Posted by marketingfrontier on November 17, 2006
Once you have realized that understanding customer lifecycles is a critical part of targeting customers at the right time in their purchase cycle, the next question becomes how to do so. Often this consideration becomes a daunting one, since the process can become so complex as to be almost impossible.
The key to success here relies on one of my core beliefs — it is better to be “about right” fast, than to delay to achieve perfection. While targeting customers based on their personal lifecycles may be difficult, segment lifecycles can be understood and leveraged in a fraction of the time with a fraction of the work.
Let’s review an example of how this can work, so that you can see the potential.
Let’s say that Janet is Marketing Director of ABC Autoparts, a retailer of automobile, motorcycle, snowmobile and watercraft supplies and parts. Her challenge is how to increase the “share of wallet” within the ABC customer base. Remember — share of wallet is the % of the customer’s total category spending that is spent with your company. Janet has discovered that her customers purchase from ABC for expensive parts and the advice that comes with them, but that the day-to-day purchases (oil, air filters, windshield wipers, etc.) are often made as a convenience purchase, from a big box discounter. Since her customers go into the big box discounter more often than into ABC Autoparts, how can Janet increase her share of those purchases.
Janet first asks, “of my most frequent purchasers of the day-to-day items, how often do they purchase them?” Janet discovers through data mining that her Best Customers purchase oil and air filters every 6 weeks. She also discovers that windshield wiper purchases are more seasonal, with purchases made primarily in the fall before winter, and in the spring, during the rainy season. She may also find regional skews, but let’s not go into that here.
Can you see where we are going here? If Janet knows that Best Customers purchase oil and filters every 6 weeks, she can target promotions at customers who resemble her Best Customers but are not purchasing with that frequency, every 6 weeks. She can also assemble frequency programs to those customers to drive them into the store and thereby increase her share of wallet.
Notice that this promotion is not directed at everyone — just at customers who resemble Best Customers but do not purchase like them. This approach permits Janet to target her spending at customers most likely to increase their spending, maximizing her impact and ROI.
How can this approach be rolled across a broader product base to different segments?