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Driving Better Marketing Results with RFM Analysis

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Marketing campaigns can often be expensive, time consuming, and worst of all, ineffective. Too many businesses waste valuable resources advertising to customers who are unlikely to respond. If it is true that 80% of sales come from 20% of customers, then how can marketing efforts be tailored to most effectively reach the right audience?

Recency, Frequency, and Monetary

One of the most popular ways to achieve this is through RFM analysis. This technique segments customers based on three factors: Recency, Frequency, and Monetary value. Ordered by their importance, recency is the most significant predictor of whether a customer will return. The more recently they have made a purchase, the more likely they will again. Frequency is also very important. Customers who purchase from you often will likely continue to do so is satisfied. Finally, the amount a customer spends on each transaction can predict future purchases, too. Those who spend more are more likely to return than those who spend less.

Scoring Your Customers

Recency, Frequency, and Monetary

Customers can be assigned a score (usually 1-5) based on segments from each of these factors. The best customers are those who have a low RFM value, and it can be safely assumed that they will respond to future offers. Customers with high RFM values, however, are the least likely to respond to marketing promotions or to make any new purchases. Depending on how you segment and score your customers with RFM the high and low scores can be reversed but the outcome is the same helping you identify your best customers based on these metrics.

RFM scores can also reveal more nuanced data. For instance, new customers might have better scores for recency and monetary value, but will score poorly on frequency. Businesses can identify these first time purchasers separately and should offer deals to these customers that will encourage them to return. Customers who have scored well on frequency but have poor recency scores are those who previously made regular purchases but now no longer do. These customers should also be enticed back, or be analyzed further to understand what is making them take their business elsewhere.

Related: The Case for eCommerce CRM for B2C

Understanding Lifetime Value of a Customer (LTV)

RFM Analysis

Knowing how to interpret a customer’s total RFM score will give a business a better understanding of their Lifetime Value of a Customer. LTV (also known as CLTV) is a more general technique used to predict customer value and response to marketing overall. It can be calculated relatively, such as how likely a customer is to respond to a certain promotion or ad campaign, or absolutely, which looks at a customer’s overall likelihood for repeat business.

Using RFM along with LTV will give businesses access to a greater amount of data and allow them to generate a more complete picture of their customers’ needs. Marketing campaigns can be broken down based on different RFM scores, allowing businesses to see their effectiveness across a wide segment of their customers. Additionally, different RFM factors can help businesses calculate a customer’s absolute LTV much more accurately.

Related: Infographic: A Visual Introduction to Customer Lifetime Value

How your CRM will help with RFM Analysis

RFM Analysis

OroCRM allows marketers to define and customize different RFM metrics for each business channel and use them, along with other data (such as income level, gender, purchase history or even browsing behaviors), to find out their customers’ real value and intelligently tailor their marketing campaigns. Different segments can be created based on RFM scores, such as Most Active Customers or Top Grossing Customers, to quickly identify groups with unique messaging needs. The RFM score is then clearly displayed for sales and marketing teams on a customer account, and can also be used to generate useful reports and segments, identify potential opportunities and leverage connected marketing automation tools such as MailChimp or dotMailer to send these customers highly targeted relevant offers. And, because no two channels or stores are 100% identical, businesses can set up and configure different RFMs per platform, marketplace, website, and more for complete flexibility.

Using RFM analytics to better understand and improve customer loyalty can have dramatic results. Research firm Deloitte reported that improving customer loyalty by only 5 percent can increase lifetime profits per customer by as much as 95 percent. Put simply, being able to personalize marketing efforts based on real and actionable data will drive more sales.

Learn more about OROCRM

OroCRM can help your business more effectively reach your customers by targeting the right customers utilizing these methods and many more. Demac Media has partnered with OroCRM to deliver customized solutions to meet the changing commerce landscape. Contact us today to learn more about how OroCRM can benefit your business.

Related: What is OROCRM?

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