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WHO ARE YOUR CUSTOMERS?
To be able to know who your customer is and then send them personalized content, it's a good idea to have a
well-segmented audience. Proven method used in audience segmentation is RFM analysis. Is this unknown for
you? No worries, we'll explain everything. In the article, in addition to the definitions of individual terms, you will also
learn how to work with individual segments, how to divide them, how to approach segmentation and what its
Jan Roelf Bult and Tom Wansbeek introduced the concept of RFM analysis to the marketing world as early as 1995.
Since then, it has settled among marketers and has become a popular marketing tool.
What is it about?
RFM Analysis = a method with which we divide the database of existing contacts into groups, depending on how
often, how much and at what intervals customers buy from us. We will then tailor the content of the message, the
communication channel and the budget to each segment created in this way. This will not only provide us with better
targeting, but also lower advertising costs and a higher probability of return on investment. While this may
seem like a complexity at first glance, the opposite is true. One of the reasons why RFM analysis is such a popular tool
is the fact that it is a technically simple method that almost anyone can handle with a little effort. Your goal is to
find out which group of customers is the one who buys most often from you and then target your message there.
What data to collect?
RFM an acronym for words that segment our customers in some way:
R = recency = the time, that has elapsed since the last purchase
F = frequency = the total number of completed transactions
M = monetary = total amount of spent money
This is why we promised you that this analysis is relatively simple. The only data you need to collect it properly is these
three criteria. However, it is possible that this analysis will become a bit more complicated. The situation may arise
when you have a very large e-shop and you offer several unrelated product categories. Then it is good to process the
RFM analysis for each category separately, if you do not do so, there is a risk of inaccurate data and your analysis
would not be very effective.
How to divide customers?
In practice, it is good to create three bands for each criterion. However, it is not possible to apply one type of band to
all three, as then the analysis would be meaningless. The customer is already aware of your brand, knows what to
expect, but does not have a shopping experience. For example, a welcome discount on your first purchase will be
great. It does not have to be particularly high, a symbolic one that will activate the customer will suffice. The discount
can be for a specific product category, or for the entire range. Remember that this individual is probably on your
website for the first time, so you want them to see the products as much as possible.
Another type can also be the category of customers just after the purchase, or those who make purchases from
you regularly. It can be according to their own choice, or you can play with automation and find out which product they
buy most often and then offer it as a gift.
How to approach segmentation?
Segmentation can be perceived in several different ways. Which suits you best is up to you. It is important that it is
uniform for your entire company and that all your employees look at individual customer groups from the same point
- Intuitive approach: an approach based on experience, intuition and trial and error
- Deductive approach: we observe how segmentation is perceived by competitors and companies operating in a similar industry
- Inductive approach: we work with the data we already have about our customers
In practice, the latest approach is increasingly being used. However, if we want to put this approach into practice, it is
good to collect the necessary data and be able to orientate in them. In addition to the frequency of purchases, also
monitor what the customer is acquiring, what price level he is at and to what extent he also uses additional services.
Summary - how can RFM Analysis help you?
- improve the performance of individual marketing channels
- increase and improve conversion rates
- increase average order value and thus improve the "customer lifetime value" of individual customers
- increase the interest and loyalty of other customers
- Improve and strengthen relationships with loyal customers and send them VIP offers