It’s All About the Offer: Marketing on the Left Side of the Brain
Using data, you can focus solidly on the customer -- not the product -- to make more effective offers.
Back in the 20th century, sales and marketing geniuses were American business heroes—they built great sales forces that built great companies, and created great ads that built great brands.
But during the past 25 years, technology changed the rules. Now and forevermore, marketing geniuses will be guided not by intuition but by predictive analytics. In the future, marketing geniuses increasingly will use an understanding of customer behavior to offer the right product, at the right price, at the optimum time. Forrester Research analyst Eric Schmitt calls this data-driven, logic-based approach, left brain marketing.
The good news is that while customer analysis has become an increasingly precise science, the raw data that fuels the analytic engine already has been collected by the enterprise. Otherwise known as highly granular customer knowledge—information such as customer ID, transaction date, transaction amount, product descriptors and other behavioral data—this goldmine is sitting in sales order, billing and accounting files, waiting to be turned into marketing insight.
The dilemma marketers face is how to apply this data: Should they use it to focus their marketing effort on the products they sell or on the customers they serve? This is not as simple a question as it might seem.
Every business carries two kinds of inventory. Its “hard” inventory consists of the products it makes and sells that sits on warehouse shelves. “Soft” inventory consists of the customers it serves. While not sitting somewhere on shelves, this asset is equally tangible—it sit in customer files, accounting ledgers and sales order books.
Marketing a tangible product is relatively easy. Products are quantities that can be defined, measured and compared. Marketing with product focus means deciding which products you want to push. This is especially compelling if inventory is piling up; when a new product is being introduced; or when an old warhorse of an item still has “legs.” But even in obvious cases like these, wall-to-wall product marketing across the entire customer base burns marketing dollars that could be otherwise invested.
The surprise is that soft inventory—the customer and customer behavior—also can be quantified. In fact, measuring loyalty and purchase behavior is the secret to improving customer performance and long-term profit. Quantifying and promoting from a customer perspective can be more difficult analytic work, but inevitably yields a greater return on marketing investment.
Marketing from a customer perspective requires three initial steps:
1. Segmenting customers into groups with shared characteristics.
2. Determining which customers are most likely to buy in the near future.
3. Deciding what offer to make.
While products are built to standards of conformity, in customer-based marketing no two customers are exactly alike. So grouping according to shared characteristics becomes a marketing necessity. They might be grouped by geography (you’ll sell more mittens in Minnesota than in Florida) or by attitudes (Porsche owners and Corvette owners share a passion for sports cars, but little else).
But while demographics and psychographics can be used for targeting, the customer information that matters most is behavioral:
• Who’s going to buy next?
• When will they buy?
• What will they buy?
• What might they add to their market baskets that they’ve never bought before?
A customer perspective asks, first of all, which customers are ready to buy—a segmentation that’s derived from using transaction data to establish past purchase patterns and, using this knowledge, to project the next expected purchase time. Marketing to customers who are ready to buy will always yield better results than a “spray-and-pray” random effort.
The customer analysis that asks who will buy next also can lead to a list of customers who should have bought but didn’t. If follow-up marketing to this list doesn’t generate sales from these laggards, it suggests that you’re looking at a list of potential defectors. It’s generally less expensive to take special measures to retain potential defectors than to prospect for new customers to replace them. Of course, a certain amount of attrition is natural and, in some cases, might even be beneficial. However, being able to predict how customers will behave and then marketing accordingly will yield more sales and greater profit both now and in the future.
Transaction Data Reveals Opportunities
Transaction data generates other knowledge that can help target campaigns. Which items are the customers in buying mode going to buy? Customer data not only will show what items are bought on a regular schedule, but also which items drive the purchase of other items—knowledge astute marketers can use to generate combination, upsell offers at the right time.
Transaction data also uncovers cross-sell opportunities when customer market baskets are compared. There are items in every company’s product portfolio that some customers will purchase even though they’ve not bought them before. It could be an item they’ve never tried. Perhaps it’s something they already buy from a competitor. Whatever the reason, customers’ not-yet-purchased items represent an important business opportunity.
A business can age its customer inventory in much the same way as it ages hard inventory. The result may be a decision to write off some low-yielding customer assets. Or, it could be a decision that every customer on the books has some value and that the key to extracting that value is to deal with each one in a way that’s appropriate to his needs and the profit he generates.
The customer segmentation in this chart illustrates the kind of knowledge that can be gained by analyzing customer transactions. Here, we have used our own scoring methods to assign each customer to a loyalty group, based on his or her purchase behavior. Each point on the chart represents an individual customer, and is located on the chart based on a blend of the current behavior, lifetime behavior and loyalty metrics we’ve developed. You can develop measurements like these for your own business.
On this chart (see bottom of the page), half the customers lie on either side of the vertical or horizontal lines. Tracking the movement of these lines—left to right, up and down—from analysis to analysis can reveal much about the health of a customer population overall.
In effect, this chart (which shows actual data from a real company) ages this firm’s soft inventory. Instead of thinking about which style number to feature in a coming promotion, the marketer’s focus is deciding what actions to take to bring customers whose performance is lagging (upper left quadrant) back from the brink of defection—and what can be done to further solidify the behavior of customers who were “bad” but have recently improved (lower right quadrant). Whether customers whose performance is bad (lower left quadrant) can be improved is an open question, but one that can now be evaluated. The very real difference between product and customer focus is obvious.
Looking at customer behavior reminds us of the story of the man who dropped his house keys on a dark night and instead of looking for them where they’d been lost, insisted on looking for them under a lamppost because “that’s where the light is.” Marketing on the left side of the brain means moving the lamppost to where you lost your keys.
Marketing on the left side of the brain means quantifying customer behavior, gaining granular customer knowledge, and using it to target the right customers with the right offer at the right time. Sophisticated analytic tools are available to perform this challenging task. It’s definitely hard work; but it’s beneficial and it’s the future of marketing in the 21st century.
Mark Klein is founder and chairman/CEO and Arthur Einstein is vice president of marketing at Loyalty Builders, a marketing service company in Portmouth, N.H. Klein can be reached at firstname.lastname@example.org. Einstein can be reached at email@example.com.