One size doesn’t fit all. Realize your first RFM analysis. 2/2

9 janvier 2017

As a business owner of a small or medium company, you may think that marketing customer analysis is made for large enterprises. You have learnt to be focused on your cash flow to survive and marketing would come after. This is quite normal. But realise that you miss an interesting part of your business analysis, and the basis for your sales strategy. And this analysis will only take a few hours to be done and may even be automatised. If you have the records of your sales and M.S. Excel (or equivalent) you are ready to perform your first RFM analysis!

Why should you use an RFM analysis

When you ask your sales team to sell to their customers, here’s what can happen: salespeople are human and they will call in the first place their most receptive customers. Even if these clients are not really the most profitable for your business. But in fact, the real problem is the following: how do you know that customer X is profitable and customer Y is not?
What you really need is to focus all your efforts on your most profitable customers, stop selling to unprofitable customers and automate as much as possible the process for the others.
This is where a customer analysis adds value and saves you money on your sales costs. Of course, you can perform a deeper analysis, including products sold, seasonality … but let’s stay basis.

Define your metrics

RFM stands for Recency, Frequency, Monetary. It is the easiest form of customer database segmentation.

The metrics are:

  • Recency = the freshness of customer activity (when was the last purchase)
  • Frequency = the frequency of customer transactions (how often do they buy)
  • Monetary = the willingness to spend (how much do they spend)

What you need for a start:

  • A unique identifier for customers
  • All you invoices with date and amount during a certain period of time (1, 2 or 3 years)

Create your segments

For each metrics (R, F, M) you need to determine the distribution and define the segmentation. For example, you can choose to have segments with customers who bought during the last 30 days, the last 90 days, the last six month, the last year or those who bought before the last 365 days. For each segment, you add a number from 1 to X.

Let’s say we want to make a first analysis with 3 segments for each metric:

  • Recency -> 3=last 3 months, 2=last 6 months, 3=last 365 days
  • Frequency -> 3=10 times and more, 2=3 times and more, 1=less than 3 times
  • Monetary -> 3=more than $3000, 2=$1000 and more, 1=less than $1000

Of course, you have to adapt these segment to your own activity. You can also have four or five segments per metric but the more you have the more difficult it is to analyse. With 3/3/3, you already have 27 segments!

RFM rating

Value your subsets

Use a stacked contingency table to count customers in each segment and compute summary statistics.

RFM analysis

You ought to separate customers with only 1 transactions as they are not yet regular customers and will bias the analyse.

RFM actions


Take decisions

What does RFM teach you?

  1. Green segment customers are the best customers. You want them to keep on buying from you. Stay close with regular promotions and communications.
  2. Orange segment customers are at risk, you want to keep them with you. They need specific attention and specific sales/marketing actions.
  3. Red segment customers are churned or bad customers, you have to take a decision on these customers, depending on their potential.

To go further with RFM analysis

RFM analysis by product category

You can perform an RFM analysis for each product category to be even more specific. Let’s say you are a product manager in an IT distributor and you want to know your best customers in your category. In that case, you will work only with sales records of your specific category.

Compare RFM results with customer potential

Be very careful with RFM results because RFM analysis will only give you an image of your actual relation with your customers. You have to compare these results with your customers’ potential, and that’s where a deeper analysis with sales managers make sense.

  • Example 1: Imagine you work with a company for three years now and this company only work with you from time to time, as a second or third supplier. You never really realise the potential of this customer. So when you compare your RFM rate, 212 for example (cf “Value your subsets”), it appears that you lose a lot of business and you should have high sales objectives with this accounts in your pipeline.
  • Example 2: you have a very loyal customer who buys almost everything from you. But this is a small company and you already took all the potential of this account. In that case, you all have to maintain good relationships with him (think in advocacy with this company) but your pipeline won’t change.

As a result, you can adapt your Sales and marketing plans accordingly and be much more efficient.

Now it’s your turn!

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Auteur : Nicolas ROUSSEL

De formation marketing et commercial, j'accompagne depuis plus de 20 ans les entreprises technologiques dans leur développement. J'ai créé l'agence I AND YOO pour répondre aux problématiques de génération de leads en vente complexe.