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ERFM. Or how to boost return by coupling email engagement tracking with RFM scoring

Making the effectiveness of your email channel match audience expectations as well as company objectives is no easy task. That's why marketers are looking for manageable ways to make email marketing more relevant, timelier and more attuned to the recipient's stage in the customer lifecycle.

By combining proven segmentation methods with available online data knowledge, email segmentation can look much smarter. And ERFM — short for Engagement-RFM — is a solid methodology to do so.

Why do you need this ERFM?
Combining behavioral data and RFM scoring (Recency, Frequency, Monetary value) creates Engagement-RFM (ERFM). By doing so, you can improve the accuracy of email segmentation, strengthen engagement and lead to an increased ROI.

RFM already uses transactional behavior to predict future purchases. ERFM adds the extra dimension of email engagement, online behavior and contact frequency, to predict those future actions. ERFM is used to define the stages within the customer lifecycle and can help predict movement from one stage to another. Each of your customers or opt-in contacts can be positioned somewhere on the lifecycle.

Traditional RFM-scoring is based on transactional segmentation: customers who bought recently are more likely to purchase again (compared to customers who haven't). This also applies to customers who bought frequently. Simply put: the most valuable customers have the tendency to become even more valuable along the way.

Combining transactional value with behavioral insights, can move your email communication up to a whole new engagement level. Building rules around user activity and particular segments allows you to send specific (automated) campaigns and targeted messaging.

How do you segment?
The number and complexity of segments is governed by ROI: if a segment and segment messaging is not producing financial return, there's one rule: don't use it.

Start at the most valuable stage: if you're in e-business, contacts who abandon baskets have the highest direct value potential of all prospects. Define goals in the conversion funnel: this allows to score contacts with key intent and to follow up this segment with targeted messaging.

When customers start showing defection, it is important to keep sending emails. But that rule only applies to contacts who are still influenced. By using transactional RFM scoring, you could decide to reduce marketing activity. However ERFM can show if these contacts are still reading the emails and what content on the website they are interested in. Though that customer segment may not have purchased in a while, this type of behavior shows they are still engaged and therefore have a huge potential to purchase in the future.

This kind of behavior-based campaigns allows you to move away from regular campaign activity. Simply by sending less email to people who don't want them and more to people who do. And by communicating more frequently with audience segments with the highest revenue potential.

How to combine the multi-channel data?
Transactional data, website data, email response data, offline data, social data, CIC data: storing and combining all this knowledge to reach a real-time single customer view is complex and expensive. And it's often a show-stopper.

So it's better to act smart and start with the essentials: combine your transactional RFM data with the key email engagement metrics.

This way you can start segmentation in a manageable way and increase revenue per email.

 

Conclusion

ERFM allows you to determine the correct frequency of communication for each customer. It also helps you de?ne the customers' stage in the customer lifecycle and how to bring them to the next one, boost customer engagement and increase the financial lifetime value of your email database.

Posted on
Jun 20, 2014