Review Aggregator Analyzer

Scrape Google Maps and TripAdvisor reviews with sentiment analysis, date filtering, and webhook alerts. Perfect for reputation monitoring, competitor analysis, and automation integration.

Supported Platforms

Platform	Best For	Review Data
Google Maps	Local businesses, restaurants, hotels, services	Rating, text, date, reviewer info, photos, owner response
TripAdvisor	Hotels, restaurants, attractions	Rating, text, date, reviewer info, helpful votes, owner response

Features

• Multi-Platform: Scrape both Google Maps and TripAdvisor in one run
• Date Filtering: Filter by last 24h, week, month, or custom date range
• Sentiment Analysis: Built-in sentiment scoring (positive/neutral/negative)
• Webhook Alerts: Instant notifications when negative reviews are found
• Incremental Mode: Only scrape new reviews since last run
• n8n Ready: Includes workflow template for automation

---

Quick Start

Example Input

{
    "businesses": [
        {
            "name": "McDonald's Times Square",
            "location": "New York, USA",
            "platforms": ["google", "tripadvisor"],
            "urls": {
                "google": "https://www.google.com/maps/place/McDonald's/@40.7579787,-73.9877438,17z/data=!3m1!4b1!4m6!3m5!1s0x89c25855b8fb3083:0x5765322ba9927c08!8m2!3d40.7579787!4d-73.9855551!16s%2Fg%2F1tdfh_7d",
                "tripadvisor": "https://www.tripadvisor.com/Restaurant_Review-g60763-d479078-Reviews-McDonald_s-New_York_City_New_York.html"
            }
        }
    ],
    "platforms": ["google", "tripadvisor"],
    "dateFilter": "last_month",
    "maxReviewsPerBusiness": 50,
    "enableSentiment": true
}

Minimal Example (Google Maps Only)

{
    "businesses": [
        {
            "name": "My Business",
            "location": "City, Country",
            "platforms": ["google"],
            "urls": {
                "google": "https://www.google.com/maps/place/..."
            }
        }
    ],
    "dateFilter": "last_week"
}

---

How to Find Business URLs

Google Maps URL

Step-by-step:

1. Go to Google Maps
2. Search for the business name (e.g., "McDonald's Times Square")
3. Click on the business listing in the search results
4. Important: Make sure the business info panel is open on the left
5. Copy the URL from your browser's address bar

URL Format:

https://www.google.com/maps/place/Business+Name/@LAT,LNG,ZOOM/data=...

Example:

https://www.google.com/maps/place/McDonald's/@40.7579787,-73.9877438,17z/data=!3m1!4b1!4m6!3m5!1s0x89c25855b8fb3083:0x5765322ba9927c08!8m2!3d40.7579787!4d-73.9855551!16s%2Fg%2F1tdfh_7d

Tips:

• The URL must contain /place/ - this indicates you're on a specific business page
• You can also click "Share" on the business and copy the link
• Short URLs (maps.app.goo.gl) also work

---

TripAdvisor URL

Step-by-step:

1. Go to TripAdvisor
2. Search for the business name and location
3. Click on the specific business listing
4. Copy the URL from your browser's address bar

URL Formats:

# Restaurant
https://www.tripadvisor.com/Restaurant_Review-g{GEO_ID}-d{LOCATION_ID}-Reviews-Name-City.html

# Hotel
https://www.tripadvisor.com/Hotel_Review-g{GEO_ID}-d{LOCATION_ID}-Reviews-Name-City.html

# Attraction
https://www.tripadvisor.com/Attraction_Review-g{GEO_ID}-d{LOCATION_ID}-Reviews-Name-City.html

Example:

https://www.tripadvisor.com/Restaurant_Review-g60763-d479078-Reviews-McDonald_s-New_York_City_New_York.html

URL Components:

• g60763 = Geographic location ID (New York City)
• d479078 = Business/Location ID (this is what we extract)
• The scraper extracts the d{number} part automatically

---

Input Parameters

Business Configuration

Parameter	Type	Required	Description
businesses	Array	Yes	List of businesses with name, location, platforms, and URLs
platforms	Array	No	Platforms to scrape: google, tripadvisor (default: both)

Date Filtering

Parameter	Type	Default	Description
dateFilter	String	last_month	Quick filter options (see table below)
dateFrom	String	-	Start date (YYYY-MM-DD) for custom range
dateTo	String	-	End date (YYYY-MM-DD) for custom range

Date Filter Options:

