# G2 Reviews Scraper — Pros, Cons, Ratings & Reviewer Context (`apricot_blackberry/g2-reviews-scraper`) Actor

Scrape G2 software reviews for any product: rating, title, pros, cons, problems solved, author, date, company size, verified flag. Gets through DataDome. $0.005 per review, no start fee.

- **URL**: https://apify.com/apricot_blackberry/g2-reviews-scraper.md
- **Developed by:** [Creator Fusion](https://apify.com/apricot_blackberry) (community)
- **Categories:** E-commerce, SEO tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## G2 Reviews Scraper — Pros, Cons, Ratings & Reviewer Context ($5 per 1,000 reviews)

Scrape software reviews from **G2.com** for any product: star rating, title, full review text split into **pros, cons and problems solved**, author, date, company size, verified/incentivized flags and review source. Plus one summary record per product with its overall rating and total review count. Choose which sort order comes first (most recent, most helpful, highest or lowest rated) and filter by minimum stars.

**$0.005 per review, $0.005 per product summary.** Nothing charged for products that cannot be fetched.

### How deep it goes

G2 shows visitors without an account the **first page (10 reviews) of each sort order** and ignores deeper page numbers. This Actor therefore collects the first page of all four orders — most recent, most helpful, highest rated, lowest rated — which yields **up to ~40 distinct reviews per product**, always including the newest and the most-helpful ones. Each review carries `sortOrder` so you know where it came from. For a product's complete review history G2 requires a logged-in account, which this Actor deliberately does not use.

### Why this one

- **It gets through DataDome.** G2 blocks ordinary scrapers hard. This Actor escalates from datacenter IPs to Apify's anti-bot Unblocker and residential IPs automatically, and only bills reviews it delivers.
- **Structured, not scraped layout.** Ratings, dates, authors and bodies come from G2's own schema.org data; pros/cons from the question blocks on the page.
- **Built for analysis**: feed `pros`/`cons` straight into sentiment or topic models; `companySize` and `verified` let you segment.

### Output

```json
{
  "type": "review",
  "product": "slack",
  "productName": "Slack",
  "title": "Organized Channels and Smooth Integrations Keep Our Workflow on Track",
  "rating": 4.5,
  "author": "Amit M.",
  "publishedAt": "2026-09-30",
  "pros": "Honestly, what I love most about Slack is the way channels work...",
  "cons": "The biggest downside for me is how distracting it can be...",
  "problemsSolved": "Slack mostly solves the headache of scattered communication...",
  "companySize": "Mid-Market (51-1000 emp.)",
  "verified": true,
  "source": "Organic",
  "incentivized": false,
  "url": "https://www.g2.com/products/slack/reviews",
  "scrapedAt": "2026-10-06T07:00:00.000Z"
}
```

Product records (`type: "product"`) carry `productName`, `category`, `rating` and `reviewCount`.

### Input

| Field | Default | Notes |
|---|---|---|
| `productUrls` | — | Slugs (`slack`) or review URLs. |
| `maxReviewsPerProduct` | 40 | Up to ~40 distinct reviews are reachable per product (see above). |
| `sortBy` | most_recent | Which order is fetched first; the others follow. |
| `minRating` | 0 | Skip reviews below this. |
| `includeProductSummary` | true | |
| `callbackUrl` | — | POST a JSON summary when the run finishes. |

### Pricing

| Event | Price |
|---|---|
| `review` | $0.005 |
| `product` | $0.005 |

### Integrations

- **API**: `POST https://api.apify.com/v2/acts/apricot_blackberry~g2-reviews-scraper/run-sync-get-dataset-items?token=…`
- **MCP**: `https://mcp.apify.com?tools=apricot_blackberry/g2-reviews-scraper`
- **Webhooks**: `callbackUrl`, or Apify run webhooks for Zapier, Make and n8n.
- **Schedules**: weekly runs with `sortBy: most_recent` to monitor new reviews of your product and competitors.

# Actor input Schema

## `productUrls` (type: `array`):

G2 product slugs or review-page URLs, e.g. slack, hubspot, https://www.g2.com/products/apify/reviews.

## `maxReviewsPerProduct` (type: `integer`):

G2 shows anonymous visitors the first 10 reviews of each sort order (most recent, most helpful, highest and lowest rated), so up to about 40 distinct reviews per product can be collected; set higher only if you also pass extra sort orders in future versions.

## `sortBy` (type: `string`):

Sort order fetched first; the other orders follow until the limit is reached.

## `minRating` (type: `integer`):

Skip reviews below this star rating (0 = all).

## `includeProductSummary` (type: `boolean`):

One record per product with its overall rating and review count.

## `callbackUrl` (type: `string`):

POST a JSON summary here when the run finishes.

## Actor input object example

```json
{
  "productUrls": [
    "https://www.g2.com/products/apify/reviews"
  ],
  "maxReviewsPerProduct": 40,
  "sortBy": "most_recent",
  "minRating": 0,
  "includeProductSummary": true
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset with one JSON record per result.

## `summary` (type: `string`):

Counts, failures and notes.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "productUrls": [
        "https://www.g2.com/products/apify/reviews"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("apricot_blackberry/g2-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "productUrls": ["https://www.g2.com/products/apify/reviews"] }

# Run the Actor and wait for it to finish
run = client.actor("apricot_blackberry/g2-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "productUrls": [
    "https://www.g2.com/products/apify/reviews"
  ]
}' |
apify call apricot_blackberry/g2-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,apricot_blackberry/g2-reviews-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/fw8QHtUnYXVaxPHlZ/builds/Xr9xEC69sv73mxSCc/openapi.json