Nowadays, the segmentation of the customer database is a real trend topic.
Specifically, the RFM matrix is known as one of the most popular and efficient segmentations, providing companies with relevant data for insight driven strategies, but how does it work? And what are the audiences that this analysis lets you map?
We have already talked about Acquisition VS Retention: the Hamletic doubt for marketing, and we come to the conclusion that actually these approaches should be complementary.
However, we should consider that:
- new business is 6-7 times more expensive than the existing business (source: Coopervision) and it will be more and more costly since the costs of advertising are constantly growing YoY,
- a 5% increase in existing customer loyalty can lead to an average revenue increase of +25 to + 95% (source: Harvard Business Review).
Focusing on the Customer Retention Rate is therefore essential. The RFM analysis is used to identify loyalty parameters – Recency, Frequency and Monetary – by defining clusters and segments.
Our proprietary technology Retention AI is based on this approach to boost your loyalty strategy.
At the end of the article, you will find the 10 custom audiences you should immediately start recognizing and segmenting.
The RFM matrix: how does it work?
The purpose of the RFM matrix is to understand, analyze, cluster and then activate those customers that are already acquired and deserve more attention.
However, it also improves the customer journey, studying your customers with an additional layer of research: by segmenting them and asking the right questions, you can understand if there are blocks or bottlenecks or even shortages for a specific product / service / storytelling.
Here’s an example. You might ask yourself: why do most customers get stuck after their first purchase? Is this a value proposition error because I promised a 10% discount in the newsletter? Or does the shipment arrive late? Or is customer care service slow to respond and the customer got upset? Or again, is my brand storytelling convincing enough?
You might think that the RFM analysis helps companies identify their top clients, but is it enough to acknowledge the strong points you already know? Likewise, identifying the worst customers – the ones you already lost and those you should better lose anyways – is not that useful after all.
The most interesting insights are in the middle of this range: people who do not complete their purchases and those who have bought back a few times and then evaporated.
Therefore, here the point is not to take the best customers and “squeeze” them even more, but to find good customers with a good potential and make them excellent, understanding what they need to become loyal customers.
As its acronym suggests, the variables of the RFM model are 3:
- Recency, i.e. how many days passed since the last transaction;
- Frequency, the frequency of the purchases;
- Monetary, the monetary value of orders.
Depending on the size of the customer database, you can assign a score from 1 to 5 to each variable.
By doing so, it is possible to understand what works and what doesn’t in the purchase path of your eCommerce, while identifying the profile of your ideal customer.
The goal of the analysis is to understand the distribution of the customer database, segmenting them and clustering their characteristics and motivations, in order to develop customized objectives and strategies for each cluster you identify.
However you should keep in mind that “recent”, “frequent”, “high / low chart” are relative parameters, to be defined according to your brand: product by product or project by project, since there are no absolute values of what is good in terms of frequency or amount of the cart.
This approach can obviously be applied to those purchases that are more likely to be repeated over time, so it is especially effective on “fast” consumer products or services.
The 10 “basic” audiences you need to know
What are the 10 typical types of audience that you can find while working in the eCommerce industry?
We have identified 10 and listed them together with their scores according to each parameter:
- VIPs – Recency 5, Frequency 5, Monetary 5
- Potential VIPs – Recency 3-5, Frequency 3-5, Monetary 3-5
- Big Fishes – Recency 4-5, Frequency 1, Monetary 4-5
- Promises – Recency 4-5, Frequency 2, Monetary 4-5
- Applicants – Recency 4-5, Frequency 3, Monetary 3-4
- Curious – Recency 4, Frequency 1, Monetary 1
- At Risk – Recency 2-3, Frequency 1-5, Monetary 1-5
- Ex lovers – Recency 1, Frequency 5, Monetary 5
- Fireworks – Recency 1, Frequency 1, Monetary 5
- Hit and Run – Recency 1, Frequency 1, Monetary 1