How do you know which customers are the most important to your e-commerce business? If you’re trying to expand your reach, constantly trying to reign in new customers might not be as effective as you hope. RFM analysis for e-commerce is a method for identifying who your customers are and what their worth is to your business.

What is RFM analysis? It started as a way for direct mail companies to organize their customers based on who would be the best candidates for different magazines. Today, it’s used by businesses across all industries to learn more about their customer behavior.

RFM stands for Recency, Frequency, and Monetary. Each of these factors ranks your customers based on their shopping history. The recency factor shows how long it’s been since a customer placed an order. Frequency shows how often they order from your store, and monetary shows the total amount they spent on your business during the time period. Typically you’ll want to pull a year’s worth or longer of your business’s customer history to receive the best results. A year gives you enough time to recognize patterns and pick customers who really stand out.

For each of these factors, you’ll want to set values to show where customers fall in the data results. For example with recency, put all customers who ordered in the last year as a 3, in the last six months as a 2, and the last month as a 1. You can add values as you see fit depending on how you want to segment your customers. Your analysis will depend on the products you offer and your price point. Customize the analysis to what suits you best. Your business might define a great customer as someone who has ordered in the last week, or someone who consistently places orders, so make sure you adjust your values to match.

Put together, these three factors tell you a lot about your customers. You’ll be able to see who your highest-spending and most frequent customers are based on the value you gave each factor. You’ll also be able to see which specific customers aren’t performing very high, and those who might be about to leave your lifecycle.

RFM analysis data can be structured in a number of different ways, so don’t think that a score of 1 in every factor is the only thing to look for. Customers who are low in frequency but high in monetary are good people to target to get them to return to your store more often. Customers who are low in both frequency and monetary are people you want to pay attention to. Think of them like red flags. These are typically people who made one purchase in their lifecycle, and you’ll want to reach out to them in an attempt to bring them back to life. If and when you do find a customer with all 1s, take note, this is a customer you’ll never want to lose.  

With RFM Analysis for E-commerce, You’ll Be Able to Dig Out the Best Hidden Opportunities for Your Business

If you have a loyal customer base already, RFM analysis shows you which customers are the most important to your business’ success. That’s who you should be focusing your time on. Don’t have a strong following yet? RFM analysis for e-commerce tells you which customers have the potential to be the start of that foundation. Instead of putting all your time marketing to new customers, engage the ones you already have to create loyal advocates to build off of.

RFM analysis can help you refocus your business on the most effective strategy for growth. Your time and your money are too valuable to spend on efforts that aren’t going to show you strong results. Even though marketing towards customers who haven’t made a purchase in a year might seem backward, you likely have a higher chance of bringing them back than pulling in enough new customers to cover your losses.

On the surface, the results from RFM analysis are just data, but you can take it one step further and use it to personalize your brand communications. If you know how your customers are behaving, you know exactly how to talk to them. Your high performing customers are already loyal to the brand, so reward them with a personalized coupon as a thank you for supporting your store.

Through the stats that you pulled out, you can also target the lowest performing customers and put together a campaign encouraging them to return to your business. Not only will this help to push them back into your funnel, but your campaign can be personalized to offer them an incentive like free shipping because you don’t want to lose their business.

RFM analysis helps you relate to your customers on a personal level. Your brand will seem less like a static figure, and more like a person behind the screen which will help people feel more connected and engaged.