You may be familiar with the 80/20 principle, where 80% of results come from 20% of the causes. When you apply this to your customers, you should find that the largest portion of revenue comes from a small group of customers. So, it follows that your customer service and marketing efforts have to focus on these top generating customers, right?
Perhaps. When we apply this principle to customers and only evaluate revenue, we’re missing big pieces of the picture. There are other means by which the value of a customer needs to be determined.
Not only that, what happens if you place all your eggs in one basket only for that basket to drop? Focusing on a single customer group based on revenue is a unidimensional way of looking at your audience.
Instead, consider another way to prioritize your best customers so that you can focus on them and keep them happy. RFM analysis is a great way to organize your customer segments and find your top customers along three dimensions.
You can apply RFM analysis to segment your email list, offer enhanced services to customers, and personalize your communication. Let’s dive deeper and look at what RFM analysis is and how to leverage it.
Recency, Frequency, and Monetary Value Analysis
RFM or recency, frequency, and monetary analysis is a popular and helpful way to group your customers.
Recency considers how recently a customer made a purchase. Recent customers have your business fresh in their minds and are better targets for your marketing efforts.
Frequency is all about identifying those customers who purchase often from you. It’s obvious that customers who buy from you frequently are good recipients for email marketing and other marketing strategies.
Monetary value takes a customer’s purchasing power and intent to buy into account. Customers who make large purchases are ones you can’t afford to lose. Knowing who they are and engaging them is vital to help your business thrive.
RFM analysis gives us a helpful lens through which we can segment and target our customers with appropriate marketing techniques.
One of the reasons why this analysis is so useful is because it is multidimensional. By combining the three elements of the RFM analysis, you have several ways to create customer segments. You’ll be able to prioritize your top customers according to varying dimensions.
Applying RFM analysis to customer segmentation
The most common application for this type of analysis is in email segmentation. When you can divide your email list into segments, you’ll be able to create more personalized content. And the more personalized and relevant content you create, the better your chances are of increasing purchases.
Here’s a helpful image by Oracle that shows how RFM can be applied to customer segmentation in a two-dimensional graphic.
Customers who are at the top of all the three dimensions of the RFM framework are manifestly important to a business. But it’s also likely that they form a small group and you’ll still need to focus on other customers in different ways. Let’s breakdown a few ways to approach the results of your RFM analysis.
Offer loyalty rewards
When you identify your top buyers, you can reward them and make them feel special by offering loyalty rewards. Customers will associate buying from other businesses as a form of loss because they’ll miss out on the benefits of your loyalty program.
Avoid customers that are low on the RFM scale
Every business gets subscribers and customers who make a single purchase and then never interact with the business again. They may have signed up out of curiosity or for a purpose that isn’t relevant anymore. In such cases, you’re better off not sending them emails since you’re not in their recent memory. You’ll avoid getting marked as spam or annoying the customer.
Offer discounts and deals to trigger more purchases
The customers who buy from you frequently are more likely to be receptive to your email communication. You can send them information about discounts, deals, and other future products. In this way, you could encourage more buying behavior and increase customer satisfaction levels.
Pay attention to ‘average’ customers
Carrying out an RFM analysis will highlight customers whom you need to pay attention to. Infrequent buyers or those who buy low-value items can be targeted with special offers. You can highlight a risk-free purchase or a guaranteed money-back offer to the low money spenders. And you can send attractive deals to infrequent buyers. Sending timely and personalized content to such groups can increase their value to your business.
Using RFM analysis will allow you to make numerous segments along the dimensions of recency, frequency, and monetary value. You’ll target different segments with the right message and know whom to avoid.
RFM analysis tools and platforms
It’s likely that you already have all the data you need to do an RFM analysis. Google analytics and CRM platforms will help you collect and analyze data on your users’ behavior. Your eCommerce platform will have reports on purchase behaviors too.
You can use a simple excel spreadsheet to calculate your RFM analysis.
There are also 360-degree marketing campaigns that include RFM analysis as part of the marketing dashboard. You’ll be able to use reports and data from your CRM, email marketing analytics, sales history, and more to generate an RFM report.
One of the positive aspects of using this type of analysis is that it’s straightforward and it’s applications to email segmentation are self-evident. It’s an interesting framework that guides and organizes your email marketing.
Conclusion
We’ve just looked at some helpful information about RFM analysis and how it can help you group your customers based on certain factors. Data on recency, frequency, and monetary value are easy to get and are very likely things that you already track.
You can apply it to great effect in your email marketing campaigns by creating personalized email content for different segments. You’ll reward your most valuable customers, rouse the ones who have potential, and either abandon or create marketing campaigns to compel currently low-value customers to buy more.
A word of caution though. Be sure not to market too much to high-value customers or to neglect other customers entirely. With data, testing, and a framework to rely on, you’ll be able to make the best of the customers you already have.
