37 marketing emails from retailers landed in my inbox today before noon. (For real.) Now, don’t shed a tear for me, I’m fine with it. Retail emails go into their own folder, where they don’t distract me until I’m ready. Plenty of them will never be opened, depending both on the subject line and my schedule. Suffice to say, I’m a fan of retail, often calling myself a “professional” shopper. I like to find exactly the right item, ideally with some efficiency. I like sales. I like to know about new products. So, I appreciate (and reward!) companies who use analytics wisely. I don’t mind targeted emails telling me about things that I might like, especially when they come with discounts. That’s not spam, that’s timely information! But what I DO mind are clearly-broken retail analytics.
Like ads trying to sell me things I already bought. Or obviously automated recommendations that make no sense. Or emails that miss the mark by an embarrassingly wide margin, for example continually promoting stuff for “my kids” (I don’t have any!) just because I’m a female in a certain age bracket. As a data and analytics professional, I often wonder: is the algorithm broken, or are they just not trying? Most people won’t give it that much thought as they click away or unsubscribe.
I understand that it’s hard, but I also know it’s possible to do better. Last month, I learned a lot more about retail analytics. First, I helped our CEO research an article, How and Why Retailers Can Do Big Data in the Cloud. We looked at the many ways that the cloud enables retailers to do more with data, not just for marketing, but also to help manage inventory, understand merchandising, make processes more efficient and reduce infrastructure costs. We wrote the article because Cazena’s Big Data as a Service makes the cloud easy to use. It’s a real boon to retailers with many ideas, but not enough IT staff to execute them. (I’ve got my credit card ready for when they sort it out.)
I also went to the Innovation Enterprise’s Retail Analytics conference in Chicago. They had great speakers from retailers and brands that I like: Stitch Fix, Zappos, MGM Resorts, Sears, GrubHub, Under Armour and many others. I love hearing about the smart ways that those retailers use data analytics to improve my experience — and their bottom line.
For example, online clothing retailer Stitch Fix uses analytics and algorithms throughout its business, but also realizes the importance of a human in the styling process. It uses analytics to show its stylists the best options for my monthly shipment of clothing, looking at what’s in stock, liked by others with my taste and in my stated price range. However, a human stylist ultimately picks the items sent to me, because there’s no substitute for the human eye (and who can reverse-engineer female fashion choices with math?!) I learned more about demand and pricing analytics, and why you might not stock up on your favorite brand of toothpaste at the Bellagio casino in Las Vegas: Premium brand toothpaste in that gift shop is like $17, because you’re analytically-unlikely to go elsewhere. Evil genius!
So retailers, no need to apologize for using big data, analytics and the cloud to understand and target offers to me. Apologize if you don’t!
