G2 Reviews Scraper

TL;DR — Paste a G2 product URL or slug → get flat review rows (rating, reviewer role, company size, industry, and the like-best / dislike / problems-solved answers). Request-only, no login, no browser. Chrome TLS impersonation over residential US proxy. Charged per review saved. Three modes: Latest, Incremental (only new), Deep History (backfill).

{ "mode": "product_reviews", "productUrls": ["notion"], "maxReviews": 3 }

That's a valid run. Everything else below is detail.

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Modes at a glance

productUrls ─▶ ┌─ 🆕 product_reviews  latest recent snapshot        ≤ 125
                 ├─ 🔁 incremental       only new since last run       ≤ 125
                 └─ 🕳️ deep_history      backfill: rating → company    ≤ 5000
                                          size partitions

mode	Does	Per-product cap
product_reviews	Latest snapshot of recent reviews	125
incremental	Only reviews published since your last run	125
deep_history	Best-effort backfill across rating + company-size partitions	5000

Actual counts depend on what G2 exposes publicly for the product — caps are ceilings, not guarantees.

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⚙️ Params cheat-sheet

Param	Type	Default	Notes
productUrls	string[]	—	required. Full URL or slug (notion, slack, hubspot-crm). Dupes removed.
mode	enum	product_reviews	product_reviews · incremental · deep_history
maxReviews	int	25	1–125 (Latest/Incremental) or 1–5000 (Deep History)
starRatings	string[]	[] (all)	any of "1"–"5". Half-stars round up (4.5 → 5).
monitoringKey	string	—	Incremental state key for direct/API runs. Tasks isolate automatically.
maxRetries	int	6	1–15. Bump only if the source is flaky.
proxyConfiguration	object	residential US	Prefill is the recommended config.

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Copy-paste snippets

🆕 Latest (default):

{ "mode": "product_reviews", "productUrls": ["https://www.g2.com/products/notion/reviews"], "maxReviews": 3 }

🔁 Monitor new — schedule this:

{ "mode": "incremental", "productUrls": ["notion", "slack", "hubspot-crm"], "maxReviews": 125 }

🕳️ Deep backfill, 5-star only:

{ "mode": "deep_history", "productUrls": ["notion"], "maxReviews": 2000, "starRatings": ["5"] }

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📦 Output row

One flat object per review (trimmed):

{
  "reviewId": "8123456",
  "productSlug": "notion",
  "productName": "Notion",
  "title": "The best all-in-one workspace",
  "rating": 5.0,
  "starRatingBucket": 5,
  "reviewerName": "Verified User in Information Technology",
  "reviewerRole": "Project Manager",
  "companySize": "Mid-Market (51-1000 emp.)",
  "industry": "Information Technology",
  "isAnonymous": true,
  "likeBest": "Flexible pages and databases that adapt to any workflow...",
  "dislike": "The mobile app can feel slow with very large workspaces...",
  "problemsSolved": "Centralizes notes, docs and project tracking in one place...",
  "publishedAt": "2026-07-30T14:22:00+00:00",
  "publishedAtRaw": "Wed, 30 Jul 2026 14:22:00 +0000",
  "reviewUrl": "https://www.g2.com/products/notion/reviews/notion-review-8123456",
  "markdownContent": "# Notion Review: The best all-in-one workspace\n\n**Rating:** 5.0/5 ★★★★★ ..."
}

Field map: reviewId/reviewUrl = identity + link · productSlug/productName = which product · rating/starRatingBucket = stars + 1–5 bucket · reviewerName/reviewerRole = who · companySize/industry = segment · isAnonymous = verified-user flag · likeBest/dislike/problemsSolved = the three G2 prompts · publishedAt/publishedAtRaw = ISO + original feed date · markdownContent = whole review as Markdown.

Dataset views: Overview (product, rating, title, reviewer, company size, date) and Full reviews (every field).

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⚠️ Gotchas

• Slug or URL — both work. notion == https://www.g2.com/products/notion/reviews.
• Fewer rows than maxReviews? You only get what G2 publicly exposes. Latest/Incremental hard-cap at 125.
• Incremental state — each monitor keeps an isolated last-seen review ID in a KV store. Apify Tasks isolate on their own; for repeated direct/API runs set monitoringKey to keep states separate.
• Billing — charged per review saved. Unavailable products are logged and skipped, no rows, no charge for them.
• Scheduling — mode: "incremental" + an Apify schedule = each run pushes only reviews new since the last.
• No login/cookies — reads the public review feed with Chrome TLS impersonation over Apify Proxy.

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⭐ Did this cheat-sheet earn its keep? A quick review on the Apify Store helps other teams find it — and tells me which mode to sharpen next.

Tags: g2 · g2 reviews · g2 scraper · review scraper · saas reviews · product reviews · competitor research · voice of customer · review monitoring