Value	Time Range	Use Case
last_24h	Past 24 hours	Daily monitoring
last_48h	Past 48 hours	Catch missed reviews
last_week	Past 7 days	Weekly reports
last_month	Past 30 days	Monthly analysis
last_3_months	Past 90 days	Quarterly review
last_year	Past 365 days	Annual analysis
all	All time	Initial data collection
custom	Custom range	Use with dateFrom/dateTo

Scraping Options

Parameter	Type	Default	Description
maxReviewsPerBusiness	Integer	100	Max reviews per business per platform (10-1000)
sortBy	String	newest	Sort order: newest, oldest, highest_rating, lowest_rating
onlyNewReviews	Boolean	false	Incremental mode - only new reviews since last run

Sentiment & Filtering

Parameter	Type	Default	Description
enableSentiment	Boolean	true	Enable sentiment analysis (adds positive/negative/neutral labels to each review)
sentimentFilter	String	all	Filter: all, negative_only, positive_only
minRating	Integer	-	Only reviews with rating >= this value
maxRating	Integer	-	Only reviews with rating <= this value

Note: Sentiment analysis is enabled by default. Each review gets a sentiment score (0-1) and label (positive/neutral/negative). This helps identify reviews that need attention without manual reading.

Webhook Alerts

Parameter	Type	Description
webhookUrl	String	URL to POST when negative review is found
negativeThreshold	Integer	Rating at or below this triggers webhook (default: 2)

Proxy Configuration

Parameter	Type	Default	Description
proxyConfiguration	Object	Residential	Proxy settings for avoiding blocks

⚠️ IMPORTANT: Proxy Requirements

Platform	Proxy Type	Notes
Google Maps	Datacenter or Residential	Works with both, datacenter is cheaper
TripAdvisor	RESIDENTIAL REQUIRED	Will get 403 errors with datacenter proxies

Recommendation: Use RESIDENTIAL proxy group for best results with both platforms. This is set as the default.

If you're only scraping Google Maps, you can switch to datacenter proxies to save costs.

---

Example Output

JSON Output (Single Review)

Each review in the dataset contains the following structure (real data from McDonald's Times Square):

{
    "id": "Ci9DQUlRQUNvZENodHljRjlvT2xaQ09HUXpkakkyY2pWa2NGWTVRbE4zY205SWEzYxAB",
    "business": {
        "name": "McDonald's Times Square",
        "location": "New York, USA",
        "businessId": null,
        "platformBusinessId": null
    },
    "platform": "google",
    "platformUrl": "https://www.google.com/maps/place/McDonald's/@40.7579787,-73.9877438,17z/...",
    "reviewer": {
        "name": "R J",
        "profileUrl": null,
        "reviewCount": null,
        "isLocalGuide": false,
        "avatarUrl": "https://lh3.googleusercontent.com/a/ACg8ocIu40q_Gyd7uJGek25e6IhiIig0POA3I1X2yT_IsYEvS6TmRg=w36-h36-p-rp-mo-ba4-br100"
    },
    "review": {
        "rating": 4,
        "ratingNormalized": 4,
        "text": "Convenient location and great customer service staff.",
        "date": "2025-12-18",
        "dateISO": "2025-12-18T21:41:33.277Z",
        "language": "en",
        "helpfulVotes": 0,
        "photos": []
    },
    "businessResponse": null,
    "sentiment": {
        "score": 0.47,
        "label": "positive",
        "confidence": 0.68,
        "source": "combined",
        "breakdown": {
            "text": 0.43,
            "rating": 0.5
        }
    },
    "metadata": {
        "scrapedAt": "2025-12-18T21:41:33.277Z",
        "isNew": true,
        "runId": "VTnrK3BNnx"
    }
}

Example: Multiple Reviews (Real Data)

[
    {
        "id": "review-001",
        "business": { "name": "McDonald's Times Square", "location": "New York, USA" },
        "platform": "google",
        "reviewer": { "name": "Elvis Jimenez", "isLocalGuide": false },
        "review": {
            "rating": 5,
            "text": "One of the cleanest mc'D in NYC very fast service hot food and hot coffee. Worth the trip",
            "date": "2025-12-18"
        },
        "sentiment": { "score": 0.64, "label": "positive", "confidence": 0.39 }
    },
    {
        "id": "review-002",
        "business": { "name": "McDonald's Times Square", "location": "New York, USA" },
        "platform": "google",
        "reviewer": { "name": "laura Vazquez", "isLocalGuide": false },
        "review": {
            "rating": 1,
            "text": "A very very nasty 🤢 security officer in here makes it a horrible customer experience I will make sure I don't return here…",
            "date": "2025-12-18"
        },
        "sentiment": { "score": -0.7, "label": "negative", "confidence": 0.48 }
    },
    {
        "id": "review-003",
        "business": { "name": "McDonald's Times Square", "location": "New York, USA" },
        "platform": "google",
        "reviewer": { "name": "Angelx Galloza", "isLocalGuide": false },
        "review": {
            "rating": 3,
            "text": "To long for the wait gentleman working with long face and attitude and got the wrong order",
            "date": "2025-12-18"
        },
        "sentiment": { "score": -0.04, "label": "neutral", "confidence": 0.55 }
    }
]

