Tech start-up raises $22m for aggressive Canadian expansion

by Neil Sharma on 14 Aug 2019

A new real estate start-up uses machine learning in lieu of sales agents and so far the results are promising.

Properly, which is Toronto-based but only operates in Calgary for the time being—although it plans to launch in Edmonton in the fall and more cities next year—buys homes from sellers in an expeditious manner, then sells them. Using a varied criteria and AI to determine future factors, it decides a purchase price. Should it later sell the home at a higher price, the original seller is refunded up to 75% of the price. Properly’s margins come from charging sellers a fee, which averages 7%.

Calgary-based Reggie Almerol and his wife sold their house to Properly in April, an experience he described as pleasant. Despite selling at a loss from what they paid in 2014, because of market conditions, they managed to upsize into a single-family home at a cheaper price.

“The experience with Properly was pretty flawless,” said Almerol, a commodity risk specialist with ENMAX. “I got an offer in a couple of days. It was a little less than we were expecting, but we knew the market was in a slump. They sent us a bunch of comparables and they had people we could speak to on the phone whenever we needed. They sold the house for more than they gave us and cut us a cheque for 75% of it. It was about $2,600.”

“In terms of what we had to do to sell the house, we took pictures and they had people come in to inspect the house to make sure it was in the condition we said it was, but we got an offer two days later around what they said it would be and we were pretty happy with it considering what other houses in our area were selling for.”

According to Anshul Ruaprell, Properly’s CEO, homeowners choose when to close—anything between five days and eight weeks. If a home sells for less money than Properly pays the seller, the company takes the hit, but, as in the case of the Almerols, refunds monies owed through its Money Match Guarantee program.

“We built proprietary technology on hundreds of factors, like active listings, comparable homes, historical sales, proximity to local schools, malls hospitals, even the amount of traffic on the street. We use machine learning, based on all those variables, to tell us the expected price the home will sell for,” said Ruaprell.

“Proplerly makes its margin on the fee alone, which is why if home sells for more than Properly paid, the majority of that price is refunded back to the seller. The goal is to provide a transparent and fair process for the home seller.”

Having just raised $22 million in Series A funding, $12m of which is in equity and the remainder in debt facility, the start-up intends to become an aggressive force in Canadian real estate markets.

To Almerol, that sounds like great news.

“I would use them again, and I’ve been recommending them to people looking to downsize, like my in-laws and people we know who bought more expensive houses when they got married,” he said. “Because we have two kids and a dog, I don’t think we’d have gone through a realtor to sell the house. I can’t imagine cleaning up for showings every single time. For us it was perfect. If we’d talked to realtors, I’m pretty sure we wouldn’t have put the house up for sale.”


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