There are numerous methods of identifying customer groups or segments analytically. Apteco, a true expert in this field, picked two of these methods - the RFM and the Pareto analysis – to assist us in understanding customer data without having to be a statistician.
The term RFM is an abbreviation for R = Recency, F = Frequency and M = Monetary that raises the questions:
- How long has it been since the last purchase?
- How often have there been purchases in total?
- How much revenue was generated?
Using these criteria, your TOP customers can be identified relatively quickly. If you display the data in a Venn diagram (as shown in the illustration below), you can see immediately how the individual criteria overlap. In this case, the TOP customers form the segment in the middle: the last purchase was not long ago, overall, there were many purchases and the sales value of the purchases is high. The target group is determined that way, now the only thing missing is coming up with the right campaign for these customers.
Each dimension of the RFM analysis can be expanded with additional criteria and variables. For example, with regard to recency, you could determine regularities in purchasing behavior or a purchasing rhythm (e.g. every three months or once every six months) in order to predict the next purchase and incentivize it with a special offer. You could expand the frequency to other levels and thus, for example, also analyze the email interactions of your customers. If you also analyze the sales value for arithmetic means, variances or include the following Pareto analysis, you will receive further valuable insights.
The Pareto principle, from Vilfredo Pareto (1848-1923), states that as a rule 80% of the result can be achieved with 20% of the effort. In relation to the customer analysis, you ask yourself the question in the Pareto analysis: “Who are the 20% of my customers who generate 80% of my sales?” In other words, who are my most valuable customers in terms of sales?
For the Pareto analysis, the first step is to divide all sales or order values in the database into ten parts of the same size (so-called deciles), as shown in the first diagram. In the next step you sort all your customers and assign them to the ten sales classes generated previously. This sorting is shown in the second diagram. It immediately becomes apparent that a relatively small part of my customers, namely the first bar in the diagram, already generate 10% of total sales, while the last bar contains a large number of customers who together also convert 10% of the order values. Now it is up to you to plan a suitable campaign for the customers who generate most of your sales.
The Pareto analysis can also provide an even deeper understanding of your most valuable customers through additional criteria. For example, you could take a more up-to-date look at your most valuable customers by including only certain time periods (such as only orders from the last twelve months) in the analysis. In addition, with the Pareto analysis, certain product groups can be examined more closely.