How AI-driven platforms match buyers with their ideal homes

As per the 2021 NAR Home Buyer and Seller Generational Trends report, 43% of all buyers go online to find properties for sale, which is around 20% more than in 2019. This means that people are increasingly exchanging traditional processes for the ability to make important decisions from the comfort of their own homes.

Because of this, property managers are constantly exploring new ways to simplify the purchasing journey for potential buyers and beat the competition. As AI is a growing trend, it is also being applied to real estate platforms, and in this article, we’ll delve into more detail about AI-driven platforms and the features that make them so successful.

The evolution of home buying

Until just recently, the process of buying a home consisted only of in-person visits and negotiations with an agent. The agent was also limited to showing them only the properties they knew of, which meant that they couldn’t always meet every request that the buyer had.

Today, real estate platforms are usually the first point of contact a buyer has with a company. Having AI power such platforms is the latest trend in the PropTech industry, and it can be labelled as a game changer – both in terms of increasing your company’s attractiveness as a partner and as an employer. AI has been proven to increase productivity by 66%, which means that it can serve as a revenue booster as well.

Having mentioned all the benefits of utilising AI in real estate, we can move on to discussing exactly how such a powerful algorithm can be implemented into your PropTech solution.

Features that streamline the purchasing process

In this section, we’ll take a look at some of the most prominent features that have shown the best results in terms of increasing client satisfaction by making the purchasing and decision-making processes easier and more straightforward. None of the features we discuss here are anything new – they’re just elements of a platform that can easily be upgraded with the power of AI.

Tailored recommendations

If you yourself have ever tried to make a purchase on the internet, you already know that the most frustrating part of it is finding the right solution in a sea of hundreds of various options. That problem grows even bigger when we take into account that real estate buyers are tasked with making a decision that will have a long-lasting impact both on their quality of life and their finances.

Implementing an AI algorithm into your PropTech platform that tracks the users’ behaviour allows the platform itself to make suggestions based on the data. For example, it can learn their preferences in terms of price, home size, and desired amenities. The smart algorithm will only become more and more accurate over time and thus grow its ability to personalise recommendations to every single user – something not even the best agents could do.

Smart search and filter system

Excellent search and filter functions are not only easy upgrades to make but also highly noticeable on the users’ part. And, since typing a request into the search bar is usually among the first things a buyer does, the good first impression you leave will only boost the chances of them becoming a customer.

AI can be used to sort search queries based on popularity, location, or any other relevant parameter. Again, this feature will only become more and more refined with each new bit of information that the algorithm learns about the user. Similarly, smart filters can be used to help buyers quickly narrow down their options to properties that closely align with their preferences.

As an additional feature, a platform can also have an alert system that notifies the user when a new property is listed and it fits the criteria they previously searched for.

Natural Language Processing (NLP)

NLP allows the platform to better understand the user, even when their requests are phrased like regular language. An example of this is ChatGPT, which functions more like a chat with a real human than the standard keyword-based tools that preceded AI.

Having an NLP-based bot integrated into a platform means that the interactions any user has with it will be much more intuitive and straightforward. This bot can be trained to fill various roles – from mundane appointment booking to pointing users in the right direction in terms of finding the right home.

A user could, for example, type in that they’re looking for a house with a pool and at least 10m2 of yard space and have the bot instantly filter out results. What sets this feature apart from standard smart filters is that the conversation can continue. The user can browse the suggestions and type in that they’re looking for something at a lower price range, and the bot will remember the previous query and apply all three requirements. This means that the search process is much faster than with previous versions of search systems – not to mention the several in-person appointments such a conversation would traditionally involve.

Tips for improving the AI algorithm

As you can see from the examples of features we mentioned above, a common thread among all of them is that the AI algorithm becomes more and more powerful as it learns about the users. To utilise this function to its fullest, there are certain steps the users can take to feed the algorithm and improve it along the way.

Here are a few tips on how you can encourage users to do that:

  • Ask enough questions in the profile set-up stage. An optimised user profile will give the AI a comprehensive overview of the user even before they begin using the platform.
  • Foster engagement. Give your users the option to interact with recommendations through the ‘like’ and ‘dislike’ buttons.
  • Ask the users to narrow down the location they’re interested in. AI can then cross-reference this with information from users’ profiles to find homes that are the right fit in no time.
  • Let the chatbot ask for feedback. Openly prompt the user to either rate or review a recent interaction they had with your platform’s AI.
  • Open up the comments section. Give your users space to voice their opinions on different listings they’ve been shown and get to know them better.
  • Monitor negative feedback. Although unpleasant, negative reviews of listings, the platform, or the AI itself, can be a valuable source of information.

Key takeaways

As the real estate industry moves away from traditional business models, embracing cutting-edge technologies is the crucial step towards success. Implementing AI algorithms into your PropTech platform is one of the most efficient ways to do so.

In this article, we discussed features such as personalised recommendations, smart search and filter systems, and NLP models as ways to increase user satisfaction with the end goal of converting leads into happy customers.

We also explored ways in which users can help enrich the algorithm through their profiles, engagement, and feedback.

As a long-time player in the PropTech game, Valcon can offer you the right IT support to create or upgrade the right platform for your users. Your ideas and requirements come first with us as we ensure all our solutions are perfectly tailored, customisable, and flexible.

Want to learn more? If you would like to learn more about AI driven platforms, please email [email protected] and we’ll be in touch right away.

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