by Gladys Kong

The eye-opening new world of alternative investor data

Jun 22, 2018
Big Data Business Intelligence Technology Industry

Business watchers and investors are using new “alternative” data like mobile location visit data to inform their investment decisions.

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Credit: Getty Images

Investors, whether they be day traders at home or managers of large hedge funds, are data hungry. They pore over earnings reports and company filings and jump to read news alerts. If they’re on the super-sophisticated side, they may be using data models. And if they’re on the cutting edge, they may be using new “alternative” data sets to inform their decisions.

The emerging alternative data category turns the traditional approach to investment research on its head, providing those interested in the health of businesses in industries from retail to airlines to auto with deeper and more unique insights than what quarterly earnings reports could ever offer.

It’s no wonder spending on alternative data is poised to grow. Research firm Tabb Group expected the market for alternative data to reach $400 million by 2021, and Daryl Smith, CFA Director of Research at alternative data firm NeuData wrote in February, “We believe that, much like 2017, 2018 will be a period of substantial growth in alternative data adoption among investment managers.”

High-flying data alternatives

The mobile location data and insights my firm provides are just one kind of a staggering array of information types available today. How’s this for alternative? Quandl, a company that compiles and analyzes alternative data sets, has a new corporate aviation intelligence product called FlightSight that monitors corporate aircraft ownership of publicly-traded and private companies and tracks their flights to more than 25,000 destinations.

Why would an investor want to track corporate air travel? Well, as the company explains, “you can monitor specific companies in your portfolio for flights to uncommonly visited destinations (or to expected destinations), staying abreast of evolving corporate developments.” In other words, with this sort of data, an investor can find out if there are multiple Walmart corporate flights between Bentonville and London in a given period, and factor that information into decisions.

Quandl’s Chief Data Officer Abraham Thomas described today’s alternative datasets as “the ‘boots on the ground’ of the digital age.” Insights derived from sources as varied as satellite imagery for predicting oil inventories or insurance records for gauging auto sales, he said, are “merely the technological descendants of methods known and used in the investment community for decades.”

Retail stock insights

Let’s say you’re an investor eyeing retail stocks. In May, Motley Fool writers recommended picking up stock in three retail firms, Dollar General (NYSE:DG), Tanger Factory Outlet Centers (NYSE:SKT), and Home Depot (NYSE:HD). “As a real estate investment trust (REIT) that focuses on outlet malls across the U.S. and in Canada, Tanger Factory Outlet Centers may not be the first name to come to mind as you’re looking for ‘retail’ stocks to buy,” noted Motley Fool. “But Tanger is uniquely positioned to weather retail-industry headwinds even as many traditional brick-and-mortar retailers fail.”

This suggestion might pique the interest of a hedge fund manager interested in diversifying retail investments. From there, she might do some research into the company’s recent quarterly earnings reports. She’d discover that the company’s CEO told those listening in on the Q1 2018 earnings call that Tanger has adjusted its 2018 guidance, noting, “We unfortunately also face the challenge of the first quarter caused by unusually harsh winter weather conditions, which led to higher than anticipated unreimbursed snow removal costs and center closures, which resulted in lower variable rents.”

Of course, keeping abreast of the weather in key Tanger markets would have provided valuable insight for any investor. However, there is alternative data that adds nuance when monitoring the health of a retailer.

For example, UberMedia recently evaluated foot traffic over Memorial Day weekend, a huge sale weekend, at a variety of outlet malls throughout the country, comparing it to average weekend foot traffic. We then looked at this year’s Memorial Day weekend data compared to last year’s and teased out some fascinating insights.

For instance, among the Tanger Outlets we tracked, most did well this year even though they dipped in Memorial Day-over-average foot traffic compared to last year. A few, however actually attracted less foot traffic during the big sale holiday weekend than during weekends on average this year — including locations in Grand Rapids, MI, Glendale, AZ and outlets in Houston, San Marcos, and Terrell, TX. It’s important to note that Houston consumers — and possibly those in relatively nearby San Marcos and Terrell — are still recovering from the hurricane. The results in Grand Rapids and Glendale may have been less anticipated by investors.

What alternative data such as mobile location visit data can do is offer insights about certain retail locations in places that haven’t experienced major weather events or economic downturn, information that investors can access before earnings reports come out.

The new parking lot photo

Today’s novel data indicators, as Abraham Thomas of Quandl suggested, are more advanced digitized versions of what data gatherers have harvested for decades. For example, companies have provided data-obsessed investors with information derived from primitive parking lot photos or satellite photo data for decades, the idea being to use the number of cars in a retailer’s lot over a period of time as a proxy for sales. If there were more cars in a lot last month compared to previous months, that might reflect the fact that the sales revenue increased last month for the retailer, providing valuable insights before earnings data is made public.

Mobile location data is the modern version of the parking lot photo. The number of mobile devices spotted in specific retail locations indicates foot traffic in those stores, which can be used as an indicator of sales, especially as mobile devices become even more ubiquitous. Mobile location data providers feed anonymized foot traffic information into sophisticated data models used by consultancies, investment firms or retailers themselves. Not only does this information provide immense value from an operational and marketing standpoint, it can give investors a leg up they never had before.

At this early stage, we can only guess at the untapped value of alternative data for investors and others with their eye on businesses. I look forward to exploring unique ways mobile location data can be part of this vibrant sector.