What Is RFM?

This method gives customers scores based on 3 factors:

• Recency: Recency refers to how recent a customer's last purchase was. Customers who have made a recent purchase, typically within the last few weeks, still have the product and brand on their minds and are most likely to make a repeat purchase. You can measure recency however you deem necessary for your business. However, it's important to note that some companies might not have customers ordering every few days, weeks, or even months. For example, a car company might sell a single car to an individual within ten years.
• Frequency: Frequency is how often the customer makes purchases, which can help you identify repeat customers. For example, many clients make frequent repeat purchases within a set timeframe. Frequency is essential in determining the individuals most likely to continue shopping with your brand after their first initial purchase.
• Monetary value: Monetary value refers to how much a customer spends within a given period. It's always important to consider because it can tell you a few things about consumer behavior. For example, you might find that customers with the highest monetary value don't purchase items as frequently as others but typically buy the most expensive products when they do.

The values of each factor allow businesses to provide objective analysis and determine which audience to target for the most effective advertising and marketing campaigns. Most companies use a scale between 1 to 5, but you can use any values you think are necessary and helpful in evaluating clients.

What's the purpose of RFM analysis?

RFM aims to help businesses identify their target audiences by telling them who the most valuable customers are to the company. With RFM analysis, you can determine what percentage of your customers support the business and leverage this information to develop more effective marketing campaigns while boosting brand loyalty and increasing conversions as customers move along the customer journey.

Predicting future customer behavior through RFM analysis can help businesses understand how likely customers will purchase another product or service and how much they will spend. But, of course, after further research, you may find that your company is supported by only a small percentage of its clients, and those are the individuals who should become your primary target audience.

For example, you can improve your email marketing success rates with RFM analysis by understanding your target audience. Then, you can effectively segment them to send personalized emails and offers that are most likely to convert, leading to increased retention rates, customer satisfaction, and sales.

Pros and cons of RFM analysis

RFM is a cost-effective way to analyze the value of your customers, offering these significant benefits:

• Create successful campaigns. The RFM model can help you create more successful marketing campaigns to boost conversions. Because it tells businesses who their target audience should be based on recency, frequency, and monetary values. Knowing your target audience lets you spend your marketing dollars wisely because it means only advertising or marketing to those who are already interested in your products or services.
• Retain at-risk clients. RFM analysis can help you effectively retain at-risk clients by understanding their purchasing behavior and how it impacts your business. It allows you to identify at-risk customers and take action at the right time to bring them back to your business.
• Boost engagement. RFM can increase engagement and customer loyalty by allowing you to market to them with more personalized messages. In addition, RFM marketing enables you to create new opportunities to improve the relevancy of your messages based on past purchases and other buying behaviors.
• Effectively use marketing resources. Every small business should aim to decrease its marketing spending while increasing its success. Unfortunately, they can only do that with the right data. RFM helps you identify your best customers, allowing you to segment them based on their rankings to create more effective and personalized marketing campaigns that reduce overall spending.

While the RFM method is effective, it shouldn't be used as the only method for ranking and analyzing the value of your customers. RFM doesn't consider other valuable information about consumers, including the type of item purchased, past marketing campaign effectiveness, and demographics, like age, sex, and location. In addition, since RFM uses historical data, it can't tell you about current customers and may be unable to predict future behavior.

RFM examples

RFM offers a simple method for evaluating your customers. First, you need a spreadsheet with columns for customer IDs and RFM scores. However, if you've never scored your customers before, the process might be confusing, so here are a few examples to get you started if you decide to rank customers using the values 1 through 5.

Recency examples

Recency refers to how recently a customer made a purchase within a designated period. Individuals who purchased a product or service most recently would receive a score of 5.

For example, let's say you're comparing 2 customers:

• Customer A purchased a product yesterday.
• Customer B bought a product last week.

In this case, customer A would receive a 5, while customer B would likely receive a 4 or 3, depending on how recently other customers have made a purchase.

Frequency examples

Frequency refers to how often a customer shops during a specific period and can effectively measure customer loyalty. As you likely already know, loyal customers are more cost-effective to retain than new customers are to acquire. For example, if customer A makes 2 purchases in a month and customer B makes 8 purchases in the same period, customer B would score higher in the frequency column.

Monetary value examples

Monetary value is often one of the most important RFM factors for businesses because you may have clients who don't purchase very often but make larger purchases when they do. Some industries may also experience low recency and frequency but high monetary value scores depending on consumer behavior.

For example, consumers don't need to purchase a new car every year, so the auto industry typically focuses most on monetary value instead of frequency or recency. Assigning scores for monetary value can help you identify your highest paying customers, which may be the most valuable to your business even if they don't purchase products often.

Again, let's consider customer A and customer B. Customer A spends $5,000 on your website in a month for 2 products. Meanwhile, customer B only spends $2,000 for 8 products. In this example, customer A would receive a higher score for monetary value.

Looking at the examples for all the RFM factors: even though customer A doesn't purchase as frequently as customer B, they still bring more value, ultimately becoming the target audience. While customer B is more loyal, they're part of another segment.

Calculating RFM

Calculating RFM is easy, and anyone can do it as long as they have access to sales data. Again, you'll need columns for customer IDs and each RFM factor. Here are the steps for calculating RFM:

1. Scoring

Every customer will receive a score between 1 through 5 for each of the 3 categories. Therefore, your target audience will be the customers that score the highest when combining their points.

2. Analysis

After determining your scoring method, you can review your customer relationship management software (CRM) and sales data to score each customer individually in every category. Then, to get their final value, you'll add their combined scores to help you determine which customers are your target audience. You can segment clients with lower scores and market to them differently.

3. Improve customer communications

Your RFM analysis will provide information about your top customers, allowing you to prioritize them in your marketing strategy and offer personalized campaigns to entice them to make repeat purchases.

Using RFM at your business

Using RFM as part of your marketing strategy can help you identify your top customers and find new ways to market to them based on their buying behaviors. Segmentation is crucial to improving engagement and increasing conversions for any business, regardless of size. With RFM, you can improve your marketing efforts throughout every stage of the customer journey and even personalize transactional emails to build loyalty.

Mailchimp makes it easy to understand your customers with our audience dashboard. Plus, you can use the RFM model to build targeted, personalized email campaigns by segmenting customers. Ready to improve your engagement rates? Try Mailchimp's email marketing platform to target the right customers at the right time.