What is RFM segmentation?

Different types of customers require different approaches to gaining and retaining their loyalty; a brand evangelist (a loyal customer who passionately promotes and advocates for a particular brand, product, or company) shouldn’t be targeted in the same way as a customer who made one purchase in the last three years.

Creating a loyal base of customers and keeping them coming back through customer retention strategies can have a positive impact on your business’s bottom line. In fact, the probability of selling to an existing customer can be up to 65% higher compared to selling to a new customer. This is where a framework for analyzing customers like RFM segmentation comes in.

What is RFM segmentation?

RMF segmentation is used to analyze customer behavior based on three different factors: recency, frequency, and monetary value. Businesses use this segmented analysis to create targeted marketing campaigns that specifically address certain market segments.

In this blog, we’ll take a closer look at how RFM segmentation works and the many ways it can be beneficial for businesses in the world of eCommerce.

History of RFM analysis

RFM analysis originally started in the direct mail industry, by analyzing data regarding customers’ past purchases and behavior, which marketers could then use to determine how likely a customer was to respond to a specific offer.

Over time, RFM analysis has evolved and is used in various contexts like ecommerce, customer retention, and loyalty programs. RFM analysis has become a powerful tool used by businesses to get insights into their customers’ behaviors.

This information can then be used to create targeted campaigns that resonate with each customer, leading to improved customer retention, increased revenue, and a more efficient allocation of resources.

RFM: Recency, Frequency, and Monetary Value

So, what is RFM? RFM describes the three different factors used to analyze customer behavior. These are:

1. Recency: How recently did a customer make a purchase? Customers who have made recent purchases are more valuable than those who haven’t.
2. Frequency: How often does a customer make purchases? Customers making more frequent purchases are more valuable than those who aren’t.
3. Monetary value: How much money does a customer typically spend? Customers who continually spend more money are more valuable than customers who spend less.

Using these three factors or RFM, businesses can not only develop a deeper understanding of their customer base’s behaviors, they can also segment their customers into groups and create better-suited marketing campaigns for each of these different segments.

A look at customer segments

Each customer segment will call for different types of action. Let's take a look at some different customer segments:

• Lost customers: Former customers that have halted purchasing your product.
• At-risk customers: Customers that are on the brink of becoming lost customers.
• Leads: Lead customers are those who have visited your site or store and left their contact information with hopes of receiving more information.
• New customers: New customers are first-time buyers.
• Promising customers: Customers that show potential to become loyal to your brand.
• Loyal customers: Loyal customers are regular buyers of your products/service.
• Champions: Champion customers are the brand evangelists, the ones sharing their positive experience with others.

By segmenting customers into these different groups, you can tailor marketing campaigns to a specific purchase behavior; using customer segmentation to identify these trends will improve sales, drive conversion rates, and improve customer satisfaction. Below you can see an example of how Patch’s retention platform segments customers into ‘buckets.’ 

RFM segmentation steps

Carrying out an RFM analysis requires you to build an RFM model, divide and select your customer groups, and then craft the customer journey. This is where retention platforms like Patch can come in and save you time and money with fully automated customer journeys. For example, birthdays and anniversaries can be great opportunities to incentivize engagement along a customer’s journey.

Customers spend more on special occasions, so by using Patch, you can automate rewards, special promotions, or personalized messages that inspire your customers to take action.   specific marketing campaigns. 

RFM model

To create an RFM model you’ll need to gather all customer data regarding past purchase history, this data will be the recency, frequency, and monetary value pertaining to each customer. Once you’ve gathered this data, you will assign each customer their RFM score.

Divide the customer segments

Now that each of your customers has a personal RFM score, you’ll divide them into their respective segments; this will be done for each of the three RFM values. Segment the customers into tier groups, with tier 1 representing the highest spenders, most frequent buyers, and most recent customers. On the other hand, tier 4 will consist of the lowest spenders, customers who made a single transaction, and those who haven't engaged with the brand recently. This means that you can not only engage with frequent buyers, but you can also resell to customers who could fall into the at-risk or lost segments.

Analyze customer segments

Analyze the customers in each segment, this helps you to understand the similarities and differences between the distinct customers. You can also start to identify your loyal customers, at-risk customers, promising customers, and champions.

Create targeted marketing campaigns

With your customers grouped into their specific segments, you can begin to create marketing campaigns that target groups based on their specific purchasing history and behaviors. With the RFM analysis you’ve gathered, you can create messaging that is tailored to customers’ behavior.

Patch’s retention tool can assist in managing various targeted marketing campaigns, such as a loyalty and rewards program. A program like this can incentivize customers to make repeat purchases and sign up for email lists. Additionally, the program can entice customers to return by offering them the opportunity to earn loyalty cash that can only be redeemed with your company.

Continue to track and improve

Track the results of your campaigns through Patch’s platform to identify what’s working with specific segments and what needs to be altered. Through segmented data analysis, Patch offers comprehensive customer insights that cover a range of factors, from demographics to buying behavior. Monitoring segmentation criteria and testing new strategies will continually improve your RFM analysis.

Below you will find some of the KPIs that you should be tracking to effectively analyze your customer segments:

• Conversion rates: The percentage of customers who take a desired action
• Number of purchases: The total number of purchases made by customers over a given period of time
• Customer lifetime value (CLV): The total amount of revenue a customer is expected to generate over their lifetime with the brand
• Retention rate: The percentage of customers who continue to make purchases from a brand over a given period of time
• Average order value (AOV): The average amount that customers spend per transaction

Benefits of RFM segmentation

Targeted marketing strategies: Identifying customer segments allows businesses to create marketing campaigns that will resonate with specific groups of customers.

Improved customer retention: When you’re able to identify your most valuable customers, you can target them with personalized offers that can improve retention rates.

Increased revenue: Personalized offers for customers will lead to increased customer  purchases and revenue.

Save money: RFM segmentation allows you to focus your marketing money on customers who are most likely to make purchases and continue to give their support. 

Competitive advantage: Businesses using RFM segmentation and analysis will ultimately be in a better position to make decisions about their customers than those businesses that aren’t. These decisions will result in increased profits and brand loyalty.

The path to smarter marketing decisions

RFM segmentation helps businesses identify valuable customers based on their buying patterns and behavior. RFM categorizes customers based on the recency of purchases, frequency of purchases, and monetary value of those purchases. Using this data, businesses can specialize their marketing campaigns to resonate more with specific buyers. 

Patch has simplified the RFM segmentation process with an all-in-one retention platform. This state-of-the-art platform uses RFM segmentation and an efficient 3-step approach to customer retention:

1. Identify the leak: Patch outlines the potential for lost revenue, or “leak” coming from at-risk customers.
2. Patch the bucket: Using RFM segmentation Patch helps create automated customer journeys, recapture lost revenue, win back lost customers, and retain brand loyalists.
3. Reinforce the patch: Patch offers a number of tools, including loyalty and win-back campaigns, abandoned cart alerts, reviews, referrals, birthdays, and more. 

Patch will guide you in dissecting the ecommerce buyer's journey and building out an ecommerce marketing machine that ensures customers remain loyal for life. Click here to schedule a demo with Patch and see how RFM segmentation can assist your business.