Do you know the Pareto principle? Maybe you know it more as the 80/20 rule. It says that 20% of our efforts (or 20% of our customers) are responsible for 80% of our success or revenue. At the same time, it also means that 80% of our customers are only responsible for one fifth of our revenue. Let’s be honest: No matter if this ratio applies to us or not. The fact remains that there is a small number of customers who are especially valuable to the company. Therefore they should be treated as such. For example, with special discounts and offers that increase customer loyalty and ensure that these customers remain with us for a particularly long time. On the other hand, we should examine where we can save costs for addressing customers who bring very little value to our company. 

So far, I have only experienced in very few projects that the value of individual customers for a company was used in the planning of communication efforts. Most marketers only evaluate the performance of marketing activities, but rarely look at the customers they interact with. However, it is not so difficult to identify the most valuable customers. In this article, I show how we can use an ABC classification to separate our customers into different groups and target them more effectively. Here we can look at identifying the most valuable customers not only for the entire company, but also on the basis of a specific topic or interest. This also makes it possible to distinguish customers with a high interest in product group A from top customers in product category B.

How does the ABC Analysis (or ABC classification) work?

An ABC analysis can of course be applied to many topics. In addition to an analysis of the most valuable customers, the markets with the highest turnover, the most profitable products or – relatet to the marketing – the most successful campaigns could also be evaluated. For this purpose, we divide our customers into the groups already mentioned depending on their value for the company. These then form the basis for a more targeted and effective use of the available resources. Of course we are not limited to three segments, but we can also form more groups or classes if this makes sense for our use case. The criteria according to which we form segments and the size of the individual groups are strongly dependent on your business, the available data and above all on the target of the selection.

The basics – getting to know the data

In our example, we will evaluate customers classically according to their spendings. Here we want to look at purchases of the last year divided into individual months. Current purchases will receive a higher value than spendings that are already several months old. Therefore we write off 50% of the purchase value from the previous month every month. The sum of the purchases and their depreciation results in a valuation revenue for the individual customer. This valuation revenue is the basis for rating the value of the customers for our business.

Example: Evolution of the valuation revenue for two customers with multiple purchases:

Customer 1	Revenue 1	Revenue 2	Revenue 3	Valuation revenue
January	100,00€			100,00€
February	50,00€			50,00€
March	25,00€			25,00€
April	12,50€			12,50€
May	6,25€	80,00€		86,25€
June	3,13€	40,00€	40,00€	83,13€
July	1,56€	20,00€	20,00€	41,56€
August	0,78€	10,00€	10,00€	20,78€
September	0,39€	5,00€	5,00€	10,39€
October	0,20€	2,50€	2,50€	5,20€
November	0,10€	1,25€	1,25€	2,60€
December	0,05€	0,63€	0,63€	1,30€

Customer 2	Revenue 1	Revenue 2	Revenue 3	Valuation revenue
January				0,00€
February				0,00€
March	45,00€			45,00€
April	22,50€	60,00€		82,50€
May	11,25€	30,00€		41,25€
June	5,63€	15,00€		20,63€
July	2,81€	7,50€	40,00€	50,31€
August	1,41€	3,75€	20,00€	25,16€
September	0,70€	1,88€	10,00€	12,58€
October	0,35€	0,94€	5,00€	6,29€
November	0,18€	0,47€	2,50€	3,14€
December	0,09€	0,23€	1,25€	1,57€

Definition of the ABC classes

After we have built the valuation revenues for some clients, we get an understanding of what valuation revenues we can expect. Now it is time to define the classes. I decide to choose a certain monetary value as a decision criterion. But it would also be possible to simply choose the top 20% for group A, the next 40% for group B and the last 40% for group C. How large the individual segments are is up to you. Again, it must make sense for the business. With three classes (A, B and C), the first group is usually smaller than the others. Class A contains the most valuable customers for the company, who often have a secure bond with you. Class B contains the middle field, i.e. the customers who are neither particularly high nor particularly low in revenues. They have the potential to become A-class customers. Therefore we should examine how we can continue to nurture these customers and increase their purchases from our company. Class C on the other hand usually contains the most, but less profitable customers. This segment consists of one-time buyers or customers who add little value to our business. Encouraging them to make additional purchases is often very complex and expensive. This is where we have the most potential to save budgets and invest them in the other groups or in the acquisition of new customers.

In my example I choose the following classification for the valuation revenue:

• Class A: > 80€
• Class B: 40-80€
• Class C: 0-40€

For customer 1 this results in the following classification:

Customer 1	Revenue 1	Revenue 2	Revenue 3	Valuation revenue	Class
January	100,00€			100,00€	A
February	50,00€			50,00€	B
March	25,00€			25,00€	C
April	12,50€			12,50€	C
May	6,25€	80,00€		86,25€	A
June	3,13€	40,00€	40,00€	83,13€	A
July	1,56€	20,00€	20,00€	41,56€	B
August	0,78€	10,00€	10,00€	20,78€	C
September	0,39€	5,00€	5,00€	10,39€	C
October	0,20€	2,50€	2,50€	5,20€	C
November	0,10€	1,25€	1,25€	2,60€	C
December	0,05€	0,63€	0,63€	1,30€	C

Usage and thinking forward: Further segmentation criteria for customer groups

In practice, it can be helpful to add further criteria to such an analysis, for example to find new target groups for marketing campaigns. One possibility would be to look at purchases in different product categories. How about offering different follow up products two years after the purchase for A, B and C customers? Are there products that are purchased particularly frequently by A-customers but rarely by C-customers? What efforts do I make for the individual product categories in the customer segments? 

Not just the purchases but the customer characteristics themselves can be an approach for further segmentation and campaigns. For example, what are the attributes of class A customers and do I have similar class B customers? How did these customers become aware of my company and can I further expand the marketing measures concerned? As you can see, an ABC analysis is just a start and there are also a lot of possibilities to enrich other analyses with the results of these classifications.

In the next post I will show how an ABC analysis can be realized with the help of the Salesforce Marketing Cloud.

Have you ever used an ABC analysis? How did you set it up and what could you achieve with it? Let us know, we are curious about your experiences!