A common question that businesses ask themselves is “Which of my customers are the most valuable?”.
While this is a simple question, there are ways of answering this which can prove to be quite complicated. For example, how does the business define “valuable”? This could be customers who spend the most in total, or customers who have a large number of transactions. Alongside this there are other considerations, such as how recent the last purchase was, or the average basket size.
Luckily, we can use the Recency, Frequency and Monetary framework (or, RFM) to help us identify high value customers.
What is RFM?
As the name suggests, RFM takes into account 3 factors for determining the value of different customers:
When did the customer last buy an item? Can we identify if a customer is “active” or has “lapsed”?
How many times has a customer made a purchase? Can we identify customers who make many purchases, or few purchases?
How much in total has each customer spent?
Using these three dimensions can help identify different segments of the user base which would respond to different marketing messages and promotions.
Analysis using PowerBI
PowerBI is a business analytics service that delivers insights by transforming data into stunning visuals. We have loaded example customer data into PowerBI to create an interactive visualisation for you to explore the RFM framework.
After loading sample customer data into the PowerBI platform, we can look at the demographic profile of those customers who score highly in the Frequency and Monetary dimensions.
The demographic data can help marketers keep their messaging relevant, should they choose to reach out to the different segments.
A particularly interesting group of customers are those who have a high Monetary score but a low Recency score. In other words, they are customers who have spent a lot of money but have not done so in a while. The business may want to consider strategies to re-engage those customers as doing so would likely prove to be very profitable.
In another tab of the dashboard we can see the (fabricated) names and email addresses of the customers in a table. This can be filtered and exported to create custom lists for marketing purposes.
The screenshot below shows those customers who:
- Are married
- Belong to a 2 adults, no kids household
- Have previously spent a lot with the business
- Transacted recently (active customer)
With the flexibility in filtering that PowerBI offers, it is a great platform for ad hoc customer segmentation for frontline marketers and stakeholders. There is also the ability to export the data once filtered, so users are really empowered to do what they wish with the data.
Get in Touch
Panalysis is an industry leader in data and analytics.
Reach out to email@example.com if you would like to hear more about how we can help you with customer segmentation and visualisation using PowerBI.