Intelligent Product Recommendations: Death to the Dumb!

Product recommendations should be about intelligent shopper merchandising. Instead, what I often see in digital commerce today, are very generic, overly broad product recommendations that seem to have much more in common with the limitations of brick and mortar stores than with the data rich and immediately responsive environment of online digital experiences.

In brick and mortar stores, in-store merchandising is really built to everyone. It is a one-to-all approach that doesn’t specialize or respond to individuals. This makes sense. You can’t have a single retail store move around the aisles and single out promotional messages to each individual person walking through the store. Can you imagine a Walmart moving around with portable product recommendations like some self-configuring maze to each shopper? In a way, the locations of merchandising messages is about all the variability that is available in store. End aisle displays are most valuable in high traffic areas or directly associated with particular product aisles.

Many digital stores today act very similarly to their brick and mortar brethren with their product recommendations. No matter who clicks on a particular item, they all get the same generic list of product recommendations. The same one-to-all approach. Oftentimes this is described as “people who bought this also looked at that”. An interesting approach, certainly better than nothing at all, but eerily similar to the limitations of brick and mortar. This approach to a dynamic, data-rich medium such as digital is under delivering on the true opportunity of online product recommendations.

The digital experience is full of insightful data compared to the brick and mortar environment.

Online you know what the shopper is interested in based on their behavior. As they click on various products, you can identify individual preferences within the products they view simply by correlating the attributes. You can also know when they last visited along with a whole host of other data (time of day, geo, device, browser, etc.). All of this information is available to create smarter, more informed product recommendations that aren’t generic, 1 to all, and instead are 1 to 1.

What is just as compelling is that your shoppers know that retailers are capable of more intelligent experiences. They have been exposed to better experiences as more mature digital consumers and they see your generic product recommendations as transparent, overly simplistic and immature. As a result, these savvy digital consumers also make judgements on your brand based on your level of sophistication and technical ability. Digital consumers are screaming for a smart shopping discovery experience online and they know you can see what they purchase, as well as view, in your digital store. What they don’t understand is why you aren’t doing anything with that incredibly valuable insight.

Kurt Heinemann

Kurt is Reflektion’s CMO. His resume includes CMO positions at Marketwired and Monetate. He’s also held senior executive positions at Priceline, Time Warner and Walker Digital Companies. Despite living in Yankees territory, Kurt is a die hard Tigers fan.