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The RFM (recency, frequency, monetary value) notebook is a marketing model for the BlueConic AI Workbench. You can use the model to analyze customer order data and score customers on three dimensions: Recency (how recent was the last purchase), Frequency (how frequent are purchases made), and Monetary value (how much was spent).

With RFM scores stored in customer profiles, you can create segments like "Frequent Buyers," "Recent Customers," or "Top Spenders in the Month before Holidays". This will allow you to market to specific types of customers based on their purchasing behavior. Note that in order to use the RFM notebook, you first need to have customer order data in BlueConic.

Scoring RFM (Recency, Frequency, Monetary value) with AI Workbench

The RFM notebook examines orders on the event timeline of customer profiles in a segment within a specific time period. By default, the notebook considers up to 500 order timeline events with a "revenue" field per customer lifetime, but you can configure a specific timeframe. Per customer profile, this notebook determines the most recent order, the total number of orders, and the total amount spent on all orders and stores these values on the profile. Next, the notebook scores customer profiles by bucketing these values in five equally sized score buckets (quintiles). Scores are values from 1 through 5, with 1 meaning the bottom 20% of the segment, and 5 meaning the top 20% of the segment.

For example:

• A customer with an RFM Recency Score of 1 is in the bottom 20% of the segment when it comes to the most recent order. In other words: the most recent order is more towards the start date when compared to most recent orders of other customers in the segment.
• A customer with an RFM Frequency Score of 3 is in the middle 20% of the segment when it comes to the total number of orders. In other words: the customer orders about as often as average customers in the segment do.
• A customer with an RFM Monetary Score of 5 is in the top 20% of the segment when it comes to total amount spent of all orders. In other words: this customer is among the customers spending most in the segment. 

Adding an RFM notebook

1. Select AI Workbench from the BlueConic navigation bar.
2. Click Add notebook.
3. A pop-up window appears. Scroll down to RFM notebook and click it.
4. The RFM notebook opens.

Configuring an RFM notebook

1. If you have the Notebook editor permissions, you can go to the Notebook editor page to initialize the parameters and to see the description of the notebook.
2. Go to the Parameters page.
3. Configure the parameters:
   • Select the RFM segment that defines the customers whose orders will be used for the analysis.
   • Select the profile property that stores the most recent order date/time.
   • Optional: Enter a specific number of months to look back at customer order event data.
   • Optional: Enter the number of days to include before the last execution.
   • Verify that the profile properties where the RFM values and scores will be stored are the ones you prefer and make changes as necessary.
   • Optional: If you'd like to add the average of the recency, frequency, and monetary value scores on the profile, select a profile property for storage.
   • Enter a name for the notebook and click Save to save the connection. 

Running the RFM notebook

1. Go to the Schedule and run history page.
2. In the metadata section at the top of the page, you can request email notifications each time the notebook runs or only for failed runs. For details, see: setting up email notifications for AI Workbench.
3. Click Run now to run the RFM analysis manually.
4. To schedule the import and export for a future date, Enable scheduling by clicking the Settings icon. Select how to schedule the import by choosing an option from the drop-down list:
   • Every X minutes
   • Number of times per day
   • Days of the week
   • Days of the month
   • Weekday of the month

   Set a time for the import. Click OK. 

After running the notebook, you can view its output by clicking Preview. Scroll to the bottom to see a graphical representation of the RFM analysis.

Visualizing RFM notebook results with insights

To display the graph of the most recent run in your RFM notebook, add a Notebook - Single cell insight to a BlueConic Dashboard. Once added to a dashboard, configure the insight by selecting your RFM notebook and entering "16" for the cell number. This insight offers a deeper analysis of profile distribution across RFM scores, complementing the main output of the notebook, which assigns scores to each profile.

Interpreting the insight:

• Bubble colors: The colors of the bubbles represent the sum of the Recency, Frequency, and Monetary (RFM) scores, ranging from 3 to 15. Warmer colors (e.g., in the (1,1,1) position) indicate lower scores, while cooler colors (e.g., in the (5,5,5) position) reflect higher scores, helping to distinguish positions in the 3D space.
• Bubble size: Each bubble represents a group of profiles with a unique RFM score combination, and the size of the bubble corresponds to the number of profiles within that combination.
• Score Assignment: Each consumer is assigned a score between 1 and 5 for each RFM dimension. The graph shows that the majority of profiles fall into the (Recency = 1, Frequency = 1, Monetary = 1) category, with a significant number of profiles having low RFM scores overall.