# G2 Review & Switching-Signal Monitor (`herazur/g2-review-switching-signal-monitor`) Actor

Monitor G2 reviews for new complaints, pricing issues, support problems, feature gaps, competitor mentions, and customer switching signals. Stateful tracking emits only new reviews and changes.

- **URL**: https://apify.com/herazur/g2-review-switching-signal-monitor.md
- **Developed by:** [Furkan Toluç](https://apify.com/herazur) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 35.7% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.004 / g2 review

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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 Review & Switching-Signal Monitor

Turn G2 reviews into recurring competitor intelligence.

Monitor G2 product reviews and detect new negative reviews, pricing complaints, competitor mentions, feature gaps, reliability issues, and customer switching signals. Persistent state means scheduled runs can return only reviews discovered since the previous successful run.

### What this Actor does

Raw review exports answer “what did reviewers write?” This Actor is designed to answer “what changed?”

- Monitors one or many public G2 product review URLs.
- Establishes a baseline on the first successful run.
- Remembers stable review IDs in a named Key-Value Store that persists across runs.
- Emits only unseen reviews on later runs when **Only new reviews** is enabled.
- Detects commercially useful signals without OpenAI, Anthropic, Gemini, or another paid AI API.
- Stops pagination after 20 consecutive known reviews, keeping scheduled runs small.
- Tracks public aggregate rating and review-count changes when G2 exposes them reliably.
- Writes detailed records to the default Dataset and a run-level summary to `OUTPUT`.

### Common use cases

#### Competitive intelligence

Find public reviews that say customers switched from or are moving to another SaaS product.

#### Product research

Discover missing-feature and reliability complaints in recent competitor reviews.

#### Pricing research

Detect new complaints about price increases, billing, cost, and perceived value.

#### Customer intelligence

Identify public dissatisfaction with competing products without building a separate monitoring service.

#### Reputation monitoring

Detect newly published 1–2 star reviews during scheduled runs.

#### SaaS founder research

Turn repeated public pain points into evidence for product opportunities.

### Input

```json
{
  "products": [
    {
      "name": "Slack",
      "url": "https://www.g2.com/products/slack/reviews"
    },
    {
      "name": "Microsoft Teams",
      "url": "https://www.g2.com/products/microsoft-teams/reviews"
    }
  ],
  "maxReviewsPerProduct": 10,
  "onlyNewReviews": true,
  "detectSignals": true,
  "competitors": ["Microsoft Teams", "Slack", "Discord", "Zoom"],
  "minimumRating": 1,
  "maximumRating": 5,
  "includeReviewText": true,
  "dateCutoff": null,
  "emitReviewsOnBaseline": true,
  "stateStoreName": "g2-review-switching-signal-monitor-state",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["UNBLOCKER"]
  }
}
```

`products` accepts 1–25 public URLs shaped like `https://www.g2.com/products/<slug>/reviews`. The URL, not the optional display name, is the monitoring identity.

`maxReviewsPerProduct` limits recent reviews inspected per product. The API default is 10. Increase it for deeper baselines; scheduled runs usually stop earlier after finding known reviews.

The Store prefilled example intentionally requests one Slack review and disables `onlyNewReviews`. Apify's automated Store QA requires a successful run with a non-empty Dataset within five minutes, while API and scheduled runs retain the stateful `onlyNewReviews: true` default.

`dateCutoff` is optional and uses `YYYY-MM-DD`. Pagination stops after older reviews are reached.

`emitReviewsOnBaseline` controls first-run output. When enabled, current reviews are returned with `baselineRun: true` and `isNew: false`. When disabled, the first run establishes state without emitting review rows.

### Recurring monitoring

1. Run the Actor once to establish a baseline.
2. Confirm `baselineRun: true` in `OUTPUT`.
3. Create an Apify Schedule for the Actor or a saved Task.
4. Keep the same `stateStoreName` so the named Key-Value Store remains available across runs. Use a different name to isolate another monitor.
5. Later runs emit only unseen reviews when `onlyNewReviews` is enabled.

State is committed once, after product processing and Dataset writes finish. If the run is interrupted, it does not advance the stored watermark and silently lose reviews. A failed product does not erase its prior state. State retains up to 50,000 recent IDs per product.

G2 applies advanced traffic protection. The production default uses Apify Unblocker, which is billed separately per successful request. The Actor sends one document request per fetched review page, does not perform a billable warm-up through Unblocker, and never reports blocked or unparseable extraction as success. Remove any country selection unless geo-targeting is required; allowing Unblocker to select the route improves reliability.

Do not purge the named state store or change `stateStoreName` between scheduled runs. A new store name creates a new baseline.

