Direct Selling: Define Your Customers
Most multichannel marketers think of customers in straight-forward terms: females, 45 to 60 years old, $75,000-plus household incomes, for example. These broad-sweeping demographic descriptors have a place in customer definitions but aren’t the end-all, be-all in defining who does business with you.
Many of the data points necessary to understand the customer are available in your database. Purchasing data, for example, provides the foundation of analysis in marketing, merchandising and price points. But some of the more meaningful data—the information that allows you to complete the puzzle—is often available through third-party service providers. These data bureaus can offer data appends that, for a fee, allow you a more complete and robust view of who the customer really is.
Let’s look at several techniques you can use to learn more about your customers (and even your noncustomers) and how, put together, they give you the intelligence and insights to tighten your brand, improve your marketing and boost profits.
What Customers Are
The first step in building a comprehensive customer profile is the application of demographic data. There are more than a thousand different demographic variables that can be appended to the typical consumer’s name and address record. These demographics, or descriptive characteristics, can range from age and income to gender and ethnicity to home ownership and consumer credit availability. By compiling data from a variety of outside sources, third-party data bureaus can overlay demographics data onto any consumer data file and provide back either a series of descriptive reports or, better yet, appended data for additional analysis.
The demographics most commonly employed in developing customer profiles are generally age, income and gender. Additionally though, it can be powerful to know more about the customer, like how much she paid for her home and how long she’s lived there; how wealthy she is, beyond just annual income estimates; etc. By applying these data points, you start to paint a picture of the person “materially”—essentially the 45- to 60-year-old, $75,000-plus household income female mentioned earlier. The additional demos also allow for more understanding about the kind of home she lives in, how thin she spreads her income, how settled she is and more. And from a marketing standpoint, demographics can enhance RFM selection as well.