Remove Duplicates from Vacation Rental Property Data
✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12
Vacation rental managers list properties on Airbnb, Vrbo, Booking.com, and their own direct booking websites simultaneously. When consolidating data from these platforms, the same property appears multiple times with different titles, descriptions, and pricing. dataclean.to matches these duplicate property listings using addresses, coordinates, and property attributes so your master inventory reflects the actual number of units you manage.
The Problem
Duplicate property records in a vacation rental portfolio cause overbooking risks, inaccurate revenue reporting, and wasted marketing spend on listings that represent the same unit. A beachfront condo listed as 'Ocean View Suite' on Airbnb and 'Seaside 2BR Condo' on Vrbo appears as two separate properties in your portfolio, doubling its weight in revenue forecasts and occupancy calculations. Property managers with hundreds of units across multiple channels cannot manually reconcile these listings. Phocuswire Vacation Rental Industry Coverage
How to Fix It
1
Export listings from all channels
Download property data from Airbnb, Vrbo, Booking.com, and your direct booking system. Include property address, listing title, bedrooms, bathrooms, maximum guests, nightly rate, and listing URL.
2
Combine and upload
Merge all exports into one CSV and upload to dataclean.to. The tool identifies address fields, numeric property attributes, and price columns for matching.
3
Configure property matching
Set full address as the primary match key. Add secondary matching on bedroom count plus bathroom count plus maximum guest capacity to catch listings where addresses are formatted differently across platforms.
4
Review property clusters
Inspect groups of listings that appear to be the same physical property. Compare titles, photos referenced, pricing differences, and availability calendars side by side.
5
Export master property list
Download the deduplicated property catalog. Each physical unit appears once with consolidated data from all channels, ready for portfolio analysis or import into your property management system.
Frequently Asked Questions
How does the tool handle properties at the same address but different units?
Multi-unit buildings have the same street address but different unit numbers. The matching logic includes unit or apartment numbers when present. Two listings at '123 Beach Dr' are kept separate if one is 'Unit A' and the other is 'Unit B'.
Can it match listings that use coordinates instead of street addresses?
Yes. If your data includes latitude and longitude, the tool can match properties within a configurable radius (such as 50 meters) combined with bedroom count to identify the same unit listed with slightly different pin placements on different platforms.
What about seasonal pricing differences between channels?
Pricing differences between channels do not prevent duplicate detection. The tool matches on property attributes and location, not price. The merged record can retain pricing from each channel as separate fields for your rate comparison analysis.
Example: Input → Output
name
address
city
stars
price_per_night
Grand Plaza Hotel
123 Main St
New York
4
$189
grand plaza hotel
123 main st
new york
NY
4 stars
$189/night
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.
{
"@context": "https://schema.org",
"@type": "Hotel",
"name": "Grand Plaza Hotel",
"address": {"@type": "PostalAddress", "streetAddress": "123 Main St", "addressLocality": "New York"},
"starRating": {"@type": "Rating", "ratingValue": "4"}
}
💡 How it works:Hotel schema helps your property appear in Google Hotel Search with star ratings and pricing.
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