CSV Output Format

When exporting as CSV, the data is flattened:

id	business.name	platform	reviewer.name	review.rating	review.text	review.date	sentiment.label	sentiment.score
review-001	McDonald's Times Square	google	Elvis Jimenez	5	One of the cleanest mc'D in NYC...	2025-12-18	positive	0.64
review-002	McDonald's Times Square	google	laura Vazquez	1	A very very nasty security officer...	2025-12-18	negative	-0.70
review-003	McDonald's Times Square	google	Angelx Galloza	3	To long for the wait gentleman...	2025-12-18	neutral	-0.04

Sentiment Score Interpretation

Score Range	Label	Description
0.0 - 0.35	negative	Bad reviews needing attention
0.35 - 0.65	neutral	Mixed or average reviews
0.65 - 1.0	positive	Good reviews, happy customers

---

API Usage

Start a Run

curl -X POST "https://api.apify.com/v2/acts/malikgen~review-aggregator-analyzer/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "businesses": [{
        "name": "McDonald'\''s Times Square",
        "location": "New York, USA",
        "platforms": ["google", "tripadvisor"],
        "urls": {
            "google": "https://www.google.com/maps/place/McDonald'\''s/@40.7579787,-73.9877438,17z/...",
            "tripadvisor": "https://www.tripadvisor.com/Restaurant_Review-g60763-d479078-Reviews-McDonald_s-New_York_City_New_York.html"
        }
    }],
    "dateFilter": "last_month"
}'

Get Results

# JSON format
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_TOKEN&format=json"

# CSV format
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_TOKEN&format=csv"

---

n8n Integration

This Actor includes a ready-to-use n8n workflow for automated review monitoring.

Quick Setup

1. Import Workflow: Download n8n-workflow-async-polling.json and import into n8n
2. Add Apify Credential: Settings > Credentials > Add "Query Auth" with your API token
3. Configure Actor ID: Update to malikgen~review-aggregator-analyzer
4. Optional: Connect Google Sheets for automatic export

Form Fields

The included n8n form has these fields with example placeholders:

Field	Example
Business Name	McDonald's Times Square
Location	New York, USA
Google Maps URL	https://www.google.com/maps/place/...
TripAdvisor URL	https://www.tripadvisor.com/Restaurant_Review-...
Date Filter	last_month
Max Reviews	50

---

Troubleshooting

No reviews returned?

1. Check URLs: Verify the URLs open correctly in a browser
2. Expand date filter: Try last_month or all to confirm data exists
3. Check platform: TripAdvisor may have fewer recent reviews than Google

TripAdvisor returns 0 reviews?

• ⚠️ USE RESIDENTIAL PROXIES - TripAdvisor blocks datacenter IPs. Make sure you have "RESIDENTIAL" selected in proxy configuration.
• TripAdvisor reviews are less frequent than Google Maps
• Try expanding the date range (e.g., last_month instead of last_week)
• The scraper filters by date AFTER fetching - if all reviews are old, result is 0

Timeout or slow runs?

• Reduce maxReviewsPerBusiness (try 50 instead of 100)
• Run fewer businesses per scrape
• Use date filters to limit data

---

Pricing

This Actor charges per result (per review scraped).

$1 USD = 2,000 reviews at $0.0005 per review

Reviews	Cost
100	$0.05
500	$0.25
1,000	$0.50
5,000	$2.50

Plus Apify platform compute costs (~$0.05-0.15 per run)

---

Support

• Issues: Report via Apify Console or GitHub
• Documentation: Apify Docs

---

Changelog

v0.0.21 (Current)

• Focused on Google Maps and TripAdvisor platforms
• Improved date filtering reliability
• Updated default examples with McDonald's Times Square
• Added comprehensive n8n workflow template

v0.0.20

• Added date filters for periodic runs
• Added sentiment and rating output filters
• Improved TripAdvisor GraphQL scraper