What Is ERFM?

The ecommerce industry is projected to reach an astonishing $7.4 trillion by 2025.

Advancements in technology, such as the widespread use of mobile devices and the impact of social media on consumer behavior, fuel this growth. Moreover, ERFM modeling is essential for understanding and predicting customer trends, transforming the global economy, and revolutionizing the shopping experience.

ERFM (Extended RFM) is a customer segmentation model used by e-commerce brands and marketers to understand and analyze customer behavior. It is an extension of the traditional RFM (Recency, Frequency, Monetary) model, which is based on three main attributes:

1. Recency: The time since the customer’s last purchase or interaction.
2. Frequency: The number of purchases or exchanges the customer has had over a specific period.
3. Monetary: The total money the customer has spent on purchases.

ERFM extends the RFM model by incorporating additional attributes relevant to e-commerce businesses, providing a more comprehensive view of customer behavior. Some of these other attributes include:

1. Engagement: This measures customer interaction with the brand through social media, email, and website visits.
2. Product Category or Preferences: Reflects the customer’s preferences for specific products or product categories, which can help brands tailor their marketing and promotional activities.
3. Channel Preference: Determines the customer’s preferred channel for communication and transactions (e.g., email, social media, or website).

By segmenting customers based on these attributes, e-commerce brands can create targeted marketing campaigns, improve customer retention, and increase overall customer lifetime value (CLV). ERFM allows businesses to understand their customers better, identify high-value segments, and prioritize resources.

Segmentation is a well-established tactic marketers use to improve the relevancy of their marketing. Using customer data such as gender, location, interests, and dislikes, you can group audiences based on their similar traits.

Customer engagement models like RFM enable marketers to segment audiences more sophisticatedly. Using insights such as the recency, frequency, and monetary value of past purchases (RFM) allows you to identify customers with the highest potential. But how do you know whether these shoppers are genuinely engaged?

ERFM: The Future of Segmentation

To determine whether customers genuinely engage with your marketing efforts, you must measure their engagement and interaction with your brand. That’s where eRFM comes in.

ERFM is the next level of RFM. In addition to measuring past purchases’ recency, frequency, and monetary value, our new customer modeling tool examines engagements like email opens and online activity. Thus, you can segment customers based on their recent interactions with your brand and past purchase behavior.

Each RFM persona receives an engagement score, which helps you identify customers primed for conversion and those needing re-engagement.

Daily data syncing ensures that your segments remain up-to-date. As customer behaviors change, so will your components. Identifying critical moments in the customer journey is now easier than ever, and you’ll never miss an opportunity to convert customers again.

Creating eRFM segments

RFM modeling creates seven personas that can be made into audience segments:

1. Non-customers: potential customers who have subscribed to your newsletter but have yet to make a purchase.
2. Inactive: customers who last purchased a long time ago.
3. Need nurturing: customers are about to fall into the ‘inactive’ segment.
4. High value: customers who have spent much with you but have not shopped recently.
5. Recent: shoppers who have been actively purchasing from you.
6. Loyal: customers who shop with you frequently.
7. Champions: shoppers who frequently spend much money with your brand.

With the addition of engagement insights, these personas are broken down further into four categories:

1. Lightly engaged
2. Engaged
3. Highly engaged
4. Most Engaged

This gives you 28 audience groups to choose from when building your segments.

How to use ERFM segments

With 28 segments to build, the possibilities are endless. Customers can receive highly personalized and relevant messages depending on their journey stage. Add eRFM segments to your day-to-day marketing automation strategy in several ways.

1. Greet new website visitors

New customers are essential for growth. A strong pipeline of potential customers can guarantee your business’s future revenue. With more consumers shopping online than ever, you must identify those who have yet to purchase to target them accordingly.

Traditional RFM modeling doesn’t account for prospective doesn’t express interest in your brand. AFM allows you to target new subscribers who are browsing your website for the first time. You can identify and enroll these non-customers in welcome or nurture programs to highlight your brand’s USPs.

2. Discover critical brand purchase intent

We know that shoppers today browse multiple bands before they’re ready to make a purchase. Competition online means you’re fighting for more and more of you’re attending.

Using AFM modeling, online behaviors are tracked to quickly identify shoppers who look ready to convert for the first time. Applying this to segment builder means you can deliver relevant and timely content that will help tip them over the edge. This is the perfect time to send readers information about your shipping or returns policy.

3. Re-engage inactive customers

Inactive customers can be a huge source of opportunity. They’ve previously purchased from you for whatever reason; you just haven’t seen them. Ouhaven’tmodel makes it easy to identify inactive customers showing signs of re-engaging with your brand.

You can target this segment with a timely win-back campaign that reminds them of your brand’s values or offers them a brand code on their next purchase. This may be the incentive they need to return to the fold.

4. Identify customers with active carts

Customers add items to their baskets for many reasons, but one thing is sure: they’re considering purchasing their products. Maximize these clear signs of intent by acting quickly to close the sale.

When your eRFM model surfaces customers with an active cart, you should retarget these shoppers with personalized product recommendations or exclusive offers. Product recommendations are proven to increase average order value, which is crucial for customers at this stage.

5. Drive repeat purchases from existing customers

Retaining existing customers is five times cheaper than acquiring new ones. AFM can surface customers showing signs of making a second purchase to tap into brand-new revenue opportunities.

You can use this clear intent to purchase to highlight unique aspects of your customer experience, such as your loyalty program. Collecting points per purchase or unlocking special rewards can drive shoppers to return repeatedly.

6. Maintain loyal customer engagement

Your most loyal customers are typically low-maintenance. You’ve already done the hard work of convincing them why you should be their go-to brand. They trust you, and because of that, they’re happy to be advocates for your brand. But what do you do when their engagement starts to wane?

Creating a segment based on this eRFM persona allows you to enroll these shoppers in a customer care automation program to maintain high engagement levels. This is the perfect segment to target with requests to complete focus group surveys. In addition to maintaining engagement, you can strengthen your relationship with these customers because they will feel directly connected to your brand.

Adding eRFM to your segmentation strategy

ERFM segments are based on customer behaviors. For marketers struggling to implement an effective segmentation strategy due to insufficient customer data, eRFM offers a solution you may have yet to consider. It helps uncover data hiding in plain sight, eliminating the need for extensive data cleansing or laborious preference collection. By using insights from your e-commerce platform, we can help you discover opportunities that can be transformed into revenue-generating moments.