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Recency, Frequency, Monetary (RFM) Enrichment

Recency, Frequency, Monetary (RFM) Enrichment

Overview

The RFM enrichment model is a powerful marketing segmentation tool that analyses customer behaviour based on three key metrics: Recency, Frequency, and Monetary value.

The RFM model helps identify and categorise customers into distinct segments.

  • Recency measures how recently a customer performed an action such as a purchase transaction.

  • Frequency assesses how often they performed an action, such as a purchase transaction.

  • Monetary* value quantifies the total amount they have spent.

Monetary is an optional metric, and you can also create RF models to analyse just Recency and Frequency for a specific action, such as visiting your website.

The RFM model can be used to create audiences based on high-value, active, and recently engaged customers.

The RFM model includes a matrix chart, using the buckets for each dimension to visually show and organise customers into different segments based on their Recency, Frequency and Monetary values. The chart is actionable, enabling you to activate a segment from the RFM chart easily. 

 

See here for further info on

 

If Enrichment does not show on the sidebar it means it is not set up for you. Please contact support@wondaris.com if you would like it set up for your account (please note additional costs may apply)

Instructions

Key steps include:

  1. Clicking ‘Create Enrichment’ from the side panel

  2. Selecting the “RFM” card

  3. Filling in all steps:

3.1. Step 1

RFm 1.png

 

  • Model’s name: Name your model anything you like. This is a required field.

  • Description: Though optional, it's a best practice to describe the model for future reference.

  • Data source: Select a data source you want to build and train the model. The default data source has been prefilled and you can change to use another available data source.

  • Model scope: This is to limit the data used for training your model as well as the customers to apply the enrichment once the model is trained. You can either select:

    • All Customers; or

    • Filter a specific segment of your customers to enrich

3.2. Step 2

RFM 2.png

 

Select the fields in your data to measure each dimension Recency/Frequency/Monetary.

 

RFM Metadata and Datatype Requirements

Please note you must have the appropriate metadata tags set for each of the dimensions to be able to select a field within the configuration step for the RFM enrichment.

  • Recency - will show all fields of tagged with Event Date and Last Modified Date and of type DATE or DATETIME or TIMESTAMP

  • Frequency - will show all fields of tagged with Event ID

  • Monetary - will show all fields of tagged with Event Value and of type INTEGER or INT64 or NUMERIC or BIGNUMERIC or FLOAT or FLOAT64

 

3.3. Step 3

In this step, configure buckets in each dimension. You can select 3, 4, or 5 buckets based on your data. We already recommend default settings for each case which you can further update the bucket ranges and their names.

3.4. Step 4

RFM 4.png

Review your enrichment configuration before clicking Finish to create the RFM enrichment.

After successful creation, you can check the RFM result in the saved Enrichment and select any segment in the grid chart to either build an audience/segment or activate to a destination.

RFM 5.png