As an eCommerce retailer, you are well aware that identifying your customer segments and catering to their need is vital. How are you putting that theory into practice?  

In this blog, we will dissect RFM analysis to understand its resourcefulness in customer segmentation and personalized marketing.  

What Is RFM Analysis? 

RFM analysis is a data mining technique that eCommerce retailers use to determine their most valuable customers.  Here, RFM is abbreviated for recency, frequency, and monetary value. With an RFM model, retailers can analyze their customers' past transactional data and use that research for effective customer segmentation.  

The specialty of RFM analysis resides in how dynamically it addresses all kinds of customer behavior based on their score on recency, frequency, and monetary value indicators.  

What Are Recency, Frequency, And Monetary? 

RFM analysis is built upon three cornerstone metrics: recency, frequency, and monetary.  

Recency 

Recency implores you to answer how recently a customer purchased from you. This factor is based on the connotation that the more recently a customer has purchased from a brand, the more likely they will do subsequent business with the brand.  

You can use the recency score to remind those customers to revisit your eCommerce store soon to continue fulfilling their needs.  

Frequency  

With frequency, you analyze how often a particular customer purchases from you. The frequency of the transaction can be impacted by the product type, the need for replacement or replenishment, and the price point. Determining the frequency score can help fixate your marketing efforts.  

Monetary Value 

The monetary value attribute demands you to determine how much money a customer spends on a purchase. The general rule of thumb behind the monetary analysis is to put more emphasis on encouraging customers who spend the most money to continue to do so.  

But you have to be careful while working on this metric—for while it produces a better return on investment (ROI) in marketing, it also runs the risk of isolating less transacting yet consistent customers. 

How To Perform RFM Analysis? 

Now that you know what RFM analysis is, let's use a simple example to perform the same. Typically, in the most simple approach, the RFM analysis has five steps, as follows:  

• RFM data collection  

• RFM scale fixation 

• RFM score assignment 

• RFM indexing 

• RFM segmentation  

RFM Data Collection 

The RFM model requires you to analyze the customer transaction history. To do that, you need the dataset of customer transactions. 

So, the first step is to pull out the recency, frequency, and monetary data for your customer base. You can extract this data by exporting the necessary fields from your customer data platform.  

RFM Scale Fixation 

Post pulling the necessary data, you need to create custom filters to curate effective customer segments for your entire customer base.  

So, we shall rank-order customers from a score of 1 to 5, with 1 being the least score and 5 being the highest score. And for each of these scores, let's create a filter subject. However, note that the subject will vary depending upon the nature of your eCommerce business.  

RFM Score Assignment 

Now, it's time to correlate the first two tables to populate the resultant table - the RFM score table. In this step, we are going to assign each of your customers a score by relating their RFM metrics and the filter subjects. This way, we are converting the absolute values of transactions into clusters of similar transactions.

RFM Indexing 

In this step, we need to get a cumulative score based on the recency, frequency, and monetary scores. We'll do away with the RFM values in parenthesis and mark the RFM index based only on the RFM score.

RFM Segmentation  

Since we executed customer ranking in 5 grades across three criteria, the mathematically resulting number of distinct customer segments would be 125. However, practically speaking, there's no need for such unique and in-depth customer segmentation aspects. You can use your best judgment to decide the number of scoring segments required and populate the quintiles.  

For this example, we shall group our customer base into 10 clusters of customers, as below: 

• Price sensitive customers 

• At-risk customers 

• Lost customers 

• Lapsing customers 

• Newbies 

• Needs attention  

• Loyal customers 

• Potential loyalist 

• High-value customers 

• Brand advocates 

Now, let's look in detail at the various customer segments we could potentially cluster our customers into.  

Price Sensitive Customers 

These are the kinds of customers who express intense interest in price-led promotions. You cannot define their loyalty by brand interactions. You will identify their loyalty wavering by the price they have to pay for your products. Discovering this group of customers can make all the difference in running special offers and discount sales. 

At-Risk Customers 

The customers who are at-risk are your existing users who haven't purchased from you in a long time and are on the verge of becoming lost customers. So, you need to coax them with a timely marketing strategy to ensure that the customer retention rate doesn't deflate.  

Lost Customers 

These are your unfortunate batch of customers - ones who have stopped purchasing from you altogether and have moved to your competitor brands. It's hard to re-engage the lost customer segment with marketing campaigns because they either hold a negative impression of your brand or nurse a trustworthy alternative. 

Lapsing Customers 

Lapsed customers are your existing customers who haven't purchased from you recently. This segment isn't looking out actively to switch to an alternative, but failing to engage them can cost you well. So, analyze the customer purchase history and induce them to make a purchase as soon as possible. An increasing number of lapsing customers could mean an increase in your churn rate, as well.  

Newbies 

This segment comprises potential customers who have recently started purchasing from you. You need to invest in them over a period of time so that they become brand loyalists. This is by far an important segment that has the potential to augment the customer lifetime. However, you need to pay close monitoring to this segment to prevent lapses after a couple of recent purchases.  

Needs Attention 

This segment consists of customers who are planning on switching to alternatives for a variety of reasons. To prevent them from severing business relations with your brand, air a marketing strategy by scrutinizing customer behaviour with hyper-personalization in communication. This will have the power to reinstate the lost trust and loyalty in your brand. 

Loyal Customers 

As the heading suggests, your loyal customers are those who hold your brand in high esteem and exhibit that judgment in their consistent purchases. This segment buckets the ideal customer that every brand dreams of generating.  

Digging deeper into their psychology, you'll understand those loyal customers are happy with your products and services. You can engage in direct marketing campaigns with this segment and make them feel valued.  

Potential Loyalist  

The potential loyalist segment hosts high-spending customers. But they need to feel valued by your brand to become your ambassador. While already they bring significant business revenue, nurturing them further will enable them to contribute further. 

High-Value Customers 

These are customers you can't afford to lose. They need consistent attention. For, though they are regular shoppers they hold a risk of switching. So, as with the potential loyalists, help them feel valued to continue doing business with you.  

Brand Advocates  

Champions are your dream customers, your most valued shoppers! 

They are the ones who have the highest RFM index - 555. They account for the most recent, and frequent purchases, and not to forget, a high basket value, every time! They also indulge in word-of-mouth marketing for your brand amongst their family and friends. Treat them with care for they are your most profitable customers.  

Create Direct Marketing Campaigns For Your Customer Segment 

Now that you have categorized your customer base using the most effective customer behavior segmentation technique - RFM analysis, it's time to put the knowledge to investment. Based on the distinct customer segment, decide if you need to improve the customer experience, or build lifecycle customer journeys, or run marketing campaigns to increase the average purchase rate for which segment.