OverviewReal estate and venue booking companies lose a lot of time in analyzing unpromising prospects. A lot of people may show interest in buying a house, but only a few ones will effectively buy them. This low-productivity process normally results in a high cost in time and effort for the real estate sellers who are pressed on time to deliver sales.
The increase in performance allows real estate companies to do recommendations better and faster, compounded over time. The number of correct venue recommendations can add up to a very considerable increase in sales and company growth while reducing the time spent doing boring, manual tasks.
ChallengeBy prioritizing the prospects with a higher probability of closing, we save real estate agents time and allow them to focus on the prospects that matter.
By analyzing historical and current data, we assisted Hire Space’s agents to make decisions giving them the most relevant prospects according to custom features.
OpportunityWe use artificial intelligence prediction models to deepen analyze the real estate market. To optimize the likelihood of customers buying real estate, we analyze the main factors behind the customer's behavior, most of the time unknown and impossible to be check without the data science process.
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