How retail stores use big data to track you

Big Brother Goes Shopping

16 |  Did you know that when you shop, big brother is watching? Major retailers spend a lot of money on a lot of technology to attract your business and persuade you to spend more and more and more of your money. While that may not come as a surprise to you, the extent of how deeply retail technology tracks you may have you raising your eyebrows. In this episode, I share several case studies on how big data is being used to monitor your spending and persuade your buying habits. | Please support my Starbucks habit by dropping something in my virtual tip jar. Thank you.

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About the host:

Over the past decade, Jim Stroud has built an expertise in sourcing and recruiting strategy, public speaking, lead generation, video production, podcasting, online research, competitive intelligence, online community management and training. He has consulted for such companies as Microsoft, Google, MCI, Siemens, Bernard Hodes Group and a host of startup companies. During his tenure with Randstad Sourceright, he alleviated the recruitment headaches of their clients worldwide as their Global Head of Sourcing and Recruiting Strategy.  He now serves ClickIQ as its VP, Product Evangelist.

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PODCAST TRANSCRIPT

Big Brother Goes Shopping

Hi, I’m Jim Stroud and this is my podcast.

Did you know that when you shop, big brother is watching? Major retailers spend a lot of money on a lot of technology to attract your business and persuade you to spend more and more and more of your money. While that may not come as a surprise to you, the extent of how deeply retail technology tracks you may have you raising your eyebrows. I’ll share with you several case studies on how big data is used to monitor your spending and persuade your buying habits, right after this special message.

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When you become a preferred customer, join a loyalty program, use coupons or visit a store; you are generating data that is being tracked and monitored; all in order to enhance your shopping experience. Here are some examples of how all that data is being used, according to Neil Patel, co-founder of Neil Patel Digital.

Okay, 5 case studies…

  1. A California fruit packing company warned Costco about the possibility of listeria contamination in its store fruits (peaches, plums, nectarines). Rather than send out a blanket warning to everyone who shopped at Costco recently, Costco was able to notify the specific customers that purchased those particular items. It first notified them by phone and followed up with a letter. Costco has been collecting reams and reams of user data even before big data was a marketing buzzword. They were able to help the Centers for Disease Control pinpoint the source of a salmonella outbreak back in 2010.
  2. Using data about women’s shopping habits, Target was able to identify that women buying large quantities of unscented lotion, cotton balls, supplements and washcloths might mean that those women are anywhere from a few weeks pregnant, to very close to their due date. In one case, a teen was suddenly getting mailers from Target promoting cribs and bibs — before she had even told her father about the pregnancy. Oops!
  3. The Weather channel monitors the weather’s impact on viewers’ emotions. These predictive weather analytics look at trends based on location, and guide advertisers on how and when to deliver their message to help spur action. One such example was the partnership between Pantene, Walgreens and the Weather Channel. Using data collected by the Weather Channel, Pantene and Walgreens were able to anticipate when humidity in the air would be at its highest, prompting women to seek out a product at their local drugstore to prevent frizz and flyaway hair. This was branded as a “haircast” and lead to a 10% increase in sales of Pantene at Walgreens for the months of July and August, along with a 4% sales lift across the entire hair care category at Walgreens.
  4. Another example involving the Weather Channel is of a local pizza chain getting a 20% response rate through the combination of a location-based text marketing campaign coupled with cold weather and the potential for power outages. If you can’t cook, why not order out?
  5. During the busiest flight seasons, tens of thousands of passengers can become stranded every day. By looking at big data correlating weather conditions and flight cancellations, plus the fact that many travellers would be browsing on mobile devices, Red Roof Inn’s marketing team did a promotional campaign targeting those areas most likely to be hit by flight cancellations due to inclement weather. This ended up generating a 10% increase in business in those areas.

These are all examples of big data in retail being used for good. However, there is a potential for it all being used for an unfair, creepy business advantage. Case in point, Target suffered a bit of embarrassment due to a Minneapolis news report from KARE 11, which found Target’s app changed its prices on certain items depending on if you are inside or outside of the store. Here’s a clip from that report.

I was fascinated by this story, so I read up on it and found a couple of quotes I wanted to share with you. Both are from the KARE 11 news website.

In an emailed statement from Target, the company said “The Target app shows in-store pricing while in store, and online pricing while on the go. If a guest finds any item for a lower price across any of the ways they can shop Target, we’ll price match it.”

And here’s the other one.

 University of Minnesota Carlson School of Management Marketing Professor George John believes there’s a little more going on than that. “That particular experiment reveals so many interesting facts about our retail environment,” said John. “Somebody at Target programmed in an algorithm which says someone who is 50 feet within the store is willing to pay more. The most reasonable explanation is that you just revealed your commitment to buying the product, you’re in the store, or in the parking lot. If you are further away, you haven’t quite committed, so I’m going to give you a juicier deal. That’s why the price went up when you got closer to the store.”

So, all that being said, is Target now evil? Are they using their big data powers to get a creepy unfair business advantage? I doubt it. I think its all a matter of unintended consequences. Someone in a lab was probably experimenting with ways to bring greater value to Target customers and this glitch happened. I’m inclined to believe that because I have yet to hear of a pattern of this type of behavior from Target. I’m also inclined to believe that there will be more unintended consequences from major retailers leveraging big data because big data is not going away; that is the world we live in. Get used to it.

If you love what you heard, hate what you heard or, don’t know what you just heard, I want to know about it. You can reach me at my website – www.JimStroud.com. In addition to finding source material and related information for this podcast episode, you’ll find other goodies that I hope will make you smile. Oh, before I go, please financially support this podcast with a little somethin’-somethin’ in my virtual tip jar. (There’s a link in the podcast description.) Your generosity encourages me to keep this podcast train chugging down the track. Whoot-whoot, whoot-whoot, whoot-whoot…

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