BrainTrust Query: Are You Measuring Customer Retention Correctly?
Through a special arrangement, presented here for discussion is a summary of a current article from Cultivating Your Customers, the M Squared Group blog.
As Fred Reichheld wrote in The Loyalty Effect, loyal customers tend to be related to loyal employees, lower returns, lower customer service expense and so on. Yet, in measuring retention, as in many things, the "devil is in the details."
Retention is usually defined as the percent of this year's customers who also purchased in the prior year. Traditionally, marketing uses this metric to gauge the impact of all relationship marketing efforts (as well as customer experience) in motivating customers to maintain a relationship over time.
But how do you identify the impact of specific salespeople, customer service agents and marketing programs on building long term customer relationships? How do you identify what contributed to a customer's extended relationship?
Here are some two approaches:
Low tech: A retailer should make sure that it sets up control groups for every marketing program. When the results of those programs are compared to the control group in terms of retention, they will clearly see which programs do the most to help build a relationship with customers that extends over time. To understand the impact of an individual salesperson or customer-service agent, a cross-tab analysis can be conducted to identify the best and the worst performing staff. A retailer may not see the small differences between two similarly performing agents, but will find the best and the worst. Then the retailer can head off the worst and interview the best to bring best practices to the rest of the team. It's not precise, but it provides a lot of value quickly.
More sophisticated: More advanced statistical modeling will permit stores to identify the ideal combination of marketing programs and staff to maximize customer retention and customer long-term profitability (which are not always the same).
The path a retailer chooses to take has to do with the "analytical maturity" of the organization -- will the company accept and act on statistics-driven conclusions or should they focus on easy-to-understand calculations that can be done on a calculator. (Do those things still exist?)
There is no right answer. There is only the answer that will be the most successful in gaining broad-scale acceptance in the company.
Discussion Question: What do you think are the best methods for measuring customer retention at the retail store level? What does knowledge of customer retention gain for an organization?