Looking for a way to measure customer value?
We talk about customer value but how do we measure it? For those of us with a small number of clients, customer value has a face and voice. We know which customers we love to work with – who appreciate our company and our services. And we know when that sense of value is missing – those clients that are just trying to get a quick job or the cheapest price.
But for these of us with larger customer bases (especially online businesses), it is not so easy to get a real handle on customer value, much less measure it. Often we only have email and purchases as data and little more. Who is more “valuable”? Is it that customer that made a big purchase last week, or the one who consistently purchases small items?
One technique, used for many years in the retail sector to segment customers by value is called RFM where the initials denote:
Recency – how recently did the customer purchase?
Frequency – how often to they purchase?
Monetary – how much do they spend?
The easiest way to use this technique is to assign 3-5 levels per variable and then “score” each customer. The “levels” will depend on the types of products or services sold.
For example, let’s use the example of an online pajama site. Here the scoring may be as follows:
Recency: 3=purchased in past month, 2=purchased in past 2-12 months, 1=purchased more than one year ago,
Frequency: 3=purchased more than 5 items, 2=purchased 2-4 items, 1=purchased 1 item
Monetary: 3=purchased over $400, 2=purchased $100-$499, 1=purchased less than $100
Your customers would have scores from 3 to 9. You can then plot them in a 3-dimensional bar chart as shown here to look at natural clusters, and to possibly make adjustments to your scoring levels.
The next step would be to look at marketing campaigns targeted at these groups such as:
Customer appreciation to reward your highest value customers
Win-back campaigns to approach those with high monetary but low Recency
Frequent purchase campaigns to up frequency scores
The advantages are that you will have more personalized, targeted messaging. And you will save money by marketing to those customers who are most likely to respond. But use some discretion with RFM. Don’t overburden high scoring customers so they feel badgered, and don’t give up completely on low scoring customers – they may very well come back.