RFM stands for Recency, Frequency, and Monetary value, each of which relates to a specific type of consumer behavior. RFM Analysis is a strategy that helps organizations assess the value of a customer based on three pieces of crucial information viz. how recently did the customer make a purchase (recency), how frequently does the client purchase (frequency), how much does the customer spend on individual transactions in general (monetary).

These three metrics help organizations logically predict which all customers are more likely to make purchases in the future. This is because frequency and monetary value affect a customer’s lifetime value while recency affects retention. By analyzing these three data points, brands can optimize their marketing strategies i.e. segment customers into homogeneous groups, engage them with relevant notifications and personalized messages, timely dispatch winback campaigns, reduce churn etc. and thereby enhance revenue and build customer loyalty.

In a nutshell, RFM Analysis is a data-driven customer segmentation technique employed by organizations to quantitatively rank and group customers based on the recency, frequency and monetary total of their latest transactions in order to identify the best customers and thereby dispatch targeted campaigns. In order to enable brands to effortlessly comprehend the aforementioned metrics, in addition to segmenting consumers into distinct groups such as loyal customers, promising clients, champions etc., NotifyVisitors consolidates the RFM scores and depicts them via easily intelligible two-dimensional charts and data tables.

RFM Analysis in NotifyVisitors

Within the NotifyVisitors software, RFM Analysis is conducted at a time for a single Revenue Event i.e. an event that indirectly or directly affects the revenue generated by your organization. 

In other words, you can map as many Revenue Events as you like such as Order Placed, Checkout Update etc. within the software, but you will only be able to view and compute RFM Analytics for exclusively one such event at a time. Proceed as follows to perform RFM Analysis:

1. Navigate to NotifyVisitors Dashboard > Real Impact > RFM Analysis.

2. You would notice that under the 'Filter' section, there exist two modules namely 'Date Filter' and 'Revenue Event'.

From the 'Date Filter' module you can specify the time period for which you intend to view RFM Analytics. From the 'Revenue Event' dropdown you can select a specific preconfigured event for which you intend to perform RFM Analysis.

3. Under the same 'Filter' section, you would also notice two buttons viz. 'Map Revenue Event' and 'Analyze'.

You can map or configure events for which you intend to perform RFM Analysis, by clicking on the 'Map Revenue Event' button. Once you configure an event, it will get listed within the 'Revenue Event' dropdown (kindly read the next section to learn how to configure a Revenue Event).

You can perform RFM Analysis for a preconfigured event by first selecting it from the 'Revenue Event' dropdown and then clicking on the 'Analyze' button. 

4. Once you click on the 'Analyze' button, after selecting an event from the 'Revenue Event' dropdown, the software will automatically perform RFM Analysis for the chosen event and provide an easily comprehensible visual representation of computed analytics in the form of two-dimensional charts and data tables.

That is to say, the software will automatically compute RFM metrics for all those customers who performed the chosen Revenue Event, within the time period specified via the 'Date Filter' module. Additionally, the software will segment customers into distinct groups (such as potential customers, loyal customers, can not lose customers, hibernating customers etc.) based upon their RFM score.

NotifyVisitors automatically creates the following RFM segments

• Champions: Highly active users with the highest recency and frequency scores.
• Loyal Users: Users with high frequency and strong recency scores.
• Potential Loyalists: Recent visitors with the potential to become loyal customers.
• New Users: Recent sign-ups with low frequency, great for encouraging repeat use.
• Promising: Users with high recency scores, showing potential for high frequency.
• Needing Attention: Users with above-average recency and frequency scores.
• At Risk: Users with above-average frequency but low recency, strong candidates for re-engagement.
• Cannot Lose Them: Previously active users with low recent engagement, important to re-engage.
• Hibernating: Users with the lowest recency and frequency scores, may be lost.
• About To Sleep: Users with below-average recency and frequency scores, may slip away if not engaged.

With a mere glimpse at this representation, you can quickly determine whether your marketing strategies are effectively yielding the desired results. You can thereby optimize and attune your advertising approach (if required) distinctly for each segment in order to enhance conversion rate.

You can also view detailed analytics for each segment in a tabulated form, simply by clicking on it. Once you click on a segment, a pop-up will appear on-screen containing the following information pertaining to it:

1. User Count
2. Average Monetary Value
3. A brief description of the segment
4. Recency Score (range and average)
5. Frequency Score (range and average)

You can close the pop-up by clicking on the 'cross' button located at its top-right corner.

How to configure a Revenue Event in NotifyVisitors

Proceed as follows to configure a Revenue Event:

Process described in step nos. 1 to 6 is illustrated in the GIF provided below.

1. Navigate to NotifyVisitors Dashboard > Real Impact > RFM Analysis.
2. Click on the button titled 'Map Revenue Event'. You can map or configure a Revenue Event via the settings available under the 'Revenue Mapping' section.
3. Click on the 'Revenue Currency' dropdown and specify the currency of your 'Revenue Event'.
4. Enter a 'Label' to identify the Revenue Event which you are about to map/configure.
5. Next, select an event from the 'Revenue Event' dropdown. Note that the event you select should indirectly or directly affect the revenue generated by your organization.
6. Next, specify an integer attribute for your Revenue Event (such as total_price, cart_items_cost etc.) via the 'Revenue Attribute' dropdown. Note that the attribute you select holds an integer value since 'revenue' is mapped in currency which in turn has a numeric data type.

Under the 'Revenue Mapping' section, you would notice two more sub-sections viz. 'Conversion Deadline' and 'Conversion Tracking Metrics'.

Via the 'Conversion Deadline' sub-section, you can specify the time limit for which conversions will be tracked against the mapped Revenue Events.

Via the 'Conversion Tracking Metrics' sub-section, you can specify the user activity (such as Email open, Click, WhatsApp read) through which conversions will be tracked and registered within the software.

7. Click on the 'Save' button once you have configured the Revenue Event(s). Next, click on the 'Back' button in order to return back to the RFM Analysis section.

A brief overview on how RFM Analysis works

RFM Analysis is a technique to determine which customers are of highest and lowest value to an organization by means of perusing three fundamental metrics namely:

• Recency (R)

  
  

  Recency refers to how recently a customer has made a purchase. Customers who have made a purchase recently are more likely to make another purchase in the future. However, if the customer hasn't made a purchase in a while, then you may need to nurture him/her with promotional offers or even reintroduce your brand if required. In RFM Analysis, customers are typically ranked based on the number of days since their last purchase.
• Frequency (F)

  
  

  Frequency refers to how often a customer makes purchases or conducts business with a brand. Customers who make frequent purchases are more likely to become loyal customers. Moreover, when customers purchase often, you learn about their product preferences. You can thereby dispatch relevant and personalized campaigns to them and thus keep them engaged. On the contrary, if a customer purchases once and never returns, then he/she can be a suitable candidate for customer satisfaction feedback. In RFM Analysis, customers are typically ranked based on the number of purchases they have made over a specific period.
• Monetary (M)

  
  

  Monetary value refers to how much a customer spends on purchases in general. Customers who spend more are likely to be more valuable to a business. In other words, customers who make many purchases at a high price point, are probably returning customers that can potentially turn into brand loyalists. In RFM Analysis, customers are typically ranked based on the total amount they have spent on purchases over a specific period.

This is how NotifyVisitors enables you to seamlessly perform RFM Analysis that empowers you to quickly identify valuable clients and segment customers into homogeneous groups, which can then be targeted with personalized marketing campaigns.