### Review output

```json
{
  "recordType": "REVIEW",
  "reviewId": "987654",
  "productName": "Slack",
  "productSlug": "slack",
  "productUrl": "https://www.g2.com/products/slack/reviews",
  "reviewUrl": "https://www.g2.com/products/slack/reviews/slack-review-987654",
  "title": "Too expensive for our team",
  "text": "We switched from Slack to Microsoft Teams because the price increased.",
  "rating": 2,
  "reviewDate": "2026-08-28",
  "reviewerName": "A. Reviewer",
  "reviewerRole": null,
  "reviewerCompany": null,
  "reviewerCompanySize": "Mid-Market (51-1000 emp.)",
  "likes": null,
  "source": "g2",
  "scrapedAt": "2026-08-29T09:00:00.000Z",
  "isNew": true,
  "baselineRun": false,
  "signals": [
    {
      "type": "PRICING_COMPLAINT",
      "confidence": 0.86,
      "evidence": "We switched from Slack to Microsoft Teams because the price increased."
    },
    {
      "type": "SWITCHING_TO",
      "confidence": 0.96,
      "competitor": "Microsoft Teams",
      "evidence": "We switched from Slack to Microsoft Teams because the price increased."
    }
  ]
}
```

Unavailable public fields are `null`; they are never invented. When G2 does not expose a source ID, the Actor creates a deterministic SHA-256-based ID from the product slug, review URL, date, reviewer name, and title.

### Signals

One review can contain multiple signals:

- `NEGATIVE_REVIEW` — rating of 1 or 2 stars.
- `PRICING_COMPLAINT` — negative pricing, billing, cost, or value phrases.
- `SUPPORT_COMPLAINT` — explicitly negative support/service context.
- `BUG_OR_RELIABILITY_COMPLAINT` — bugs, crashes, downtime, errors, or poor performance.
- `FEATURE_GAP` — missing capabilities and feature requests.
- `SWITCHING_FROM` — phrases such as “switched from X” or “previously used X.”
- `SWITCHING_TO` — phrases such as “moving to X” or “using X instead.”
- `COMPETITOR_MENTION` — case-insensitive, word-safe match of a configured competitor name.

Confidence values are deterministic heuristic scores, not machine-learning probabilities. Evidence is a short excerpt around the matching phrase. Full configured competitor names are matched: configuring `Microsoft Teams` does not make the generic word `teams` a match.

### Run summary

The run's default Key-Value Store record `OUTPUT` includes run status, baseline state, succeeded/failed product counts, fetched/emitted/new review counts, signal totals, competitor mention counts, aggregate changes, pages fetched, timing, and per-product errors. Durable review watermarks are kept separately in the named `stateStoreName` store.

```json
{
  "status": "SUCCEEDED",
  "baselineRun": false,
  "productsProcessed": 2,
  "productsSucceeded": 2,
  "productsFailed": 0,
  "reviewsFetched": 48,
  "reviewsEmitted": 3,
  "newReviews": 3,
  "signalsDetected": 5,
  "negativeReviews": 1,
  "pricingComplaints": 1,
  "supportComplaints": 0,
  "featureGaps": 1,
  "switchingFromSignals": 1,
  "switchingToSignals": 1,
  "competitorMentions": { "Microsoft Teams": 1 },
  "pagesFetched": 2
}
```

If one product fails, the run is `PARTIAL`, successful products are retained, and the Dataset receives a `PRODUCT_ERROR` row with an actionable message. If every product fails, the Actor run fails.

### Cost and performance

With the default Unblocker strategy, the Actor requests public G2 review HTML with Apify's recommended `got-scraping` client. Each attempt is bounded to about 55 seconds and transient 403/429/5xx responses receive up to four independently routed attempts across the plain, localized, and review-fragment surfaces. It sorts newest-first when that surface is available, stops at the requested limit/date cutoff, and never turns a blocked or unparseable response into a successful product result. For custom or non-Unblocker proxies, a resource-restricted Chrome fallback remains available.

Apify Unblocker is enabled in the Store input default because G2 commonly rejects ordinary datacenter and residential sessions. Each successful page request consumes 10 Unblocker units in addition to Actor compute and storage usage. No private proxy credentials are hard-coded and no third-party API keys are required.

The logical commercial usage unit is `review_processed`: it is predictable and avoids charging once for a product check and again for every signal on the same review. The source is ready for a future Apify Pay Per Event configuration, but this repository intentionally does not invent a price or enable billing events without an Actor pricing configuration.

