team One-Click Integrations That Just Work for slack",
  "responseType": "text",
  "nps": 8,
  "npsScore": 4,
  "easeOfUse": 5,
  "easeOfSetup": 5,
  "easeOfAdmin": 5,
  "easeOfDoingBusinessWith": 4,
  "meetsRequirements": 5,
  "qualityOfSupport": 3,
  "securityConfidence": 3,
  "securityImportance": 7,
  "direction": null,
  "userName": "Sameer G.",
  "country": "India",
  "region": "Asia",
  "primaryRegion": "Asia Pacific",
  "companySegment": 180,
  "companySegmentLabel": "Mid-Market (51-1000 emp.)",
  "industry": 313,
  "industryLabel": "Information Technology and Services",
  "role": 6,
  "roleLabel": "Consultant",
  "loveTheme": null,
  "loveThemeHumanized": null,
  "loveThemeParentHumanized": null,
  "hateTheme": null,
  "hateThemeHumanized": null,
  "hateThemeParentHumanized": null,
  "switchedFromOtherProduct": "unknown",
  "switchedFromProductIds": null,
  "switchedReason": null,
  "switchingThemes": null,
  "switchingThemesNested": null,
  "submittedAt": "2026-06-26T17:10:48.781-05:00",
  "publishedAt": "2026-06-26T19:30:00.900-05:00",
  "reviewSource": "user_profile",
  "sourceType": "user_profile",
  "helpful": 0,
  "englishAvailable": true,
  "contractLength": null,
  "discount": null,
  "price": 5,
  "status": "approved",
  "isPublic": true,
  "published": true,
  "productPaidProfile": false,
  "productIds": [3437],
  "categoryIds": [2174, 2360, 2363],
  "defaultSort": 8.525176115868225,
  "templateKeyword": "react",
  "videoReviewSubmittedAt": null,
  "editionIds": [],
  "expertiseIds": [],
  "serviceLocation": null,
  "contractLengthWeight": null,
  "discountWeight": null,
  "everApproved": true,
  "isInLimbo": false,
  "read": false,
  "reportable": true,
  "userUpdatedAt": "2026-06-26T17:10:48.965-05:00",
  "highlightedSnippets": null,
  "scrapedAt": "2026-06-28T06:00:34.982Z"
}

Analytics output

Aggregated over all of a product's reviews. nps/easeOfUse/etc. each carry avg, stdDev, min, max, and count; the full record also includes easeOfSetup, easeOfAdmin, qualityOfSupport, meetsRequirements, easeOfDoingBusinessWith, securityConfidence, securityImportance, direction, topHateThemes, uniquelyHated, and bySourceType. The theme, demographic, and reviewsOverTime arrays are trimmed below for brevity.

{
  "productId": 3437,
  "productName": "Slack",
  "productSlug": "slack",
  "totalReviews": 20201,
  "totalHelpfulVotes": 69,
  "nps": { "avg": 9.211870699470323, "stdDev": 1.1668658162744323, "min": 0, "max": 10, "count": 20201 },
  "easeOfUse": { "avg": 6.549680122289532, "stdDev": 0.7953808393082141, "min": 1, "max": 7, "count": 17663 },
  "ratingDistribution": { "1": 40, "2": 93, "3": 468, "4": 3646, "5": 15954 },
  "npsPercentiles": { "p10": 8, "p25": 9, "p50": 10, "p75": 10, "p90": 10 },
  "uniqueCountries": 140,
  "uniqueIndustries": 145,
  "topLoveThemes": [
    { "theme": "Chat", "count": 3436, "sampleReviews": [{ "title": "Slack Review", "userName": "Hunter C.", "npsScore": 4 }] },
    { "theme": "Collaboration", "count": 2254, "sampleReviews": [{ "title": "\"Ping\" From Your Creative Side", "userName": "Daniel G.", "npsScore": 5 }] }
  ],
  "uniquelyLoved": [
    { "theme": "Chat", "score": 3.472215696777018, "count": 3436 },
    { "theme": "Collaboration", "score": 1.2096931571663356, "count": 2254 }
  ],
  "switchingReasons": [
    { "reason": "Ease of use", "count": 126 },
    { "reason": "Communication Features", "count": 108 }
  ],
  "bySegment": [
    { "code": 179, "label": "Small Business (50 or fewer emp.)", "count": 8191 },
    { "code": 180, "label": "Mid-Market (51-1000 emp.)", "count": 8141 },
    { "code": 181, "label": "Enterprise (>1000 emp.)", "count": 3516 }
  ],
  "byRegion": [
    { "region": "Americas", "count": 12760 },
    { "region": "Asia Pacific", "count": 4821 },
    { "region": "EMEA", "count": 2526 }
  ],
  "reviewsOverTime": [
    { "month": "2014-02", "count": 1 },
    { "month": "2026-06", "count": 73 }
  ]
}

Facet values output (metadata dataset)

{
  "field": "source_type",
  "type": "enum_values",
  "values": [
    "ai_assisted_review", "api_collect", "g2_incentivized", "g2_nonincentivized",
    "g2gives", "influitive", "organic", "pop_up", "referral", "review_referral",
    "review_widget", "stale_reviews_callout", "thank_you_page", "un_survey",
    "unincentivized", "user_profile", "vendor", "vendor_nonincentivized",
    "vendor_self", "vendor_self_nonincentivized", "vendor_self_sendoso"
  ],
  "count": 21
}

Limitations

• Reviewer job titles and avatar URLs are not available.
• industry and role are returned as numeric category codes with a human-readable label for common values only; they are not available as filters.
• country and region are not available as filters because their values are not normalized across languages. Use primaryRegion (Americas / Asia Pacific / EMEA) for consistent geography filtering.
• similarTo returns at most 1,000 reviews per run (a single relevance-ranked fetch; it does not paginate).
• A product's reviewCount reflects G2's total across all reviews; review scraping and analytics return only public, approved reviews, so their counts are typically lower.
• Some reviews have unstructured text (no clear pros/cons/benefits separation).