It’s no secret that the housing market fluctuates. To stay in step with local rates and trends, ongoing market research – and sometimes even costly property advice – is required. In other words, before they know it, advertisers can easily spend hours of their precious time setting rental prices for their properties.

What if we told you that we’ve built a benchmarking pricing tool, that can suggest market-appropriate rental rates in mere seconds?

At HousingAnywhere, we want to make your advertising experience the best it can possibly be. That starts with setting an optimum rental rate – at no extra cost to your schedule or bank account – so you don’t misprice your property and miss out on tenants. Our tool has been engineered to minimise your vacancies, and ultimately, sustain your rental income. Time to put it to the RentRadar…

What is the RentRadar?

A pricing prediction tool for HousingAnywhere’s 7 major focus cities, the RentRadar is a machine-learning engine that offers rental price suggestions for properties based on:

• Your property details – the type of property, number of bedrooms and area in ㎡
• Our platform data – for similar listings in that city location

It may sound simple, but the RentRadar is a complex pricing algorithm that was engineered after much number-crunching, data analysis and machine learning. The result? Our team successfully delivered a smart tool for landlords to decide upon a rental price in keeping with local market rates.

How is it calculated?

The RentRadar is trained to deliver rental price predictions for your new listing using data collected from our platform over the past two years. All previous or existing listings fed to the RentRadar generated at least one booking request or an ‘invitation to book’, and are therefore aligned with the fair market price (expenses included). This allowed us to eliminate outliers with unreasonably high or low prices, and maintain the accuracy of the algorithm.

Whilst training the algorithm, we called upon the domain expertise of our Supply Managers, so we could validate the metrics with their city knowledge and refine the overall machine-learning process. Mixing our human expertise with the data ensured the tool is set to evolve, offering relevant pricing predictions to landlords now and in the future.

Cities under the RentRadar

Naturally, city-specific dynamics heavily influence local pricing and as a result, rental rates vary from place to place. For instance, the possibility of registering at the municipality is very important for tenants in the Netherlands, but less so in Milan. With this in mind, the RentRadar calculates suitable pricing for properties in:

• Barcelona
• Madrid
• Rotterdam
• Vienna
• Berlin
• Milan
• Brussels

So, whether you’re renting out in a new area or staying put, the RentRadar can keep up with the dynamic local rates – so you don’t have to.

3 ways you can benefit from the RentRadar

1. Be seen as trustworthy: pricing your property in accordance with other local listings means potential tenants will be more inclined to book with you.

2. Save yourself time: create and publish your listings faster by skipping the market research and entrusting your calculations to the RentRadar.

3. Generate income: avoid overpricing or undervaluing your property and charge optimal rent to boost your occupancy rate.

Ready for the RentRadar? Check it out here.