G2 Software Reviews Scraper

Scrape software reviews from G2.com — the leading B2B software review platform. Extract structured review data including ratings, pros/cons, reviewer role, and company size.

What you get

Field	Description
product_name	G2 product display name
product_slug	URL slug (e.g. notion, hubspot-marketing-hub)
review_id	Unique G2 review ID
rating	Star rating (1–5)
title	Review headline
text	Full review body
reviewer_name	Reviewer display name
reviewer_role	Job title (B2B-critical field for buyer intent analysis)
company_size	Company size bracket (e.g. 51-100, 201-500)
pros	Pros text (G2 signature structured field)
cons	Cons text (G2 signature structured field)
review_date	ISO 8601 publish date
url	Direct link to review on G2
parse_confidence	Per-record parse quality (0.0–1.0) for drift detection
warnings	Machine-readable warning codes

Use cases

• Competitive intelligence — monitor competitor reviews; track sentiment changes over time
• CRM enrichment — identify leads by role/company size from verified buyer reviews
• Product research — extract structured pros/cons for feature analysis
• Market research — aggregate review sentiment across software categories
• Sales enablement — understand objections (cons) at scale

Proxy requirement

⚠️ Residential proxy required. G2 blocks datacenter IPs with HTTP 403. Configure Apify Residential proxy in the input. Without a proxy, all runs will fail.

This is the same requirement as other review platforms (Trustpilot, Booking.com). The buyer pays proxy costs as part of their Apify actor usage budget.

Input

{
  "productSlugs": ["notion", "hubspot-marketing-hub"],
  "maxReviews": 100,
  "sort": "most_helpful",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Finding the product slug

The slug is the last part of any G2 product URL:

• https://www.g2.com/products/notion/reviews → slug is notion
• https://www.g2.com/products/hubspot-marketing-hub/reviews → slug is hubspot-marketing-hub
• https://www.g2.com/products/salesforce/reviews → slug is salesforce

Sort options

Value	Description
most_helpful	Highest-quality reviews (default, best for analysis)
most_recent	Newest reviews first (best for monitoring)
highest_rated	5-star reviews first
lowest_rated	1-star reviews first (surface pain points)

Output example

{
  "product_name": "Notion",
  "product_slug": "notion",
  "product_url": "https://www.g2.com/products/notion/reviews",
  "review_id": "abc-review-123",
  "rating": 5,
  "title": "Best collaboration tool we have used",
  "text": "We switched from Confluence and never looked back...",
  "reviewer_name": "Sarah M.",
  "reviewer_role": "Product Manager",
  "company_size": "51-100",
  "pros": "Extremely flexible, great templates, excellent for documentation",
  "cons": "Can be slow with large databases, search could be better",
  "review_date": "2024-03-15T10:00:00.000Z",
  "url": "https://www.g2.com/reviews/abc-review-123",
  "parse_confidence": 1.0,
  "warnings": []
}

Parse confidence

Every record includes parse_confidence (0.0–1.0). This is our reliability edge:

• 1.0 — all core fields extracted successfully
• 0.7–0.99 — some optional fields missing (normal)
• < 0.5 — structural issue (G2 schema change) — check warnings

Use parse_confidence < 0.8 as a filter for high-quality data, or to detect if G2 changed their page structure.

Pricing

Pay-per-result (PPE): $2.00 per 1,000 reviews.

G2 shows 20 reviews per page, so a 100-review run = 5 page fetches.

Technical notes

• Parser approach: Extracts __NEXT_DATA__ JSON embedded in G2's Next.js HTML — not fragile CSS class scraping
• Pagination: Uses G2's /_next/data/ JSON API for pages 2+ (no HTML parsing overhead)
• Rate limiting: 3-second delay between pages; automatic retry on transient blocks
• Schema stability: JSON key paths are more stable than CSS class names across G2 UI updates

Limitations

1. Residential proxy required — datacenter IPs are blocked
2. 20 reviews per page — 10,000 reviews = 500 proxy requests
3. Not affiliated with G2 — this actor scrapes public review data from G2.com

Integrations

Built for B2B marketers and product teams mining competitor reviews, ratings, and buyer-persona signals on G2 — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Disclaimer

This actor scrapes publicly available data from G2.com. Use in compliance with G2's Terms of Service and applicable data protection laws.