G2 Product Reviews: Reviews by Product Slug

G2 Product Reviews Scraper: Reviews by Slug

Pull G2.com product reviews for any SaaS product by slug. One row per review: title, body, rating, reviewer role / company size, posted date, pros, cons, recommendation.

Cloudflare notice: G2 aggressively blocks datacenter IPs. This actor will likely return zero rows unless the run environment provides residential proxies. If the first page of a product returns 403, 429 or 503, that product is skipped with zero rows rather than retried indefinitely.

Example output row

{
  "reviewId": "12345678",
  "product": "slack",
  "title": "Best team communication tool we've used",
  "body": "Overall a solid product for async communication.",
  "rating": 4.5,
  "reviewerRole": "Product Manager",
  "reviewerCompanySize": "51-200 employees",
  "postedAt": "2024-03-15",
  "pros": "Integrations are excellent. Threads keep conversations organized.",
  "cons": "Notifications can be overwhelming without careful configuration.",
  "recommendation": "Highly recommended for remote teams."
}

Reviewer names are not included; e-mail addresses and phone numbers inside review text are replaced with [email removed] / [phone removed].

reviewerRole, reviewerCompanySize, pros, cons and recommendation are filled only when the page shows them. When the page carries JSON-LD reviews (tried first), these fields are null.

How to use

Input

{
  "products": ["slack", "notion", "figma"],
  "maxReviewsPerProduct": 50
}

Field	Type	Default	Description
products	string[]	["slack","notion","figma"]	G2 product slugs: the segment after /products/ in the URL
maxReviewsPerProduct	integer	50	Maximum reviews to collect per product (across up to 5 pages)

The slug is the URL path component: for https://www.g2.com/products/salesforce-crm/reviews the slug is salesforce-crm.

Source endpoint

GET https://www.g2.com/products/{slug}/reviews?page={N}

Pagination is via ?page=N (max 5 pages per product). Reviews are extracted from JSON-LD structured data when available, otherwise from review card HTML elements.

Pricing

Pay per event. Price per 1,000 events:

Event	Base price	Bronze	Silver	Gold
Result	$1.27	$1.14	$1.02	$0.89

Bronze, Silver and Gold are the discounts Apify gives users of its paid plans. The Pricing tab always shows the current prices.

You are charged only for rows actually written to the dataset. A run that is blocked by Cloudflare and emits zero rows costs nothing.

Buyer

• Competitive intelligence teams monitoring what customers say about competitor SaaS products.
• Product managers tracking sentiment and feature requests for their own G2-listed products.
• Sales & marketing teams building social-proof assets from reviews.
• Market researchers aggregating multi-product review corpora for NLP analysis.
• CX analysts tracking reviewer role and company-size distribution over time.

Run it through the API

Python, with the apify-client package:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("v0iddo/g2-product-reviews").call(run_input={"products": ["slack", "notion", "figma"], "maxReviewsPerProduct": 20})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript, with the apify-client package:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('v0iddo/g2-product-reviews').call({"products": ["slack", "notion", "figma"], "maxReviewsPerProduct": 20});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call that waits for the run and returns the rows (for runs that finish within 5 minutes):

curl -X POST "https://api.apify.com/v2/acts/v0iddo~g2-product-reviews/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"products": ["slack", "notion", "figma"], "maxReviewsPerProduct": 20}'

Use it from an agent (MCP)

Claude, Cursor, VS Code and other MCP clients can call this actor as a tool through the Apify MCP server. Add it to the client's MCP configuration:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=v0iddo/g2-product-reviews",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

FAQ

Do I need an account, cookies or an API key?

No. The actor reads public data without logging in. You only need an Apify account to start it.

How many results can one run return?

Set maxReviewsPerProduct to the number you need. Large jobs can also be split into several runs or scheduled.

How am I charged?

Pay per event, at the prices on the Pricing tab for your Apify plan (the Pricing section of this page lists them). The platform usage of the run is included in those prices, and your spending limit for a run is always respected.

Why did my run return no results?

The status message and the log of the run say why: usually nothing matched the input, or the source did not answer for a moment. Check the input against the example above and run it again.

Can I run it on a schedule?

Yes. Save your input as a task and add a schedule in the Apify Console (daily, hourly or with a cron expression). Each run gets its own dataset, so you keep a history.

Which formats can I export?

JSON, CSV, Excel, XML, HTML table and RSS from the Output tab or the API. Integrations send the rows to Google Sheets, Slack, Make, Zapier, n8n or a webhook.

Is collecting this data allowed?

The actor collects data that the source publishes openly, without a login. Public data can still be personal data under laws such as the GDPR, and sources have their own terms: make sure your use of the data follows the rules that apply to you.

What happens when the source changes?

An automated test runs the actor every day on the example input and checks the rows, not only that the run finished. When a check fails, the actor is repaired and rebuilt; the build history on this page shows each update.

Something is missing or wrong. Where do I report it?

Open an issue on the Issues tab of this actor with the run link. Requests for a new field are welcome too.

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Source

Public review pages at https://www.g2.com/products/{slug}/reviews. No authentication required. Reviews are extracted from application/ld+json structured data blocks embedded in the HTML, with a BeautifulSoup card parser as fallback.