Originally published January 30, 2013
The majority of the conventional wisdom and guidance for an organization’s relationship with its customers is largely linked to a general recommendation that all customers are of equal value and importance. We are bombarded with aphorisms regarding customer relationships – such as “the customer is always right,” “the customer is king,” or “it’s about the customer, always” – that essentially say that the goal of any business is to consistently and continuously ensure that every single customer is completely satisfied. And to some extent, there is some wisdom in suggesting that customers be treated well, since a business cannot survive without customers.
In reality, though, not every customer is the same, nor is each customer equally valued. A quick web search about the distribution of profitability at banks yielded some (unscientific) results that the Pareto principle (AKA the “80-20 rule”) generally held: 20% of the customer base accounts for 80% of the profit. In one case study, the top 16% of the customer base accounted for 105% of the profit and the bottom 28% of the customer base actually accounted for -22%, or an effective loss.1 One can interpret this factoid to draw two interesting conclusions. First, approximately one-sixth of the customer base accounted for all of the bank’s profit; and second, more than one out of every five customers accounted for a loss to the bank.
This raises a bunch of questions about customer relationships, customer engagement and, ultimately, customer centricity. I plan to introduce some of the concepts this month and continue with a series of columns over the next few months to explore some of these issues and questions in greater detail, with the hope that we can use data, thoughtfulness, analytics, and insight to drive a cohesive customer centricity model. For example, consider these:
Customer Value: What is the value of a customer? Clearly, different types of customers have different kinds of value, and the bank case study shows that different types of customers account for different levels of profitability and, consequently, value. In addition, different customers have different values over both the lifetime of the company as well as the lifetime of the customer. Attempting to quantify the value of a customer is somewhat complex, especially when organizations struggle to even define what a customer is, let alone what a customer’s value would be.All of these factor into a different take on customer centricity that goes beyond the conventional expectation of the always-right customer. Instead, a model for customer centricity considers the value of the customer over the duration of the customer’s relationship, and enables continuous refinement of the level of engagement so as to maximize “profitability” while minimizing costs and risks. And customer value analytics will prove to be a key variable in this refinement, and I look forward to exploring these issues in greater detail over the next set of columns.
Customer categorization: In the bank case study, there is an implicit stratification of customers as “best customers,” “good customers,” and “unprofitable customers.” What are ways to stratify or organize the different types of customers, and how are those levels defined? Sometimes the first step in understanding ways to interact with your customers is to look at how they can be organized in relation to the value drivers for your business.
Differentiation: Presuming that there are discrete categories for customers, how do you classify each customer within those categories? What are the business demographic characteristics that are common among your “best customers”? Examples of business demographics might include number of products purchased, monetary value of subscriptions, or the length of the business relationship.
Classification: As opposed to what I referred to as differentiation, which focused purely on the business value criteria for assigning a customer’s category, one might instead seek to determine the qualitative demographic characteristics that are common among customers within the same category, such as annual income, whether they own their own home, or educational attainment, to name a few. A combination of differentiation and classification helps in developing predictive models about the future of a customer relationship.
Cost of doing business: What is the relative cost of operations associated with customer relationship management? What are the average costs for customer acquisition, retention, as well as ongoing service and maintenance among all customers? Can these costs be estimated or calculated on a customer-by customer basis? And how does this factor into assessing the value of a customer?
Engagement: What is the proper level of engagement and interaction with a customer? And at what point does the level of engagement overwhelm the value of customer retention? I can point to a story involving Southwest Airlines former CEO Herb Kelleher’s response to a perennially complaining customer, whose latest rant had been escalated to the top level of the company. Herb’s reaction was to draw the line between customer satisfaction and retention: He wrote back: “We’ll miss you.”
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