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case study 

Real Estate

How Fountech Solutions Improved Results for an Online Property Sales Portal

sector 

Real Estate

 / 

the client

An established but relative newcomer to the UK property sales sector approached Fountech Solutions in order to get help with increasing the level of traffic and sales for their property advertising websites.

This company was unusual in that it offered three separate conduits; property sales, tenant rentals and holiday lets. Their property sales website allowed vendors to choose a pricing structure – ‘no sale no fee’, plus a percentage of any final sale price, or a one-off ‘up front’ charge for advertising a property, with no further fees incurred.

the problem

Our client already had well-functioning websites, but their fee structure dictated the targeting of different categories of vendors with certain selling packages.

Our client also emphasized that featuring a property, then having it viewed as soon as possible, was the key to a quick sale.

In terms of pricing, the ‘no sale no fee’ option was usually chosen by agents, who often included an accompanied viewings service. But if a private property owner chose the ‘up front’ (cheaper) fee for an advertising listing, no intermediate agent was involved; the seller would have to arrange and conduct viewings themselves. In any case, potential buyers would use a contact form on the website to approach both types of vendors.

Algorithms were needed to display certain properties to certain buyers, not only on property preference, but how likely those buyers were to be able to view a property at the earliest opportunity. This was crucial; consequently, private sellers and buyers alike had to be asked about their typical viewing availability patterns as part of the user account onboarding form. This was so that both parties’ likely viewing times and days could be integrated into the property / buyer matching process.

We Consult. We Imagine. We Disrupt.

the solution

Personalization was the key. In effect, the task was to create a property / buyer ‘dating agency’ format. The Fountech team decided at the outset that the most important features were identifying categories of seller and buyer demographics, and applying similar, but adapted, algorithmic techniques in order to push selling packages or appropriate properties, whenever the visitor filled in a form on a landing page.

For selling agents and commercial landlords, one particular form was provided, whereas private sellers and potential home buyers were asked to fill out discrete specific forms to outline their particular requirements.

The usual parameters were assigned into categories for either an available property, or one created as hypothetically ideal. Algorithms were needed to create a closest available match. Criteria examples were the actual / desired number of bedrooms, a (large or small) garden, parking facilities, proximity to schools, was the building occupied or empty etc… Our team also created a very valuable facility, which allowed buyers to rank these factors into their own order of personal importance. Once again, this sorting facility, together with all the other requirements, would have been impracticable to perform optimally without AI computing.

The client’s ‘rapid viewings’ request was further taken into account by people and properties being assigned into actual or desired localized postcode areas or suburbs of towns. The required or actual distance from public transport hubs or arterial roads was assessed. This allowed the system to predict commuting times to major population centres and / or how easily viewings could be arranged quickly.

People were then rated by their readiness to buy: Had they a property to sell? Did they need a mortgage? Could they move quickly or did they need several weeks’ notice? Did they commute to fixed locations? In this way, the Fountech Solutions team created many parameters for buyers and sellers alike; extra data security for GDPR sensitive data was always, of course, of the utmost importance.

Only AI driven computing could be used to assess all the extremely complex relationship factors between potential buyers and sellers efficiently, so that search results were usefully personalized. Listings were displayed as a combination of the most tempting, combined with the most easily viewable, to each individual potential buyer.

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the outcome

Our client was pleased to report an early uptake in the number of buyers ‘favoriting’ properties and an increased percentage of arranged viewings. As the UK property market differs by location, it is too early to state if overall property sales have increased as a direct result of our work, but our client remains happy that the trends appear to be moving in the right direction.

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features

The vCAIO will conduct a situational assessment to identify the needs of, and opportunities for, the organisation.  They will provide a report outlining a gap analysis and the baseline from where to start defining the AI strategy going forward

Create a vision of where the organisation should be going

Set standards for strategy implementation through establishing the correct management structures and considering ethical issues

Make things happen by operating at the right level, knowing what to outsource and what to achieve in-house for optimum delivery

Build capacity in the organisation by recruiting the right talent and identifying appropriate vendors or consultants to solve key problems

Become the public face of the new technology, both internally and externally

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