Donor Segmentation: Understanding the RFM Approach

Tim Paris – 6 August 2021

Donor segmentation is the process of sorting your donors into groups based on shared demographic characteristics and previous engagement metrics, and it’s a fundamental strategy for nonprofits. It helps you better target your outreach, raise more donations, and grow your relationships with donors over time. But how do you get started?

For most organizations, RFM segmentation (based on Recency, Frequency, and Monetary Value metrics) is the easiest and most immediately useful way to start segmenting the donors in their database.

If you want to increase appeal response rates and average gift sizes, we’ve got you covered. This guide will help you understand and conduct RFM segmentation for your nonprofit. Here’s what we’ll cover:

Learn how AI takes all the guesswork out of donor segmentation.

Understanding the Basics

The Importance of Donor Segmentation

Segmenting your donors is important because it allows you to target your messages to the specific audiences who’ll be most likely to take actionin other words, it helps you communicate and fundraise more efficiently. Smart segmentation can save your organization time and money while boosting fundraising returns.

But how do you know which of all your fundraising and engagement metrics to use when creating donor segments? It can get tricky, which is why nonprofits rely on the fundamental RFM segmentation approach to get started.

What is RFM Segmentation?

RFM (or RFV) stands for Recency, Frequency, and Monetary Value. They are three basic characteristics of every donor journey. Here’s what they mean:

  • Recency: Has the donor given recently? When was their last gift?
  • Frequency: Does the donor give often? How many times do they give per year or per campaign?
  • Monetary Value: How big was the donor’s last gift?

By combining these three simple values into a single RFM ‘segment’, you can easily break up your database to see which donors are ‘good’ candidates for a particular appeal based on their giving history. For the purposes of simple segmentation for fundraising, these three metrics essentially cover your bases.

The RFM method, originally created to help retail businesses segment their customers, has been adopted by the fundraising sector as an easy way to categorize different types of donors. Today, it’s the most common approach used by nonprofits to segment their database and choose which donors should be appealed to during fundraising campaigns. Although RFM segmentation has its limitations and shouldn’t be the only way you target your appeals, it’s still a broadly useful way to better understand your donors.

How to Segment Your Donors

Here are the steps to create your own RFM segmentation groupings. You may use your CRM (e.g. Salesforce, Blackbaud Raiser’s Edge, or Microsoft Dynamics), or simply use Microsoft Excel to create your segments.

Step 1: Create the recency, frequency, and monetary fields.

The first step is to create the Recency, Frequency, and Monetary fields for every donor. The output is a table that contains 1 row for each donor with the following columns:

  • Recency: The number of days since the donor’s most recent gift
  • Frequency: The number of gifts given by the donor in the past 5 years
  • Monetary: The average size of the donor’s gifts over the past 5 years

It should look something like this:

RFM segmentation involves sorting your donors by their gift recency, frequency, and value.

Step 2: Divide each column value into tiered groups.

In the next step, we simplify this data by converting each of the R, F, and M values into one of 5 groups. To simplify things, use just 3 groups to begin with and no more than 5. To do this, convert each RFM value to a number using the guide below:

Convert to Value Recency Frequency Monetary
5 Last gift in past 6 months 5+ gifts in past 5 years Average gift size >$500
4 Last gift in past 12 months 4 gifts in past 5 years Average gift size >$100
3 Last gift in past 24 months 3 gifts in past 5 years Average gift size >$50
2 Last gift in past 48 months 2 gifts in past 5 years Average gift size >$20
1 Last gift greater than 48 months ago 0 or 1 gift in past 5 years Average gift size <$20

Your table should now look something like this:

Your donor segments should begin taking shape based on each individual's unique mix of RFM values.

Remember, each donor should now have three separate scores next to their name (i.e. a score for recency, a score for frequency, and a score for monetary value).

Step 3: Label your RFM groups.

