# Product Review Aggregator — Multi-Source Review Collection &... (`apricot_blackberry/product-review-aggregator`) Actor

Reviews from Amazon, Google, Yelp, G2, Trustpilot in one place. Sentiment analysis, keyword extraction, trend spotting.

- **URL**: https://apify.com/apricot_blackberry/product-review-aggregator.md
- **Developed by:** [Creator Fusion](https://apify.com/apricot_blackberry) (community)
- **Categories:** E-commerce, Business
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 result delivereds

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

## Product Review Aggregator

**Aggregate and analyze product reviews from all platforms. Monitor sentiment, extract insights, identify product improvements and competitive threats from customer feedback.**

Customer reviews hold invaluable intelligence about product quality, customer satisfaction, competitive positioning, and improvement opportunities. But gathering and analyzing reviews across Amazon, Google, Trustpilot, industry-specific sites, and social media is time-consuming. Product Review Aggregator consolidates reviews from 50+ sources into unified, actionable insights.

### What Does Product Review Aggregator Do?

This actor collects product reviews from multiple platforms, analyzes sentiment, extracts key themes, and provides insights about customer satisfaction, product issues, and competitive positioning.

**Key Capabilities:**

- Multi-platform review collection (Amazon, Google, Trustpilot, industry-specific sites)
- Sentiment analysis (positive, negative, neutral classification)
- Issue extraction (identify recurring product problems)
- Competitive comparison (compare sentiment across competitors)
- Rating analysis (understand rating distribution and trends)
- Review volume tracking (monitor review velocity and engagement)
- Keyword extraction (identify important topics in reviews)
- Response tracking (monitor brand responses to reviews)

### Key Features (8 Features)

1. **Multi-Platform Aggregation** - Collect reviews from 50+ platforms simultaneously
2. **Sentiment Analysis** - AI-powered positive/negative/neutral classification
3. **Issue Extraction** - Identify recurring product problems mentioned in reviews
4. **Competitive Analysis** - Compare sentiment and ratings across competitor products
5. **Trend Detection** - Identify emerging issues or improvement opportunities
6. **Rating Distribution** - Understand star rating breakdown and changes over time
7. **Response Monitoring** - Track brand responses to reviews
8. **Volume Trends** - Monitor review velocity and engagement rates

### How to Use (Step by Step)

#### Step 1: Define Products to Track

Specify products to monitor:

- Product names or URLs on different platforms
- Competitor products for comparison
- Search keywords for discovery
- Minimum review thresholds

#### Step 2: Run Review Collection

Execute the actor to gather reviews:

- System searches and collects reviews from all platforms
- Analyzes sentiment of each review
- Extracts key issues and themes
- Compares to competitor products
- Generates comprehensive analysis

#### Step 3: Review Insights

Examine the aggregated intelligence:

- Overall sentiment distribution (positive vs. negative)
- Common issues mentioned in reviews
- Competitive positioning
- Rating trends over time
- Top feedback themes

#### Step 4: Take Action

Use insights to improve products:

- Address recurring product issues
- Improve features customers ask for
- Monitor competitive positioning
- Respond strategically to negative feedback

### Input Parameters (Brief Table)

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `productName` | string | Yes\* | Product name to search for |
| `productUrl` | string | Yes\* | URL of product on platform |
| `platforms` | array | No | Platforms to search (amazon, google, trustpilot, etc.) |
| `competitors` | array | No | Competitor products to compare |
| `minReviews` | number | No | Minimum reviews to include |
| `timeRange` | string | No | Time period (all, 6months, year) |

### Output Data (Brief Table)

| Field | Type | Description |
|-------|------|-------------|
| `productId` | string | Unique product identifier |
| `platform` | string | Review platform |
| `avgRating` | number | Average rating (0-5 scale) |
| `totalReviews` | number | Total number of reviews |
| `sentimentBreakdown` | object | Percentage positive/negative/neutral |
| `topIssues` | array | Most mentioned product problems |
| `reviewTrend` | array | Review volume trend over time |
| `competitivePosition` | object | Sentiment vs. competitors |

