Two of the questions we’re often asked here at StreetLight Data are: “What percentage of the population is creating the location records in your sample?" and "Does the location data in your sample fairly represent all income groups, or is it biased?” In this blog post, we’re pulling back the curtain on our internal evaluation process with a deep-dive analysis of our newest data source: Location-Based Services data. We started using this data source chiefly because of its large sample size and representativeness, so in this blog post, I will show you our process for determining these characteristics. (Click here to read more about Location-Based Services data in general.)
Fehr & Peers has published an excellent and detailed project report here. They did all the work involved in the validation. We have merely summarized the results most relevant to StreetLight validation questions below.
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"A Note from StreetLight: We are starting a series of blogs on the theme of "data validation." Since StreetLight measures behaviors that are generally hard to measure, it presents a challenge for validation (what's the baseline?). We are collecting cases where good baseline data is available and publishing our findings. If you have suggestions for future editions of the validation blog please get in touch! We're very glad to have a guest blogger, Dave Chipman from Men's Wearhouse, for our initial post. ~Laura Schewel, CEO of StreetLight
by Dave Chipman: Senior Director of Analytics at Men's Wearhouse
This year is an exciting one for analytics at Men’s Wearhouse. Not only are we expanding the Men’s Wearhouse fleet of stores, we’re also integrating our fleet with the Jos. A Bank brand. To keep our momentum going, we are constantly exploring and evaluating new and exciting technologies. We’ve been curious about new data resources from mobile devices for some time now. We wanted to find a way to get some of the really interesting insights about customer mobility in a way that matched our own high standards for protecting our customers’ privacy (as well as the privacy of people who aren’t yet our customers). When we heard about StreetLight Data’s InSight product, we were intrigued.
But, like many data scientists, we were also skeptical. The key question – can StreetLight’s approach accurately describe the patterns of who visits a location? Most importantly for us, can they accurately describe who visits an apparel store?
In a recent conversation with Max Sheets, VP of Real Estate at Freddy's Frozen Custard & Steakburgers, he explained how his perspective has changed during his more than 30 year career in the retail real estate business. Freddy’s, based in Wichita, KS, is a 12 year old fast-casual restaurant chain that has over 120 stores in more than 20 states and is growing rapidly.