BrainTrust Query: Are You Measuring Customer Retention Correctly?
Commentary by Mark Price, Managing Partner of M Squared Group
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?
Time and time again we see customer retention at retail being measured in terms of total customers (e.g., active, or even within specific spending bands such as “between $500 and $1,000”). These metrics are okay but they miss a big part of the churn and correspondingly, the opportunity to realize growth through loyalty marketing.
One of the best measures of retention for retail–and other industries–is comp customers. This is a measure similar to same store sales (comp store sales) but it is specifically based on same customers. As in, exactly the same customer: Is Joanie Smith spending more this year than last year?
This kind of measure isolates where the opportunities are and which customers are increasing in value and which are declining. It is also a great metric for determining profitability of customer marketing programs and further, for measuring the effectiveness of the organization at managing its key asset: customers.
Customer retention is critical for retailers and also for all consumer products and brands because it often takes up to five new prospective consumers to replace one that is lost forever.
Measuring retention is continuing to gain attention from large and small retailers. Key analytics like customer lifetime value, best customer analysis and cross channel shopping behavior are three approaches commonly deployed by retailers to measure retention and profitability.
However, another dimension that is beginning to pick up momentum is “customer engagement.” As digital applications continue to dominate the customer relationship algorithm retailers must begin to understand how and where their customers are engaging. Browsing the retailer’s website, how much time they are spending on the site, which pages are they gravitating to and what actions they are taking as a result of their engagement with the retailer must be addressed into the retention equation.
It is a fact that the easiest customer to keep is a current or past customer and the number one reason is that you have a track record with them. The question is, how do you extend that track record? Well, it would seem that if you know what you sold this customer you can make some assumptions. You can ask for feedback, you can make offers on companion items; this does require some thinking.
Now if it were me, I would measure customer retention by determining how many dollars this customer spend with me last year vs. the year before. That would give me an indication if I were doing the right things.
I recently had an experience with a local merchant when I needed service on an appliance. After getting my phone number the service person informed me that their records reflected that I had purchased a refrigerator and dishwasher from them but not the range I was calling about. The stated that they only service “What they sell” and that they wouldn’t work on my range. Well, guess what, they have not retained me as a customer and furthermore I will probably make it a point to badmouth this merchant to anyone in ear shot for the next year or two at least.
Now I am sure there is some reason for this attitude (sounds like a kid is running a business his old man built), but most service departments actually pay the bills for many merchants. So sonny scared away a potential future profit, walked away from a current profit on a service call and bought himself a million dollars worth of badmouthing. And we worry about foreign competition!
Measuring retention is a challenge for many retailers simply because they lack a reliable process to track customer behavior. Even those with loyalty cards can suffer from lack of full customer participation and bad data. Trying to objectively quantify the impact of individual salespeople, customer service agents and marketing programs in a relationship within that TOTAL customer experience (often including multiple weekly or monthly interactions) requires more than measures of retention, satisfaction or NPS.
But let’s consider a second challenge to retention measures. What a retailer really needs to be profitable is not just “retention,” but retention of the right customers and a sustained or growing share of wallet from those customers. Retailers often don’t totally lose a customer but rather suffer a gradual defection–which is even more difficult to measure. The customer that once made 90% of their category purchases with them drops to 75% then 40%–almost invisibly. The customer still comes in occasionally for that convenience purchase or that highly discounted sale item, and may appear as “retained” by many measures, but their loyalty has shifted to the competition.
Analytics are great but how about ASKING YOUR SALESPEOPLE? They are the folks who are on the floor, helping customers day after day. They know more about why customers are spending more, or defecting, than analytics could ever tell you.
There must be some method of analytics and the measurements being used are only a piece of the puzzle. Actually speaking to your customers sounds like a plan to me.
A great question has been asked and the answer could fill volumes.
To keep it simple, the biggest challenge for retailers is to identify individual customers and link them to sales. Without this, retailers can compare same store sales for similar time periods to get an idea of sales trends, but can’t understand performance at a customer level.
Some retailers have loyalty programs or customer clubs simply to achieve this first objective.
Once you have established a unique identifying number for the customer, decisions can be made as to further sophistication. Some form of measurement should be used as best practice. Phil Rubin has outlined one good approach, looking at same groups of customers and comparing change in sales over time. If outbound marketing is planned (email and white mail), retailers can of course set up control groups which are not mailed and evaluate performance between the groups to understand the effectiveness of the stimulus.
The biggest lever of data-driven marketing is to “use the data” and the ability to measure results and understand ROI has made the job of many CMOs much easier.