Join Jill Griffin for an in-depth discussion in this video Misreading data, part of Building Customer Loyalty.
In your marketing space, there's a limited number of best customers. In his eyeopening book, "All Customers Are Not Created Equal," author Garth Hallberg points out some important facts. In most categories of business, one third of the buyers account for two thirds of the volume. This best customer segment generally delivers six to 10 times as much revenue as the low-volume segment. They are critical, not only because of their revenue contribution, but also because of their relatively small number. You need to keep your best customers close, but getting clear on who your best customers are can be tricky. In our previous video, we explored two ways to identify your best customers. Now I want us to look at how a company misread the true value of a customer and how you can avoid making the same mistake. To tell you the story, I need to first explain some lingo. In the marketing industry, there's a term called RFM and it stands for recency, frequency, and monetary value. R stands for recency, how recent they bought. F stands for frequent, how frequent they buy. M stands for monetary value, in other words, on average how much money they spend each time they buy. The rule of thumb is the shorter the recency, the bigger the frequency, and the higher the monetary value of purchases, the better the customer. Now here's the cautionary tale. Consider the case of a home shopping channel which religiously applied the industry's RFM model for scoring customer buying behavior. How recent they bought, how frequent they bought, how much money they spent. A long-time customer had graduated into buying roughly $1,000 a month in merchandise and was now dubbed a top customer per the RFM model. In fact, her stair-step purchasing trend was exactly what the company preached as a best practice. But six months later, the bloom was off the rose. When the customer's revenue data, which was stored in one database, was compared to merchandise returns, which was stored in a different database, a surprising finding was revealed. Her returns were sky high. Digging deeper, the company was shocked to discover that the customer owned a small gift shop and was using the shopping channel's merchandise on a consignment-type basis while carefully complying with the company's 60-day return policy. Sadly, the company's data siloes masked this top customer's true value for too many months. So here's the big ah-ha. You probably have vital customer information and knowledge in your different departments of your business. You need to combine that intelligence to get a true picture of who your best customers are. Think about it. This home shopping channel forgot about returns when they were analyzing their best customers. So when it comes to your business, don't let a key piece of information get by you. Consider all the revenue and all the cost to serve each of your customers.