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Could predictive analytics become tomorrow’s QR code?


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Do you remember the buzz that surrounded the introduction of the QR (quick response) code? We all rushed to put it on everything: We put it on our flyers, our newspaper ads and our business cards. One agent in Seattle even put it on his billboard.

What was he thinking? That people were going to stop their cars, get out their phones and shoot the QR code off the billboard to go to his website?

We did it because we were told it was the coolest and hottest new “have to have” technology. But guess what? When we looked at our Google Analytics, the traffic generated by QR codes were in the single digits.

Single digits!

It didn’t matter that we put it on tens of thousands of postcards, thousands of flyers and hundreds of business cards. The QR code craze over promised and under delivered.

Fast-forward to the next big thing

Today, the big “have to have” technology is clearly predictive analytics. By mining big data, we can now figure out the homeowners who are most likely to sell their home even before they contact an agent. It’s just like how Google knows so much about people from their online behavior that it can tell if a woman is pregnant before she even knows she is.

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Today, many companies are jumping on yet another new tech bandwagon somewhat blindly, I would argue. They are starting to change some of their marketing tactics because this next big thing is supposed to be better.

But consider this: Once predictive analytics helps these brokerages figure out who the most likely person is to sell their house, doesn’t somebody still have to make the phone call? And when an agent makes that call, how does that conversation go? “Hello, I’m John Doe with XYZ Real Estate. You don’t know me, but by any chance are you thinking about selling your home?”

Can you imagine being the homeowner? “Who are you and how did you get my name? I am on a list? What list?”

It’s not rocket science, which is a problem

One thing that no one is talking about is the impact of the immediate proliferation of predictive analytics services that have appeared seemingly overnight. Initially, only a few companies were talking about it, now there seems to be dozens of firms offering some version of it. Which leads me to believe that data science being used isn’t really all that complicated.

If my suspicions are correct, here is what I worry about: How many companies that are offering predictive analytic services are going to be identifying the same homeowners as those most likely to sell? Because if that is what happens, the user experience would be immediately corrupted, right?

Think about it.

How many phone calls or — worse — knocks on their door would a homeowner have to get asking them if they are thinking about or getting ready to list their home for sale before they come unglued?

If it were rocket science — if it was really, really hard to determine who is most likely to sell a home — that would be great. Predictive analytics would be incredibly expensive and very few companies would be able to make the investment. That would mean fewer calls to homeowners, and it would prevent them from being bombarded. But if everyone gets the same information, well, it kind of reminds you of what has happened with internet-based lead generation, doesn’t it?

A bigger issue looms

Even if the same information is not being replicated, there’s a bigger limitation with predictive analytics: it’s too narrowly focused on what it does. It limits the result it delivers in terms of the total return on investment, it is limiting in the business value for most real estate agents, and it is limited in the scope of its reach in the marketplace.

Predictive analytics is targeted marketing. And while targeted marketing can be very effective, it is just one tool; you can’t sustain a business solely with target marketing. Top-producing agents will tell you that to build long-term business, you have to saturate a market.

Predictive analytics needs to be evaluated not just on what it delivers, but how it fits into an agent’s marketing plan. It can’t be a standalone solution. It would be no more effective in building long-term business than a QR code is in driving people who get a postcard in the mail from you to your website.

Better ways to target

If you really want to leverage the power of predictive analytics and saturate a market as an agent, then you should become very well acquainted with Facebook. One could argue that other than perhaps Google, there is no single entity that is better at mining big data than Facebook.

Real estate agents and brokerages are discovering how much more powerful Facebook is as a marketing tool than just about any other marketing investment. The beauty is that Facebook not only lets you saturate a specific neighborhood for a very low investment, but simultaneously use their predictive behavior and demographics tools to target people who are, for example, “Likely To Move” or “Buying A House” (yes those are actual features on Facebook!)

Also, when you post to Facebook, its algorithm automatically directs your content to people who are likely to be interested in it, which is really just another way Facebook’s predictive technology puts you in front of the right people. In effect, you get the best of both worlds, building both a long-term business by reaching a larger geographic and a broader demographic sphere.

This new approach raises your visibility for those who are in need of immediate help, connecting to those who want to invite you in to do business with them. I would think that’s the better way to leverage predictive analytics.

Lane Hornung is the founder and CEO of both zavvie — a digital power farming platform — and Boulder, Colorado-based real estate company — 8z Real Estate. He’s a respected innovator, entrepreneur and accomplished Realtor and broker-owner. Follow Lane on LinkedIn.

Email Lane Hornung.

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