Big Data & Analytics Heroes

David Speights

Chief Data Scientist, The Retail Equation

Retailers today have an insurmountable amount of data to digest and act on quickly not just to personalize the customer experience, but also to prevent fraud. This week’s IBM Big Data & Analytics Hero, David Speights, chief data scientist at The Retail Equation, shares some insights with us.

How have big data and analytics impacted how you do your job today?

Right now—and we are still growing so this number goes up all the time—we probably get around 100 million line items a day from about 26,000 store locations. Now that alone is not that scary—you could load that into a lot of traditional systems, no problem. The problem is that 100 million line items contain 30 million different new identities that we have never seen before, or maybe some fraction of that we have seen before. So when that data comes in, we have to tie it back to the original identities and then anything new that happened that day that allowed us to link things together, we have to process all of that and build all those new links. That procedure is fairly complex and needs a pretty heavy piece of equipment, and that is what landed us in buying the Pure Data for Analytics product.

How are big data and analytics solving problems for retailers?

So an example might be somebody who buys a TV every Friday. They use that TV for some period of time, they return the TV, and then they just get another one. And keep repeating the process throughout the year. So they buy the TV on one credit card one month and then they get another credit card and use that one the next month. And then maybe the next month, they go to another credit card. At some point, they are going to tip the scales from normal to maybe not so normal behavior. We are going to look up their history and we are going to see, “Oh, this person has purchased and returned a TV 18 times in the last year.” So if we are able to surgically remove these people that are causing all the damage, then it opens up possibilities for the retailer, becoming a win-win for the retailer and for the customer.


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