(Dip Your Toe into Segmentation)
Is your organization sitting on its customer data? Do you have the feeling there are actionable insights hidden in that customer data, if only your company would make the effort to find and use them? Perhaps you haven’t yet invested in a squadron of data engineers and data scientists to practice “Big Data”.You don’t have data lakes, machine learning, augmented analytics, pattern recognition, or any of the other technologies promising accessible, automated business intelligence.
Well, you don’t need Big Data, and the Big Cost that comes with it, to begin leveraging the information buried in your customer data. With relatively modest effort, you can:
Understand your customers in terms of relative profitability, product usage, lifestyle, demographics, interests, how they engage with technology, where they live and how they shop;
Find consumers (not your customers) who are like your customers and are good prospects for building profitable relationships;
Identify consumers who are poor prospects and, thereby, steer your marketing resources clear of mirage-like opportunities that fail to meet ROI objectives.
These key capabilities will empower you to take advantage of customer segmentation strategies that help your business grow efficiently and profitably. Customer segmentation is the practice of grouping consumers together that are similar in specific ways relevant to marketing, such as shopping habits, demographics, interests, media preferences, and geography. The purpose of segmentation is to focus your organization on knowing customers better and catering to their needs more effectively.
A good place to start is by profiling your customer base using consumer segmentation available from companies like Claritas (PRIZM®, ConneXions®) and Acxiom (Personicx®). These companies specialize in compiling shopping data and demographics from multiple sources and modeling consumer behavior. Their pre-developed segmentation schemes can reveal a host of insights about your customers. In addition, since their models have been applied nationally, you can use the segments to find prospects that are like your customers.
How does it happen? If you have customer addresses, then it can be a straightforward process to append consumer segments to your customer data. Customer names are not required, nor do you offer your customer list to the compiler – you retain ownership of that asset. And, by appending segments to a sample of your customer base, you can keep the cost reasonable as you evaluate the results for insights and potential utility.
Addresses are enough to help you understand who your customers are, where they live, how they shop, and, most importantly, where to find more prospects who are like your customers. But does your company also capture sales data by customer, such as: spend amount, date of purchase, and products bought? If so, then you can further segment by customer value, by type of shopper, and by product preferences. This knowledge facilitates the tailoring of offers, channels, value propositions, and messages to resonate with different customer segments and market more effectively to each one.
You may be thinking: “Okay, getting started with profiling is simple, but practicing marketing segmentation seems complex. My business is already crazy enough without segmentation.” One of the beauties of segmentation, is that you can begin simply and build from there. You might start by identifying consumers who don’t buy from your product category to avoid wasting resources on them. From there, you may identify just two or three segments that are key drivers for growth. Eventually, the number of segments will be determined by the composition of your customer base and your company’s ability to develop and deliver segment-specific marketing treatments.
What if you don’t have customer addresses or sales data by customer? Even without such data, there are methods that can help you begin practicing segmentation quickly and affordably. More on this in another post.
In this age of real-time analytics and data engines that make shopping recommendations to consumers, it is easy to overlook the fundamental value of customer segmentation. While we wait for Big Data technologies to reach their promise and trickle down to the rest of us, customer segmentation is something most businesses can start benefiting from today. It’s not an either-or proposition. Segmentation will continue to provide a company with valuable context, understanding, guidance, and actionable information even after Big Data is deployed. Case in point, it is common practice among data-driven organizations for predictive models and recommendation engines to be developed uniquely for each segment or to use segmentation data as inputs (independent variables) into the models.
If your organization is not already practicing segmentation, you should consider it. Getting started can be simple, quick, and low cost. The rewards can be substantial and long-lasting.
