G2 Review Gap Analyzer

Find what competitors get wrong — straight from G2 reviews.

G2 Review Gap Analyzer collects low-rated G2 reviews of a competitor product and tags each review with the complaint it maps to (missing feature, pricing, performance, integration, etc.), so you can surface what the market dislikes about competing tools — to sharpen your positioning, roadmap, or pain-first sales copy.

Who uses this

• B2B SaaS founders building against established competitors
• Product managers tracking what the market hates in competitor tools
• Marketers writing competitive positioning and comparison pages
• Sales teams building battle cards

How it works

1. Point it at a competitor's G2 reviews page (/products/<slug>/reviews).
2. It gathers reviews within your chosen rating band (default: low-rated, 1–3 stars).
3. Each review is tagged with an extracted_pain_point keyword when the text matches a common complaint theme, so recurring pain stands out without manual reading.

Input

Field	Type	Description
competitorUrl	string · required	G2 product reviews URL, e.g. https://www.g2.com/products/<slug>/reviews
minRating	integer	Lower rating bound to include (default 1)
maxRating	integer	Upper rating bound to include (default 3 — low-rated reviews)
maxReviews	integer	Max reviews to analyze (default 10, range 1–1000)

Example:

{
  "competitorUrl": "https://www.g2.com/products/notion/reviews",
  "minRating": 1,
  "maxRating": 3,
  "maxReviews": 25
}

Output

The Actor writes one item to its default dataset containing the filtered, tagged reviews (each review keeps its source URL so you can jump back to the original):

{
  "source_url": "https://www.g2.com/products/notion/reviews",
  "filters": { "min_rating": 1, "max_rating": 3 },
  "review_count": 25,
  "reviews": [
    {
      "rating": 2,
      "review_text": "No offline mode; unusable on a plane or train.",
      "extracted_pain_point": "feature",
      "review_date": "2026-01-01",
      "source_url": "https://www.g2.com/products/notion/reviews#review-abc"
    }
  ]
}

extracted_pain_point is the first complaint keyword matched in the review text (e.g. missing, lack, slow, expensive, integration, feature, bug) or null when no keyword matches — a lightweight first-pass signal, not a full NLP taxonomy.

Cost

Charged per Apify usage as shown in the pricing box on this page (pay-per-event — no flat subscription). Collection is delegated to a G2 reviews scraper, so a run's real cost depends on review volume and the scraper's own pricing; confirm the cost box before a large run rather than relying on a fixed per-run estimate.