eRFM is our ecommerce behavioural model designed to help you better understand the potential of your contacts by creating customer personas from a combination of engagement score and RFM score.
eRFM is made up of two scoring models:
Engagement score - looks at how engaged your contact is - for example, their email opens and clicks, web sessions, and abandoned carts. This creates a set of scores from Lightly Engaged to Most Engaged.
RFM score - compares your customers' purchases made to each other against three dimensions of data: Recency (R), Frequency (F) and Monetary (M). This creates a set of scores from Inactive to Champions.
When we compare both scoring models we get a new set of eRFM personas that combine the engagement score and RFM score:
On the X-axis (horizontal) the engagement score increases from lightly engaged to Most engaged.
On the Y-axis (vertical) the RFM score increases from Inactive to Champion.
The decision window
At the core of eRFM, we have the decision window. This is the timeline where a contact makes a purchase. The decision window timeline goes like this:
We set this timeline as 30 days by default, but you can change this if you want.
As the decision window develops, we assign a score to your contact to determine how likely they are to make a purchase. If your contact is engaging well by opening emails, clicking links, and viewing webpages, they are scored highly by the eRFM model.
How eRFM scoring works
We score your contacts throughout the decision window based on three factors:
This is the weakest scoring criteria.
This is the middle scoring criteria.
Viewing your webpage for five seconds or more
This is the highest scoring criteria.
As time passes, the scores start to decline until the end of the decision window, where they reset entirely. The eRFM scoring model updates every 24 hours.