I recently read an article from Modern Distribution Management that talked about the power of cross-selling to current customers as a way to increase each existing customers’ spend with your organization and drive sales. In the article, I was reminded of a cross-marketing and data mining myth that I first heard in business school but is completely relevant to today’s distributor. It goes something like this:
On Friday afternoons (some versions state Thursday, others Saturday), men who stop to purchase diapers from the convenience store also buy beer. As the story goes, stores that understand this hidden correlation and move the diapers near the beer cases will see increased sales on both items.
Now, it turns out that the beer and diapers equation is actually mostly myth embellished by fact over the years. But, the lesson this myth teaches is more powerful than simply allowing you to sell more beer and diapers (which is good since it’s unlikely that you sell both if you read this blog).
The power of the myth lies in mining your transactional data and making educated suggestions to your customers as a result.
We all know it’s easier–and cheaper–to keep a current customer than to go out and find a new one. As a result, it makes more sense to strategically recommend products to your existing customer base in hopes that they will buy more products from you and less from another supplier than to try to increase sales through new customer acquisition. But which items are most likely to be sold together? Good question. Mining your transactional data for correlations will help you figure it out.
First there are the obvious cross-sells to consider. If a business buys a copier from you, it’s likely that they will need copy paper and toner as well. These would be excellent cross-sells to consider presenting to those who are currently researching for a future purchase or those who have purchased a copier from you in the past.
Here’s another less obvious example: Let’s say you supply clean chef’s uniforms to local restaurants each week. It’s likely those restaurants will also need bar towels and table linens. If you supply bar towels and table linens as well as clean chef’s uniforms, you should promote those items to customers who don’t already purchase that service from you.
Then there are the “beer and diapers” correlations. For example, if a customer regularly buys office supplies from you but you also supply industrial coffee and brewing machines, and you know that offices generally need a coffee supplier (right?), it would make sense to mine your transactional data to see which coffee products your office supply customers are most likely to order from you. Moreover, if your customers think of you as the “office supply vendor” they might inadvertantly ignore the fact that you also provide coffee service unless you call it out for them.
Mining your ecommerce transactional data will likely pull a number of obvious cross-sell correlations, but you might also discover a few “beer and diapers” that could vastly improve your sales. You’ll never know until you start comparing data and seeing what jumps out at you.