Customers are not created equal. Breaking customers into homogenous groups – called segments, helps with 2 objectives –
- Help with understanding customer better. Aka know your customer.
- Improve targeting and communication to drive better results.
It sounds easy and powerful.
The only problem with segmentation is it goes out of hand very soon. You can segment on geographic, demographic, technological, behavioral, and whatnot. Also on each segment (maybe 100+), you need to make different targeting.
Not worth my time and effort.
RFM (Recency, Frequency, and Monetary) framework of segmentation based on customer behavior is one of the best approaches to take for segmentation to keep your sanity and get results.
What is RFM Framework?
RFM stands for segmenting your customer base on Recency, Frequency, and Monetary behavior has taken together. Looking at all of them together for a single customer is a key, otherwise, it will be imbalanced.
How recent is the interaction/behavior shown by the customer?
Taking purchase behavior, when was the last order was placed?
Taking visit behavior, when was the last visit done by the customer on the website/app?
Frequency – What’s the frequency of the behaviour shown by the customer.
Again, taking purchase behavior, how frequently customer places the order in a given time frame?
Taking visit behavior, how frequently customer visits the website/app in a given time?
Monetary – What’s the monetary worth of the customer during the journey.
Taking purchase, we can include the total lifetime value of the customer.
Taking visits, we can include the total ad revenue generated by this customer.
How To Do RFM Analysis?
To get the RFM analysis for your customers, here are the steps –
- Take the customer data in simple excel or database with following fields
- Customer ID
- Last behaviour done date / time. Like last order date.
- Total Interactions during time frame / Total orders in last year
- Total monetary worth during time frame / Customer life time value.
- Give scale to the