### Privacy and public-data scope

This Actor collects only fields displayed on public G2 review pages and needed for review monitoring. It does not log in or access private profiles. Its default Apify Unblocker route may handle anti-bot/CAPTCHA challenges automatically; use it only when you are authorized to collect the target's public pages. Disable `includeReviewText` when downstream consumers only need metadata and detected signals.

Review text and reviewer display information can be personal data. Use the output only for a lawful purpose, minimize retention, and follow G2’s terms and applicable privacy rules.

### Limitations

- G2 actively restricts automated traffic. Unblocker materially improves access but is not a guarantee and can add tens of seconds per page.
- Website structure and access conditions can change. The Actor fails loudly when a page reports reviews but none can be parsed.
- Public G2 markup does not expose every field on every review; unavailable values remain `null`.
- Keyword/regex signals are explainable but do not understand sarcasm, every linguistic nuance, or languages other than English.
- Switching entities that are not in the configured competitor list are best-effort phrase extractions.
- Aggregate rating/count changes are emitted only when both prior and current public values are available.
- First-run reviews are a baseline, not urgent new events, even if baseline rows are returned.

### Development

```bash
npm install
npm run check
npm start
```

The project uses TypeScript, Crawlee/Playwright, Cheerio, Apify Key-Value Store, and Vitest. Tests cover parser behavior, missing/malformed fields, ratings/dates, signal combinations and false positives, stable IDs, state transitions, and transactional staging.

# Actor input Schema

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

One or more public G2 product review URLs. URLs are used as stable monitoring identifiers; names are optional labels.

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

Maximum number of recent reviews inspected per product during this run. Monitoring stops early after a streak of already-known reviews.

## `onlyNewReviews` (type: `boolean`):

When enabled, reviews seen during a previous successful run are not returned again. The first run establishes a clearly marked baseline.

## `detectSignals` (type: `boolean`):

Detect low ratings, pricing/support/reliability complaints, feature gaps, competitor mentions, and switching intent without an AI API.

## `competitors` (type: `array`):

Competitor product names to match as complete names or word-safe phrases in review content.

## `minimumRating` (type: `number`):

Return reviews at or above this 1–5 star rating.

## `maximumRating` (type: `number`):

Return reviews at or below this 1–5 star rating.

## `includeReviewText` (type: `boolean`):

Include public written review content in Dataset rows. Disable to minimize personal/content data after signal detection.

## `dateCutoff` (type: `string`):

Optional YYYY-MM-DD date. Older reviews are ignored and newest-first pagination stops after reaching it.

## `emitReviewsOnBaseline` (type: `boolean`):

Return current reviews during the first run with isNew=false and baselineRun=true. Disable to establish state without Dataset review rows.

## `stateStoreName` (type: `string`):

Named Key-Value Store used to preserve review IDs and aggregate values across runs. Use a different name to isolate independent monitors.

## `proxyConfiguration` (type: `object`):

Apify Proxy settings. UNBLOCKER is the production default for G2 and is billed by Apify per successful request. Country is intentionally omitted so Unblocker can choose the best route.

## Actor input object example

```json
{
  "products": [
    {
      "name": "Slack",
      "url": "https://www.g2.com/products/slack/reviews"
    }
  ],
  "maxReviewsPerProduct": 1,
  "onlyNewReviews": true,
  "detectSignals": true,
  "competitors": [
    "Microsoft Teams",
    "Discord",
    "Zoom",
    "Google Chat"
  ],
  "minimumRating": 1,
  "maximumRating": 5,
  "includeReviewText": true,
  "emitReviewsOnBaseline": true,
  "stateStoreName": "g2-review-switching-signal-monitor-state",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "UNBLOCKER"
    ]
  }
}
```

# Actor output Schema

## `reviews` (type: `string`):

No description

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

No description

# 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": [
        {
            "name": "Slack",
            "url": "https://www.g2.com/products/slack/reviews"
        }
    ],
    "maxReviewsPerProduct": 1,
    "onlyNewReviews": false,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "UNBLOCKER"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("herazur/g2-review-switching-signal-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": [{
            "name": "Slack",
            "url": "https://www.g2.com/products/slack/reviews",
        }],
    "maxReviewsPerProduct": 1,
    "onlyNewReviews": False,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["UNBLOCKER"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("herazur/g2-review-switching-signal-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": [
    {
      "name": "Slack",
      "url": "https://www.g2.com/products/slack/reviews"
    }
  ],
  "maxReviewsPerProduct": 1,
  "onlyNewReviews": false,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "UNBLOCKER"
    ]
  }
}' |
apify call herazur/g2-review-switching-signal-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,herazur/g2-review-switching-signal-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/dXf4oV7wg1XVTzq9R/builds/gq0hibTyQMapN65nX/openapi.json