We are so excited at RentSquare this week – as the third version of our calculator’s algorithm is finally released!
I’m sure for many of you; this doesn’t mean much. But for us, it’s the result of months of testing, and analysing, and making changes and testing again. It also means that we’ve been able to respond to 91% of all enquiries so far.
We thought this was a great opportunity to explain to you what our calculator does.
As we’ve highlighted before: We use open data and user generated data to work out what the sweet spot of rent is for specific addresses in the UK.
But that might be quite a broad explanation, so let’s explain further.
Firstly, what is open data?!
You probably came across the concept of big data before. A high volume of information that companies and organisations collect from their activities and their users. The data is then archived into dreadful spreadsheets and often, companies don’t know what to do with this data.
Many started doing beautiful infographics that analysed this information but gave it very little use and didn’t create any new value from it. Then, some companies started finding more creative (and sometimes scary) ways of re-purposing this information and creating new products.
The government has as well collected a lot of information which has been sitting with no use. But many argued that because the information is valuable, and was collected with taxpayers’ money, it should be made available to anyone for use.
When the government, or any other organisation, makes available, through an open licence, a very high volume of information that has been collected and anonymised, they are publishing open data.
Open data has allowed us to look at what existed out there and we started creating new value by crossing different sources.
We began crossing different sources of open data and started crowdsourcing information from users to start calculating the sweet spot of rents.
The sweet spot means that the landlord needs to recover his costs and earn a profit so that they can have a sustainable business. But, it also means that tenants can afford it; otherwise, the landlord loses money for the time that it takes to look for a tenant vs finding a tenant who is prepared to pay the asking price.
We use this data, by crossing information to help find out what the costs of the landlord’s investments and outgoings are. This includes the cost of maintenance, taxes, mortgage costs, and void periods, time of return on investment etc. We then utilise local information to understand what is being charged in a certain area, how desirable is one area, how much people earn, how much their salaries go up, how many people are looking for properties, how long are properties empty, etc..
Voila! That gives us a range of how much a property should be rented out at to be rented quickly. Of course, we then need to see the property to account for the quality, if we are to advertise it.
We have also been testing these prices when we advertise the property at the same time as a traditional letting agent – and we just bit them every time.
After refining this calculation for a while, we have also been testing the results with experts in housing and economics.
Calculator next steps
Our next job with the calculator is to work on the calculation of the 10% that has not yet worked. We also want to keep working on this tool to increase the confidence on the calculations that have already been given to users. Finally, we are working on a better visualisation of the rent price so that you can have a breakdown on what contributes to that price.
Very exciting times!
RentSquare, making rent simple!