Overview

RFM (Recency, Frequency, Monetary) on the Netcore CE dashboard is a feature that helps you understand your customers. It helps you identify your most loyal, highest paying, one-time, high-risk, and likely to churn customers. It segments users such as Loyal, Unsure, Hesitant, and so on based on their behavior. It analyzes the following factors: recency of the customer purchase, frequency of product purchase, and average order value. This analysis allows you to identify their loyal customers and create marketing strategies accordingly.

Refer to the given table to understand the key metrics of RFM.

Metric	Description	Example
Recency	The frequency of the customer transactions or visits.	Ordered a product in the last 7 days/14 days/1 month/3 months.
Frequency	The frequency of the customer transactions or visits.	Purchases a product every 6 months/once in 3 months,
Monetary	The intention of the customer to spend or the purchasing capability of the customer.	The total order value has been Rs.5000 over the last 12 months, and the average order value is Rs.416.

RFM Calculation

RFM calculation involves ranking customers based on their recency, frequency, and monetary scores. Here is how it works.

Recency Score

Rank customers from most recent to least recent.
Divide them into three groups (1 to 3), where 3 indicates the most recent purchases.

Frequency Score

Rank customers by the number of purchases.
Divide them into three groups (1 to 3), where 3 indicates high frequency.

Monetary Score

Rank customers based on total spending.
Divide them into three groups (1 to 3), where 3 indicates high spending.

This results in nine segments (3 recency scores x 3 frequency scores) that help you understand customer behavior.

RFM Model

Refer to the given table to know the RFM models and how it is calculated in Netcore CE.

Matrix	Criteria	Applicable Activities
RF (Engagement - Recency Frequency Matrix)	Engagement: User actions like email open or click. Recency: Last activity date. Frequency: Number of activities.	Push channels (Email, SMS, APN, BPN) and web/app activities except product purchase, page browse, and product view.
RFM (Recency Frequency Monetary Matrix)	Recency: Last purchase date. Frequency: Number of purchases. Monetary: Revenue from purchases.	App/ Web activity
RFDM (Recency Frequency Duration Matrix)	Recency: Last page browse date. Frequency: Number of activities. Duration: Time spent browsing.	Page Browse

Create RFM

Log in to the Netcore CE dashboard.
Navigate to Analytics > RFM. The RFM listing page appears.

The listing page displays two columns: All RFMs and Starred. All created RFMs appear under All RFMs, while starred RFMs are listed in the Starred column. To add a path to Starred, click located to the left of the RFM name.

Click CREATE RFM in the top right corner to create a new FRM. Refer to the table below for the options for creating a RFM.

Option	Description
Duration	Select the time period for analyzing user activity.
Target audience	Select the group of users you want to analyze, including existing contacts, lists, or segments.
Channel	Select the communication channel for analysis. RFM is available for Email, SMS, App push, Web push, and App/ Web activity tracking.
Activity	Select the activity from the dropdown menu you want to analyze.

Once you have added the necessary parameters, click APPLY.

Based on your filters, a chart is generated. In the chart, the X-axis represents Recency, divided into three sections: Low, Medium, and High. The Y-axis represents Frequency, divided into three sections: Low, Medium, and High. Each section shows different categories of users, displaying both the number of users and the percentage of users for each category.

The users are divided into various types with unique tags/names. To understand their descriptions, refer to the table below.

User type	Description
Need attention	Users who have been inactive recently.
At-risk	Users who have below-average RFM scores and are likely to churn.
Dormant	Users who have the lowest RFM scores.
Loyal	Users who have engaged multiple times and have the potential to become loyal users.
Unsure	Users who have above-average RFM scores but are yet to become loyal users.
Hesitant	Users who have above-average frequency but low recency.
Rising stars	Users who have a strong frequency score and the recency score is increasing.
Novice	Users who are your most recent users with low-frequency scores. Engage these customers to make a repeat purchase.

After adding all desired filters to your RFM analysis, click SAVE in the top right corner. Your created RFM will appear on the RFM matrix listing screen.