# G2 Reviews Scraper (`usestring/g2-reviews`) Actor

Collect the 10 most recent G2 reviews per software product - rating, pros, cons, reviewer role and segment.

- **URL**: https://apify.com/usestring/g2-reviews.md
- **Developed by:** [String](https://apify.com/usestring) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## G2 Reviews Scraper — pros, cons and company segment

This Actor scrapes G2 software reviews. Give it a G2 product slug such as `slack` and the G2 Reviews
Scraper returns the **10 most recent reviews** for that product, with the star rating, the review
title, and **pros and cons as two separate fields** rather than one merged review body.

No G2 account, login or cookies are used — this reads what a logged-out visitor sees. Measured at
**10 reviews per product, one G2 request each**.

### What it returns

| Field | Type | Notes |
| --- | --- | --- |
| `reviewId` | string | G2's own review ID — stable across runs, use it to de-duplicate |
| `productSlug` | string | The G2 product slug requested, e.g. `slack` |
| `productName` | string | G2's display name for the product |
| `title` | string | The review headline, with G2's wrapping quotes stripped |
| `rating` | number | Stars out of 5, e.g. `4.5` |
| `pros` | string | The reviewer's answer to "What do you like best?" |
| `cons` | string | The reviewer's answer to "What do you dislike?" |
| `reviewerName` | string | Null where G2 shows the reviewer as "Verified User" |
| `reviewerRole` | string | The reviewer's job title, where they disclosed one |
| `companySegment` | string | `Small-Business`, `Mid-Market` or `Enterprise` |
| `industry` | string | The reviewer's industry, where disclosed |
| `isValidated` | boolean | `true` when the review carries G2's "Validated Reviewer" badge |
| `publishedAt` | string | Review date as `YYYY-MM-DD` |
| `reviewUrl` | string | Permalink to that single G2 review |
| `sourceUrl`, `collectedAt` | string | Provenance for every row |

### Input

```json
{ "products": ["slack", "https://www.g2.com/products/asana/reviews"], "maxItems": 1000 }
```

| Field | Description |
| --- | --- |
| `products` | G2 product slugs (`slack`) or full `g2.com/products/...` URLs. Required, 1–100. |
| `maxItems` | Cap on dataset items. Default 1000. Free plans stop at 250 requests and 250 results — see below. |
| `concurrency` | Products fetched in parallel. Default 3, maximum 5. |

A slug and a full URL for the same G2 product collapse to one fetch, so a mixed list is never billed
twice. A URL on any host other than `g2.com` is rejected and reported as a failed target.

### Use cases

- Competitor and category monitoring — what buyers praise and complain about, by segment
- Pulling verbatim pros and cons into win/loss and battlecard research
- Tracking sentiment on your own product over time by re-running on a schedule
- Segmenting feedback by `companySegment` and `industry` before a positioning change
- Feeding review text into a summariser or topic model with the metadata attached

### Reliability

Reviews are read from G2's own review cards, so `pros`, `cons`, `companySegment`, `industry` and the
Validated Reviewer badge are the page's own values rather than a reconstruction. G2's JSON-LD copy of
the same page merges all three survey answers into one body and omits the segment, the industry and
the badge, which is why the cards are the source.

A product that cannot be read is recorded in the run's `SUMMARY` under `failures` rather than
silently returning fewer rows, and a run where every product failed exits with an error.

There are no retries by design: the String Unblocker owns proxy rotation and anti-bot solver
selection, so a retry loop here would only re-roll the same block.

### Frequently asked questions

**How do I scrape G2 reviews?** Run the G2 Reviews Scraper with a list of G2 product slugs — the last
path segment of the product's G2 URL, for example `slack` from
`https://www.g2.com/products/slack/reviews`. Full G2 product URLs work as input too.

**How many G2 reviews does it return per product?** 10 — the most recent page of reviews, one G2
request per product. Ten products therefore return roughly 100 rows.

**Does it page through every review on a product?** No. The G2 Reviews Scraper collects the first
page of the most-recent ordering only, so it does not return a product's full review history.

**Do I need a G2 account, API key or cookies?** No. Only the public, logged-out review page is read.

**Are pros and cons separate fields?** Yes. `pros` and `cons` carry the two survey answers
separately, so you do not have to split one review body afterwards.

**Why is `reviewerName` empty on some rows?** G2 publishes those reviews under "Verified User"
instead of a name. Where the reviewer disclosed an industry, it is still returned in `industry`.

### Limitations

One page of reviews per product, ordered most recent first — this is not a full review-history
crawler and there is no date filter or rating filter. The third G2 survey answer ("What problems is
the product solving…") is not emitted, and no product-level fields (overall score, pricing, feature
grids, competitor comparisons) are collected. Only `g2.com` URLs are accepted.

### Free plan limit

Runs started from an Apify **free plan** stop at **250 requests and 250 results**, and the run
reports that it reached the limit. Any paid plan runs the full input and `maxItems` you set.

The limit exists because this Actor fetches through our own infrastructure, which Apify does not
cover for free-plan runs. It binds on requests as well as results so that a large input list cannot
spend those fetches for rows the run will not return.

# Actor input Schema

## `products` (type: `array`):

G2 product slugs or full review-page URLs.

## `maxItems` (type: `integer`):

Global cap on dataset items. Runs started from an Apify free plan stop at 250 requests and 250 results; any paid plan runs the full amount.

## `concurrency` (type: `integer`):

Targets fetched in parallel.

## Actor input object example

```json
{
  "products": [
    "slack"
  ],
  "maxItems": 1000,
  "concurrency": 3
}
```

# Actor output Schema

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

Collect the 10 most recent G2 reviews per software product - rating, pros, cons, reviewer role and segment.

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

Item count, failure count and every target that failed, with its error.

# 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 = {
    "products": [
        "slack"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("usestring/g2-reviews").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 = { "products": ["slack"] }

# Run the Actor and wait for it to finish
run = client.actor("usestring/g2-reviews").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 '{
  "products": [
    "slack"
  ]
}' |
apify call usestring/g2-reviews --silent --output-dataset

```

## MCP server setup

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

```

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/Jfu4NRXrDcmYr2QhK/builds/vrYdTECnLj2VRcQPm/openapi.json