Understanding RFM Segmentation: The Key to Targeting High-Value Customers in a Turbulent Market

Are you struggling to identify patterns and trends in your customers' buying behaviors? Do you want to know which customers are most valuable and when they're losing interest? The current economic climate is making it harder than ever to gain and retain customers. This is where customer segmentation comes in.

In this blog, we explore the concept of RFM segmentation, a powerful approach to customer segmentation that can be quickly developed to provide insights sooner rather than later. We explain why it's important to segment your customers, what RFM segmentation is, and how it can help you stand out. Finally, we show you how to put RFM segmentation into action and track your results.

?“The current economic climate” has recently been the subject of many articles. Some experts are convinced that it’s nothing more than nervousness in response to global events, while others will lead you to believe that we are on the precipice of another recession.

?Nevertheless, we can all agree that customer behaviors are continuing to evolve and that is not going to change anytime soon.

?As organizations tighten their belts to prepare for whatever the economic situation brings next, it is more important than ever that they are strategic in their efforts to gain new customers and prevent existing customers from churning. One answer: segmentation.

Customer segmentation doesn’t have to be complicated to provide value to decision-making, but without the understanding of your customers that it can provide, developing your marketing or merchandising strategy might feel like you’re playing darts blindfolded.

Why Segment Your Customers?

Each customer is unique, but you can begin identifying patterns and trends by segmenting customers into groups based on their buying behaviors. You can answer questions such as:

• Did my recent campaign improve customer loyalty?
• What are my highest-value customers searching for on my site?
• When are customers losing interest?
• Which customers should be targeted with our next promotion?

?It is easier to confidently make strategic decisions by considering the mannerisms of customer segments rather than attempting to navigate the activities of each customer individually.

RFM (recency/frequency/monetary value) segmentation is an approach that will enable you to identify high-value customers and trends in customer purchasing behaviors and one that can be quickly developed to provide insights sooner rather than later.

What is RFM Segmentation?

RFM segmentation is not a new concept in marketing, but it’s an undervalued one. It relies on three elements:

• Recency: When was the last time the customer made a purchase? This is usually measured in days-since relative to when the segmentation is executed.
• Frequency: In a given time frame—which can be year-to-date, month-to-date, the past 12 months, or all time—how many orders did the customer place?
• Monetary Value: What is the financial value of this customer?

How RFM Segmentation Stands Out

RFM segmentation is one of many approaches to customer segmentation, some of which are simpler while others are highly complex. RFM segmentation falls somewhere in the middle of that spectrum and stands out for three reasons:

1. You already have the data! One of the most significant advantages of this approach is that it relies on data you already have: customer transactions.
2. Quick implementation. Because RFM segmentation does not rely on advanced machine learning, it can be established and implemented quickly and with a fraction of the resources.
3. Maximum customization. Nothing about this model is set in stone. Each element is customizable to meet your business’s needs.

RFM Segmentation is Tailored to Fit

Let’s talk more about customization. There are several out-of-the-box segmentation solutions on the market today, but where many of them fall flat is customization. As aforementioned, this is one of the most significant advantages of RFM segmentation and, therefore, a missed opportunity to overlook.

?Customization can look like adjusting the measurement of one of the three keys of the model. For example, you might measure a customer’s recency in weeks rather than days or their monetary value in average purchase amount rather than lifetime spending. It could be valuable to consider additional factors, such as whether a customer has already signed up for a loyalty program, proximity to your location, or how long a customer has been making purchases. These variables can easily be incorporated into an RFM approach.

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Understanding Your Customers for RFM Segmentation

After your parameters have been refined, the next step is defining your segments—again, this is an opportunity to tailor this approach to fit your business.

?Popular segments used in the industry include:

• ?Champions: These are your highest value, most loyal customers.
• Hibernating: These shoppers used to be regulars, but their activity has recently stagnated.
• Promising: They recently made a purchase but aren’t as engaged as other buyers yet.

?However, this is a case where once again, the “right” approach is the one that suits your business. If you have incorporated additional information, you might have segments like these:

• ?Disengaged Big Spenders: These customers have made one or more major purchases but have not signed up for the loyalty program or interacted with marketing materials.
• Loyal Trekkers: These customers don’t shop as frequently as those who live nearby, but they are loyal buyers who might need an extra nudge to make the trip.
• Infrequent but Engaged: These shoppers shop very infrequently and make small purchases when they do, but they have been returning reliably to your shop for 3+ years.

Putting RFM Segmentation in Action

Finally, when the model is established and the segments defined, the final step is putting this segmentation model into action. Although there is quite a bit you can learn from applying segmentation to a snapshot of your audience, its maximum value comes when it is launched into production.

What putting your model into production looks like will depend on your company’s current tech stack and existing analytics solutions. Your implementation should include a way to visualize and compare key performance indicators for each segment over time.

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Visualize KPI performance with the results of your RFM segmentation model so that you can capture the most important insights.

The latter is crucial. Implementing your new segmentation model in a way that can be regularly updated and your results visualized enables your business to monitor the health of your customer base by tracking movement between the segments. Are customers coming out of hibernation and becoming loyal shoppers? That’s great marketing! Are loyal customers churning suddenly? Time for an intervention! And, speaking of interventions, those can be strategically planned and targeted, too.

For example, if you notice a segment of customers routinely browses your site but is slow to make a purchase, you might test the effectiveness of sending them a discount code the next day. This is an example of an intervention to increase the lifetime value (LTV) of customers belonging to a specific segment. Other interventions could be targeted at moving customers from a segment with a lower LTV to a higher LTV. For example, you could target new customers that demonstrate promise with messaging to convert them to loyal champions of your brand.

The bottom line is that whether you have 100 customers or 100,000, segmentation is a great way to get to know them better. Out-of-the-box segmentation software might be tempting, but it lacks adaptability. No two businesses are exactly the same and their customers aren’t either.?

Regardless of whether your organization has used analytics, RFM segmentation can be implemented from scratch quickly and efficiently to provide near-immediate insights. It can be a long-term value add or just the beginning of your relationship with your data before delving into advanced techniques.

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Talk to an expert about your customer segmentation needs.

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This blog was written by Meg Malone-Hallberg, a data and analytics consultant at Analytics8. For more blogs like this, visit www.analytics8.com.