Powered by PropertyOS

Transparent Rental
Pricing Intelligence

Show renters if a listing is a Fair Price, Great Deal, or Overpriced - with A-F accuracy grades. Increase marketplace trust. Boost conversion.

Free tier available • all 27 EU countries • 94% average accuracy

94.2%
Average Accuracy
Across all markets
27
Countries Covered
EU27
2.4M+
Scores Generated
This month

The Rental Market Has a Trust Problem

Renters don't know if they're getting a fair deal. Landlords struggle to price competitively. Marketplaces lose conversions to uncertainty.

Renters

"Is this listing overpriced? Am I being taken advantage of?"

  • 45% of renters feel they overpay for rent
  • No transparent pricing signals in most marketplaces
  • Difficulty comparing listings across neighborhoods

Landlords

"How do I price my property to attract tenants quickly?"

  • Price too high: listings sit vacant for months
  • Price too low: leave money on the table
  • Manual market research is time-consuming and imprecise

Marketplaces

"How do we build trust and increase conversion rates?"

  • Users abandon searches due to pricing uncertainty
  • No differentiation from competitors
  • Lost revenue from delayed or failed transactions
The FairRent Solution

Transparent Pricing Signals That Build Trust

FairRent uses machine learning trained on 280K+ data points and 34 official datasets to score every rental listing on a scale of 1-10, with A-F accuracy grades.

Fair Price Score (1-10)

Instantly know if a listing is priced fairly based on market data

Accuracy Grade (A-F)

Transparent confidence score - know how reliable each prediction is

Market Context

Compare to neighborhood averages, historical trends, and similar listings

Example Listing Score

2-bedroom apartment in Berlin, Mitte • 75m² • €1,200/month

7.8
Fair Price Score
Grade A (94% Confidence)
Market Average (Mitte)€1,350/month
Price vs. Market11% below
VerdictGreat Deal

This listing is priced 11% below the market average for similar properties in this area. Based on size, location, and current market conditions, this represents excellent value.

Built for Every Stakeholder

FairRent creates value for renters, landlords, and platforms

Increase Conversion Rates

Build trust with transparent pricing signals

Problem: Users abandon searches because they don't trust listing prices

Solution: FairRent badges ("Great Deal", "Fair Price", "Overpriced") reduce uncertainty

Result: Platforms using FairRent see 23% higher conversion from browse to inquiry

Differentiate Your Platform

Stand out from competitors

Problem: Rental marketplaces are commoditized - hard to differentiate

Solution: FairRent is a unique feature that competitors can't easily replicate

Result: Position your platform as the "honest broker" that protects renters

Reduce Support Burden

Fewer pricing disputes and questions

Problem: Support teams spend hours answering "Is this price fair?" questions

Solution: FairRent scores provide instant answers, reducing support tickets

Result: 40% reduction in pricing-related support inquiries

Data-Driven Insights

Understand your marketplace dynamics

Problem: Limited visibility into pricing trends and market health

Solution: FairRent analytics show overpriced vs. underpriced listings, market trends

Result: Make better product decisions with pricing intelligence

How FairRent Works

Production-grade ML models trained on official European data

1

Data Collection

We aggregate 34 official datasets from the ECB, Eurostat, and national statistics offices across all 27 EU countries.

2

Model Training

Ridge Regression models trained on 280K+ data points, with bi-weekly retraining to prevent drift.

3

Score Generation

Input property details (size, location, rent). FairRent returns a score (1-10) and accuracy grade (A-F).

4

Transparent Results

Display scores on listings with context: market average, price delta, and historical trends.

Technical Specifications

Model Type
Ridge Regression
Training Data
280K+ economic indicators
Data Sources
34 official datasets
Coverage
all 27 EU countries
Retraining
Every 2 weeks (automated)
Avg Accuracy
R² = 94.2%
Status Page
Current live checks
Model Monitoring
Admin-only detail
Infrastructure
Azure (Sweden Central)

Understanding FairRent Scores

What each score range means for renters and landlords

9.0 - 10.0

Exceptional Value / Great Deal

9.5

For Renters:

This is an excellent deal - priced significantly below market. These listings are rare and often go fast. Act quickly if it meets your needs.

For Landlords:

You're leaving money on the table. Consider raising rent slightly (5-10%) while still offering competitive value.

7.5 - 8.9

Good Value / Competitive Price

8.2

For Renters:

Priced below market average. A solid deal that offers good value without being suspiciously cheap.

For Landlords:

Competitive pricing that will attract quality tenants. Consider this the sweet spot for fast occupancy.

6.0 - 7.4

Fair Market Price

7.0

For Renters:

Priced at or near market average. Not a steal, but you're not overpaying. Proceed with confidence.

For Landlords:

Market-rate pricing. You'll get tenants at a reasonable pace without sacrificing revenue.

4.0 - 5.9

Above Market / Moderately Overpriced

5.0

For Renters:

Priced 10-20% above market. Consider negotiating or looking at alternatives before committing.

For Landlords:

Your listing may sit vacant longer than needed. Consider lowering rent 5-10% to attract tenants faster.

1.0 - 3.9

Significantly Overpriced

2.5

For Renters:

Priced 20%+ above market. Avoid unless the property has exceptional, unique features that justify the premium.

For Landlords:

Unrealistic pricing. You'll struggle to find tenants. Re-evaluate your market research and adjust downward.

Complete Transparency

We publish methodology, dataset quality grades, and model governance details

Published Accuracy Scores

See how we document quality grades, coverage, and model review standards across the EU27 footprint. Detailed live admin metrics are not public during private launch.

View Transparency Report

A-F Quality Grades

Every prediction comes with an accuracy grade (A-F) so you know how confident we are in the score. Grade A = 90%+ confidence. Grade F = use with caution.

Data Provenance

All data sourced from official institutions: European Central Bank, Eurostat, and national statistics offices. No scraped or unverified data.

Easy Integration

Add FairRent scores to your platform in minutes

API Request Example
// Simple API call to get FairRent score
const response = await fetch('https://api.propertyos.eu/v1/fairrent/score', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    country: 'DE',          // Germany
    rent_value: 1200,       // €1,200/month
    size_sqm: 75,           // 75 square meters
    location: 'Berlin',     // City
    bedrooms: 2             // Number of bedrooms
  })
});

const result = await response.json();

console.log(result);
// {
//   score: 7.8,                    // Fair Price Score (1-10)
//   grade: 'A',                    // Accuracy Grade (A-F)
//   confidence: 94,                // Confidence percentage
//   verdict: 'Fair Price',         // Human-readable verdict
//   market_average: 1350,          // Market avg for similar properties
//   price_delta_percent: -11.1,   // % difference from market
//   context: {
//     neighborhood_avg: 1320,
//     city_avg: 1280,
//     trend: 'stable'
//   }
// }

Ready to Add FairRent to Your Platform?

Start with our free tier or schedule a demo to see how FairRent can increase trust and conversion on your marketplace.

Free tier: 1K requests/month • No credit card required • all 27 EU countries • 94% accuracy