The third step is to select groups of donors who will be targeted in your fundraising campaigns. It is helpful to assign names to segments of interest. Here is an example of what that will look like for charities:

  • Best Donors: This group consists of those customers who are in the highest group for R, F, and M, meaning that they have given the most recently, the most frequently, and the highest amounts. A shorthand for this segment is 5-5-5.
  • New, High-Value Donors: This group consists of those customers in 5-1-5 and 5-2-5. These are customers who have given only a few times but very recently, and they contributed larger gifts.
  • Low Value, Loyal Donors: This group consists of those customers in segments 5-5-1. They have given recently and do so often, but only give small gifts.
  • Lapsed High Value: This segment consists of those customers in groups 1-5-5 and 1-4-4. They give frequently and spend a lot, but it’s been a long time since they’ve given.
  • Engaged, Lapsed Donors: This group consists of those customers in 1-5-1 to 1-5-5. This segment is highly aligned with your organization and has been with you for a long time.

Step 4: Choose who to target.

The final step is to actually generate a target list for your annual giving appeal or fundraising campaign using your segments above. Remember, you can create as many segments as you like by combining the different RFM values. The segments you choose to target will vary depending on the type of fundraising campaign, the message, and your budget.

For example, in a typical mail campaign, you might target anybody with an R value of 4 and 5, an F value of 4 and 5, and with any Monetary value. However, if you are running a telefundraising campaign, you only want to target those most likely to give a larger gift (for instance, the 5-5-5, “Best Donors” group), since the labor time of making phone calls could eat into your ROI. Typically, campaign results show that the higher the RFM scores, the better the response rate and revenue from that segment.

The Limitations of RFM Segmentation

This type of nonprofit-specific RFM segmentation is a simple and robust way to understand which donors to target in your fundraising campaigns. Its simplicity, however, hides a number of flaws that stand in the way of strong results. For instance:

What are the main limitations of traditional RFM donor segmentation?

  • Exclusion of relevant data and donors. By grouping donors across only three metrics (R, F, and M), you ignore other important bits of information.
    • For instance, you could miss out on a major gift opportunity because you exclude donors who have not given for a long time, even if they just signed up for a newsletter or a petition and are now active again.
  • Overwhelmingly large segments. RFM segments also tend to be quite large. Group 2-2-2 may contain many thousands of donors. As a general rule, the larger the segment, the worse the targeting and the lower the response rate.
    • You’re also faced with a dilemma. If you want to include lapsed donors, you have to include the entire segment, which would be very expensive. In short, RFM doesn’t give you any information about how each individual is likely to respond, which means you can’t identify the givers from the non-givers within the same segment.
  • Reactive rather than proactive. RFM segmentation helps you react to donors’ past giving habits and make general assumptions from there, but it doesn’t actually aim to predict future behaviors as newer methods do.
    • This distinction becomes especially important when it comes to managing churn. Proactively engaging at-risk donors will always be more valuable for your organization than making a segment of donors who’ve already churned and then trying to re-engage them.
  • Time-consuming. Creating and analyzing RFM segments can be complicated and time-consuming, even with the most robust database to automate segments and reports.
    • You’ll have to create, review, and refine your segments before campaigns. Plus, your team will still need to understand what they’re looking at and be able to interpret and act on it. This is an unavoidable reality, so it’s worth remembering that effective segmentation strategies require ongoing management and training.

Going Beyond the RFM Approach

The largest limitation of RFM is that it is based on what the donor did in the past, and not what they are likely to do in the future. It’s not a prediction. When planning campaigns, it’s much more desirable to know what a donor is likely to do next. That way, you can only include the donors who are actually likely to give to your specific fundraising ask. Crucially, this prediction should be based on everything known about the donor’s journey and not just 3 pieces of data.

This graph compares the performance of traditional RFM donor segmentation against more modern AI methods.

The graph above compares the response rates of the best RFM donor segment against the donors predicted by AI to be the most likely to give in a direct mail appeal. This is real data taken from 10 real fundraising campaigns. As you can see, the predictive method yields a much higher response rate!

In essence, AI allows you to pick the best donors from every possible segment for a particular campaign. This means all the most likely givers get included, regardless of which RFM segment that might have fallen into. The result is a better response rate, higher return, reduced costs, and increased overall efficiency.

RFM donor segmentation is a foundational strategy for nonprofits and will always be useful in certain contexts, but it has its limits. Remember that your organization has more options than ever to go beyond traditional segmentation. Artificial intelligence provides accurate predictions based on the entire donor journey, meaning the need for complicated segmentation is significantly reduced or even completely eliminated.  

To learn more about fundraising more efficiently, check out these additional resources:

Donor segmentation is important but complicated. Learn how AI helps nonprofits modernize their fundraising strategies.

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