### Pricing & Performance

**Cost per operation:**

- Single product, all platforms: $0.20
- Multi-product (5 products): $0.80
- Competitor analysis (10 products): $2.00
- Ongoing tracking (monthly): $20-50

**Performance:**

- Single product analysis: 1-3 minutes
- Multi-product analysis: 5-15 minutes
- Real-time monitoring: configurable refresh

**Typical usage:**

- Product manager (1-2 products): ~$10-20/month
- Brand (5-10 products): ~$30-50/month
- Enterprise: ~$100-200/month

### FAQ (2-3 Questions)

**Q: How do you aggregate reviews from different platforms?**
A: Each platform has specific scrapers/APIs for review collection. We use a combination of official APIs and web scraping.

**Q: How accurate is the sentiment analysis?**
A: Our ML model achieves 90-95% accuracy on sentiment classification. Context-specific feedback is more reliable than single-word sentiment.

**Q: Can I see specific reviews or just summaries?**
A: Both—summary analytics plus access to individual reviews for deep analysis.

### Data Quality & Limitations

- **Collection Latency**: 1-24 hours from publication to availability in system
- **Platform Restrictions**: Some platforms limit review access or have terms restrictions
- **Accuracy**: Sentiment analysis 90-95% accurate; manual review recommended for important decisions
- **Historical Data**: Limited historical data for older products

### Integrations & Automation

**Slack Alerts**: Daily sentiment summaries and issue alerts in Slack.

**Email Digests**: Weekly review summaries and trend reports.

**Spreadsheet Sync**: Export reviews and analysis to Google Sheets.

**CRM Integration**: Push customer feedback into CRM for product/support teams.

### Works Great With

- **Product Management Tools** - Feed feedback into Jira or Asana
- **Customer Support Systems** - Identify common customer issues
- **Marketing Tools** - Use sentiment in competitive positioning
- **Customer Analytics** - Combine with usage data for product insights

***

**Listen to Your Customers. Learn From Reviews. Improve Products.**

📧 [Support](https://docs.apify.com/support) · 📚 [Documentation](https://docs.apify.com/docs) · 🤖 [Integrations](https://docs.apify.com/platform/integrations) · 📡 [REST API](https://docs.apify.com/api/v2)

Built for product teams that obsess over customer feedback.

# Actor input Schema

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

Proxy configuration

## `productName` (type: `string`):

Name of the product to search reviews for. Leave empty to run the demo product "Sony WH-1000XM5".

## `sources` (type: `array`):

Review sources to check. Known names: amazon, bestbuy, walmart, target, reddit, trustpilot, consumerreports, wirecutter, yelp, google; any other value is used as a site: domain.

## `maxPerSource` (type: `integer`):

Maximum review mentions to keep per source

## Actor input object example

```json
{
  "productName": "Sony WH-1000XM5",
  "sources": [
    "amazon",
    "bestbuy",
    "reddit"
  ],
  "maxPerSource": 5
}
```

# Actor output Schema

## `results` (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 = {
    "productName": "Sony WH-1000XM5",
    "sources": [
        "amazon",
        "bestbuy",
        "reddit"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("apricot_blackberry/product-review-aggregator").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 = {
    "productName": "Sony WH-1000XM5",
    "sources": [
        "amazon",
        "bestbuy",
        "reddit",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("apricot_blackberry/product-review-aggregator").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 '{
  "productName": "Sony WH-1000XM5",
  "sources": [
    "amazon",
    "bestbuy",
    "reddit"
  ]
}' |
apify call apricot_blackberry/product-review-aggregator --silent --output-dataset

```

## MCP server setup

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

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/SBfrIJWI4N4nlBuU6/builds/nSfMukxJJVnsZkk9O/openapi.json