A battle royal rages among astute direct marketers. In one camp, the best offers are made to the best customers in an effort to keep their business. Another camp sends the best offers to lower-tier customers, hoping to make them better customers.
Other marketers simply ignore their customers and make their best offers to prospects they hope will come aboard. We’ve seen all three.
There’s little argument that the easiest, most profitable source of new business is represented by the customers who are already on the books. As marketers try to squeeze new business from current customers, they make three expensive mistakes:
· They assume that their best customers, usually the top 10 percent, are their best prospects.
· They assume that their worst customers, the bottom 10 percent producing the lowest revenue, are their worst prospects.
· They assume that 80 percent of their customers, who are neither very good nor very bad, are an undifferentiated crowd with modest growth potential.
· Here’s why that’s wrong.
Though the best customers are easy to spot based on revenue, the biggest spenders often have no more to give. The bottom tier of customers – also easy to spot – may be steady, low-maintenance sources of continuing revenue, or they may be new customers who’ve not yet built a transaction history with the company. Analysis that better defines customers and groups them by their real-world behavior paves the way for better-targeted marketing programs.
The gold mine in every customer set, and its richest new business opportunity, is the 80 percent in the middle of the pack.
This middle majority seems like an undifferentiated crowd. But a close look reveals a raft of differences, and it is the group of customers every company needs to know better. They may be new. They may buy regularly and often. They may place healthy orders but buy from only a few product categories. They may generate similar dollars but buy from quite different categories. Without analysis they’re simply a mystery – and a missed opportunity.
Marketing effectively to the 80 percent in the middle should be the target of every penny invested in CRM and customer loyalty programs. When you can predict which customers are ready to buy in the near future, and what they’re likely to buy, then targeting campaigns and promotions based on predicted behavior will improve your return on marketing investment. “Spray and pray” marketing goes out the window.
When you can predict what new items a customer will buy from your assortment, you can cross-sell and upsell more effectively, regardless of whether you use call centers, e-mail or feet on the street.
You don’t need a crystal ball to predict how customers will behave. It’s understood that the best predictor of future behavior is past behavior. The information you need – records of what customers have done in the past – already exists in your accounting and order-entry files. Here’s how to analyze it:
· Put customers and their transactions into a database.
· Segment customers into groups based on behavior (what they bought, when they bought, how much they bought, etc.).
· Market to each group based on what their established behavior indicates they’re likely to do next.
It’s that simple. And that difficult, especially when the customer set is large and the product selection is wide. But the principles remain the same whether the customer set numbers in the hundreds or hundreds of thousands. As complexity grows, there are more powerful tools that make analysis more granular and targeting more precise.
The math that drives high-level predictive customer analysis goes beyond traditional RFM and regression techniques. It’s not as easy as conducting a satisfaction survey. But it’s predictive and actionable, and marketers are finding it worth the effort. Consider some examples:
· A major software company used this kind of analysis and targeting to achieve a lift in response from its customer-facing direct marketing campaigns.
· A large Midwest wholesaler with more than 250,000 customers has used these techniques to segment customers based on their predicted future behavior. Knowing what and when they are likely to buy has improved sales performance from its call center team.
· A direct marketer finds that only 30 percent of its customers account for 100 percent of sales in a certain category. The DMer realized that marketing dollars can be conserved without sacrificing sales.
Targeting customers who’ll buy specific products in a future quarter offers a powerful advantage. But it doesn’t mean that next quarter’s non-buyers should be ignored. Far from it. Ongoing analysis is essential. It continually produces a new group of ready-to-buy target customers as the quarters roll by.
Creating offers that are appropriate and timely makes each campaign more effective. And the sweet spot of the customer set is the 80 percent who can be cross-sold and upsold by knowing them better.