This is one of the most important type of marketing customer analytics in the e-commerce sector. It helps you assess the value of a particular customer to your online store, or any other business. It involves analyzing user behavior in three areas:
- how recently customers have made a purchase (Recency)
- how often customers make a purchase (Frequency) and
- how much money our customers spend on purchases (Monetary).
What is analyzed:
1. Traffic sources based on RFM segments:
- what are the main media used by each user segment?
- which media initiate the customer journey and which media end it?
- how does the customer journey change depending on the user segment?
2. User behavior across groups:
- what elements are different in the behavior of users who have completed a transaction from those who have not?
- does user behavior vary depending on the products being searched for?
- how users’ behaviors on the website differ depending on their previous experience (frequency of visits to the website or purchases made)
3. Flow of users between defined segments in the long term, taking into account the “seniority” of the customer:
- do customers flow from one segment to another increasing or decreasing their engagement?
- how do business parameters change over time within each segment (average cart value, frequency of purchases, churn rate, etc.)?
- what percentage of new users become loyal customers and what percentage of them leave?
Key benefits of RFM analysis:
- you can capture insights and gain a better understanding of user behavior
- you can identify key data describing the length of customer journeys and the sources of visits
- you can identify the most effective traffic sources
- you can precisely select communication channels optimizing the effectiveness of advertising budgets