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What Is ERFM?

what-is-erfm?

The e-commerce industry, expected to reach a staggering $7.4 trillion by 2025, is experiencing unprecedented growth, driven by advancements in technology, the widespread adoption of mobile devices, and the influence of social media on consumer behavior, with ERFM modeling playing a critical role in understanding and predicting customer trends, thereby reshaping the global economy and revolutionizing the way we shop.

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 amount of 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: Measures customer interaction with the brand through channels like 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 better understand their customers, identify high-value segments, and prioritize resources.

Segmentation is 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 a customer is genuinely engaged with your marketing efforts, you need to measure their engagement and interaction with your brand. That's where eRFM comes in.

ERFM is the next level of RFM. As well as measuring past purchases' recency, frequency, and monetary value, our new customer modeling tool also looks at engagements like email opens and online activity. This means that you can segment customers based on their recent interactions with your brand and their past purchase behavior.

Each RFM persona receives an engagement score, so you can identify customers primed for conversion and those who need to be re-engaged.

Daily data syncing means that your segments will always remain up-to-date. As customer behaviors change, so will your components. Identifying critical moments in the customer journey is now easier than ever; 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 haven't made a purchase.
  2. Inactive: customers who have not purchased in a long time.
  3. Need nurturing: customers who 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 a lot of 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 a total of 28 audience groups to choose from when building your segments.

How to use ERFM segments

With 28 segments to build, the possibilities are endless. Each customer can receive highly personalized and relevant messages depending on their journey stagthey're are a couple of ways to add eRFM segments into your day-to-day marketing automation strategy.

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 yet to make a 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 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 eRFM modeling, online behaviors are tracked, so you can 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 froThey'veut for whatever reason; you just haven’t seen them in a while. Ouhaven'tmodel makes it easy for you to identify inactive customers who are 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 come back into 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 be retargeting these shoppers with personalized product recommendations or exclusive offers. Product recommendations are proven to increase average order value, so they are crucial for customers at this stage in their journey.

5. Drive repeat purchases from existing customers

Retaining existing customers is 5x cheaper than acquiring new ones. To tap into brand-new revenue opportunities, eRFM can surface customers showing signs of making a second purchase.

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 time and time.

6. Maintain loyal customer engagement

Your most loyal customers are typically low maintenance. You’ve already done the hard worYou'veing them why you should be their go-to brand. They trust you, and because of that, they’re happy to be advocates fothey'rebrand. 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 keep engagement levels high. This is the perfect segment to target with requests to complete focus group surveys. As well as maintaining engagement, you can create a stronger relationship because these customers will feel directly connected to your brand.

Adding eRFM to your segmentation strategy

ERFM segments are based on customer behaviors. For those marketers struggling to implement an effective segmentation strategy because of insufficient customer data, eRFM is the solution you didn’t know you were waiting for didn't pull data hiding in plain sight. There’s no need for extensive daThere'snsing or laborious preference collection. We use insights from your ecommerce platform to help you discover opportunities waiting to be turned into revenue-generating moments.

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