# G2 Negative Review Monitor (`yearly_register/g2-negative-review-monitor`) Actor

Automatically monitor G2 products for new 1–3 star reviews. Track multiple products, avoid duplicate results, and run on a schedule with pay-per-check pricing.

- **URL**: https://apify.com/yearly\_register/g2-negative-review-monitor.md
- **Developed by:** [Automation Tech](https://apify.com/yearly_register) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $7.50 / 1,000 product checks

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?

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 Negative Review Monitor

**Monitor G2 products for newly published 1–3 star reviews.** This lightweight Apify Actor reads public G2 RSS, remembers already-seen review IDs in the Actor Key-Value Store, and writes only new matching reviews to the default Dataset.

It is designed for monitoring, not bulk historical extraction: run it on a schedule to catch the newest negative feedback without duplicate results.

### Input

```json
{
  "products": ["slack", "notion"],
  "ratings": ["1", "2", "3"]
}
```

Each `products` value can be a bare slug (`slack`), a G2 review URL (`https://www.g2.com/products/slack/reviews`), or its RSS URL (`https://www.g2.com/products/slack/reviews.rss`). Non-G2 URLs are rejected and all accepted forms normalize to `slack`.

### Output

Each new matching review contains `product`, `reviewId`, `rating`, `title`, `review`, `reviewer`, `publishedAt`, `firstSeenAt`, and `sourceUrl`.

### How it works

1. Loads `review-state` from the persistent named Key-Value Store `g2-negative-review-monitor-state`.
2. Requests G2's verified public RSS endpoint: `https://www.g2.com/products/<slug>/reviews.rss`.
3. Defensively parses, normalizes, and locally filters reviews to the requested whole-star ratings.
4. Uses the G2 RSS `guid` (or review URL) as the stable ID and emits only unseen reviews.
5. Writes successful product state only after it has been fetched and parsed. State is bounded to the 250 most recent relevant review IDs per product. Invalid products are logged, not billed, and do not pollute state.
6. Charges one `product-check` pay-per-event only for every successfully checked product. If the run charge limit is reached, it stops before checking another product. Configure its price in Apify Console before publishing.

G2 currently serves the same RSS document for tested `rating=1`, `rating=2`, and `rating=3` query variants, rather than separate rating feeds. The Actor therefore uses the live verified feed and filters its normalized rating locally. It makes no browser or proxy requests.

### Example schedules

Run every hour to alert downstream systems, or every day for a lightweight customer-feedback digest. On the **first run**, all currently visible matching 1–3-star reviews are emitted. On later runs, only review IDs that have not been seen in the retained per-product state are emitted; an unchanged second run emits zero records.

### Local development

```bash
npm install
npm test
npm run build
ACTOR_TEST_PAY_PER_EVENT=true npm start
```

For a live, non-persistent parser validation against Slack, Notion, and HubSpot Sales Hub:

```bash
npm run test:smoke
```

### Store copy

**Title:** G2 Negative Review Monitor

**Short description:** Get only newly published 1–3 star G2 reviews for one or more products, with persistent deduplication.

# Actor input Schema

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

Use a slug (slack), a G2 reviews URL, or a G2 RSS URL. All formats normalize to the product slug.

## `ratings` (type: `array`):

Select which negative G2 ratings to monitor.

## `storeTestBootstrap` (type: `boolean`):

Emit one clearly labeled monitor-status record when the exact Store sample input finds no new reviews. This never emits a fabricated review and has no effect for other inputs.

## Actor input object example

```json
{
  "products": [
    "slack",
    "notion"
  ],
  "ratings": [
    "1",
    "2",
    "3"
  ],
  "storeTestBootstrap": true
}
```

# Actor output Schema

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

URL of the default Dataset containing newly seen matching G2 reviews.

# 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",
        "notion"
    ],
    "ratings": [
        "1",
        "2",
        "3"
    ],
    "storeTestBootstrap": true
};

// Run the Actor and wait for it to finish
const run = await client.actor("yearly_register/g2-negative-review-monitor").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",
        "notion",
    ],
    "ratings": [
        "1",
        "2",
        "3",
    ],
    "storeTestBootstrap": True,
}

# Run the Actor and wait for it to finish
run = client.actor("yearly_register/g2-negative-review-monitor").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",
    "notion"
  ],
  "ratings": [
    "1",
    "2",
    "3"
  ],
  "storeTestBootstrap": true
}' |
apify call yearly_register/g2-negative-review-monitor --silent --output-dataset

```

## MCP server setup

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

```

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/BYf2KBvkJzMQETzCO/builds/8Y3lvVvOMeDiQ7uP2/openapi.json