Brandon Donnelly — Daily insights for city builders. Published since 2013 by Toronto-based real estate developer Brandon Donnelly. — Page 1466

I’m reading a great book right now called Tech and the City . I’m only 31% of the way through it (according to my Kindle app), but already it’s been an interesting read. It’s about the making and rise of New York City as a technology and startup hub – which, is fairly recent phenomenon. There aren’t too many cases where New York plays second or third city, but tech is one of those instances. Silicon Valley dominates.

The book talks about the deliberate efforts that were made, by the Bloomberg administration as well by many others, to diversify New York’s economy away from financial services and towards technology, startups, and entrepreneurship. It gives you all the backstory about the rise of Silicon Alley  in the 90s, its subsequent crash in the dot com era, and all the players involved. And yes the reference to Sex and the City is both on purpose and explicit throughout the book.

But at a time where cities all around the world are trying to replicate the success of Silicon Valley, the takeaways from this book are perhaps universally applicable. It certainly got me wondering if, here in Toronto, we’re doing enough to prepare our city to dominate in the 21st century.

Image: Stephen Wilkes

A few weeks ago I had coffee with a friend of mine who is a partner at a Toronto-based enterprise software company called Polyform Labs . Their products are geared towards the commercial real estate industry and, since I’m a big proponent of introducing more technology into the real estate space, I thought I would share a little bit about them with you all today.

The first of their 4 main products is called Lingo , which is a machine learning tool that helps companies quickly review legal documents and contracts. In the case of commercial real estate firms, the most obvious use case is leases. These documents are often hundreds of pages long and, if you have a big portfolio of properties, I’m sure you can imagine how quickly these pages add up.

What’s neat about Lingo is that you basically upload a lease and then the tool interprets and summarizes all of the clauses for you. It then tells you where you’re potentially exposed and where your risk factors are. And if by chance it gets it wrong, you can correct it and the system will actually get smarter – hence the machine learning part.

I’m not going to go through their entire product line, but I did also want to mention one more called Aura. They call it a “location-aware loyalty engine”. And you may have heard of similar products out there in the marketplace. What it does is use the MAC address on mobile phones (which is a unique, but anonymous, identifier) to track how people and crowds move through spaces.

The most common use case I’ve come across is within shopping malls and retail spaces . It’s used to determine which stores have the most foot traffic, which departments and aisles draw the most people, how long people stay in each store, where they buy, and so on. So even if you didn’t already know about this technology, you may have already been giving up your location data. There are lots of mall landlords using it.

And it’s producing some interesting data. For example, as soon as somebody buys one thing in a mall, their propensity to buy something else grows exponentially. This is what the data tells us and I can certainly relate to it from my own experience. So as a mall landlord and tenant, you are obviously trying to figure out ways to encourage people to make that first purchase. 

The other use case that (obviously) came to my mind was with respect to city planning and urban design. How could we harvest anonymous location data to improve the way we design both our private and public spaces? Imagine if we had this data for subway stations, public parks, public plazas, and so on. I bet we would discover all kinds of ways to improve the experience within our cities. I’d like to see the location data for  Trinity Bellwoods Park  in Toronto on a sunny summer day.

But I digress.

If you’d like learn to more about Polyform Labs and their real estate products, click here . 

Image: WPC

Last week a friend of mine sent me a really fascinating article from The Economist talking about the role of foreign investors in Vancouver’s housing market. If you subscribe to The Economist, you can click here to read the article. If you don’t subscribe, you’ll have to rely solely on what I’m about to say.

In case you weren’t aware, Vancouver is an incredibly expensive city when it comes to real estate. The average price for a single-family detached house is now around C$1 million. By some measures, that makes it the most expensive housing market in North America. Here’s a chart that looks at house prices as they relate to household income:

According to The Economist, the median household income in Vancouver is $68,970. This places them 23rd out of 28 in terms of Canada’s major cities. So how is it that homes are, on average, selling for $1 million? The locals don’t seem to be able to afford them.

Well, it’s a well known fact that Chinese buyers continue to be an integral part of Vancouver’s housing market. In fact, up until this year, Canada offered a fast track option for citizenship applications if you brought at least $800,000 into the country.

So we know that foreign buyers are having an impact. It’s a phenomenon we’re seeing in many other cities around the world, such as London . But to what extent is hard to measure–which has forced analysts to get creative.

To try and figure out what percentage of homes are going to foreign buyers, analysts have been looking at macro data, filing through sales records, and even monitoring utility bills to see which homes might be sitting empty.

What they found is that there’s a fairly significant correlation between economic activity in China, and Vancouver’s housing market. When the Chinese economy does well, so do Vancouver homes. Interesting. Still, that doesn’t quantify impact.

When analysts looked for utility bills that would suggest an empty home, they found that only about 8% of high end downtown condos were likely sitting empty. That’s a relatively small amount. It could be vacancy rate.

But when they looked for “mainland Chinese-sounding names” on sales records, they found that for homes priced $3M and up, almost ¾ of the buyers could be from mainland China. Now that’s a significant number!

I found this all rather fascinating and I thought you all might as well. It yet again reminds me of how much opacity there is in real estate markets. We’re all craving better data. Why else would people be scouring utility bills?