Property prices — the obsession of a nation. This topic will come up if you are going to a dinner party so you probably should have a point of view. In this post I’ll discuss my email inbox’s point of view.
I am an engineer and struggle to make up my mind based on intuition or discrete data points so the Sunday paper saying that Brexit didn’t have an impact on the UK property prices or that my friend’s friend bought a property in the area 10 years ago for £200,000 and it is now worth £500,000 therefore prices are going up, just aren’t enough data points for me.
Then there are the property indexes which for my area range from £260K up to £3M as they include the 6 bedroom manor house up the road and the 300 sqf studio flat down the road. Neither of these provide much context for the market I am interested in.
A few months ago I subscribed to property alerts and since then I receive a daily email digest from Zoopla and Rightmove, now amassing to over 500 emails with information on over 1200 properties asking prices. This is a particularly interesting dataset for me for a number of reasons:
- It contains all the results of a multi-postcode search filtered by the specific types of property that I am interested in: 2–3 bedroom properties between £400,000 and £600,000.
- It contains property alerts by two of the largest property websites.
- Given that the average time to sell a property in the UK is quoted at 6 weeks, it should contain at least a few complete snapshots of the entire market.
So I have this interesting dataset sitting in my inbox yet there is no simple way to analyse it and extract insights. I could spend an entire weekend manually transferring data into a spreadsheet but by the time I finished it it would already be obsolete as I would probably have a number of new property alerts in my inbox. This is precisely the reason why we started Red Sift, we believe that individuals and organisations alike are sitting on vast amounts of relevant but inaccessible data and that it is time to change that. But I digress, let’s get back to property prices.
Curious about what my data might reveal, I decided to spend an afternoon building a Sift, I called it the Homebuyer Sift. It not only analyses my historical data but also automatically updates it every time a new property alert is received and creates my own personalised, real-time, property index.
Through the Red Sift platform, the output of the Homebuyer Sift is integrated directly inside of my email client and also available on my personal dashboard on the Red Sift cloud.
A few interesting insights can be drawn from the charts and numbers above:
- Asking prices did actually increase in the first half of the year, confirming the overall media reports.
- Brexit did seem to have an impact on the property market, or at least on the segment of the market that I am interested in, with average asking prices sharply dropping in July and steadily dropping since then.
- The number of new property adverts dropped in June, after the Brexit vote, then bounced back up in July but down again in August, suggesting some effect on supply as well.
The Homebuyer Sift also integrates as a contextual widget on property alert emails so now when I read a new property alert I can compare the price of the new properties with my own personal property index and other stats.
The source code for this Sift is available as open source here so if someone wants to add new providers or customise it with completely different stats, that’s also cool.
As for property prices, if you are on the market for a 2–3 bedrooms property between £400,000 and £600,000 in the Kingston area, my inbox says you should probably wait and see…
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