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Using Staupell RFM Tool Basic: Adding Data and Computing Scores

This walks through how to load your data into the Staupell RFM Tool Basic and generate Recency, Frequency, and Monetary (RFM) scores for your constituents. You will first need to install the tool onto your computer.

Step 1: Prepare Your Data Before Importing

Before you import anything, decide what should count toward a constituent’s RFM score, and remove anything that shouldn’t. Common exclusions:

  • In-kind gifts, if you don’t count them toward giving history
  • Planned gifts, if you don’t count them toward giving history
  • Engagement or event records that aren’t actual gifts
  • Adjustment records

A note on pledges:

Pledges need special attention, because pledges and pledge payments will produce different scores. Pledge payments (made over time) will show more recency and frequency than the original pledge commitment, which will show less of both. The monetary total may also look different depending on where a donor currently sits in their pledge cycle.

If you are not counting pledges toward RFM, remove both the pledge records and any pledge payments tied to them. If you are counting pledges, decide intentionally whether you want the pledge commitment or the pledge payments represented in your data, since the two will change the resulting scores.

Step 2: Importing Full Gift Data

If you’re able to export gift-level data, you’ll need at minimum three fields for each record:

  • Constituent ID
  • Gift Date
  • Gift Amount

Extra columns beyond these three are fine — the tool will only use what it needs.

  1. Click Import Gifts.
  2. Click Build My Overall RFM.
  3. The tool will try to automatically detect which of your columns are the Constituent ID, Gift Date, and Gift Amount.
  4. Check its guesses. If any field is mapped incorrectly, select the correct column yourself before continuing.
  5. Click OK. The tool builds a new, time-stamped RFM results sheet, so running it more than once won’t overwrite previous results.

What you’ll get:

For each constituent: days since their last gift (Recency), total gift Frequency, total gift Monetary amount, an R score, an F score, an M score, and a combined RFM text field showing all three together (for example, “511”).

Step 3: Importing Gift Summary Data (If You Can’t Export Full Gift History)

If your database can only export person-level summaries rather than individual gift records, you can still run RFM. You’ll need four fields per constituent:

  • Constituent ID
  • Total lifetime giving
  • Count of gifts
  • Last gift date
  • Import your demographic/summary file.
  • Tell the tool to Assign Gift Summary Fields, rather than looking for individual gift records.
  • Match your columns to the correct fields (Constituent ID, count of gifts, total giving, last gift date). Check the tool’s guesses before confirming — it will try to map them automatically, but not always correctly.
  • Click Build My Overall RFM. This creates a new RFM results sheet.
  • To bring the scores back into your original people/demographics table, use Append RFM. This merges the RFM scores directly onto your demographics sheet, alongside each person’s other information.

Step 4: Understanding Your Scores — Don’t Sum R + F + M

Keep Recency, Frequency, and Monetary as three separate scores rather than adding them together into one number. A summed score can be misleading. For example:

  • A donor who gave a single $5 million gift 20 years ago might score 5‑1‑1.
  • A donor who just made their first $1 gift might score 1‑1‑5.

Both of these would add up to a “7” — but they are two very different donors, and treating them the same would be a mistake. Instead, combine R, F, and M intentionally based on what you’re looking for:

  • High Recency + High Frequency → planned giving signals
  • High Recency + High Monetary → major gifts prospects
  • High Frequency → engagement or annual giving prospects

Step 5: Building a Prospect List

Once your RFM scores are appended to your demographics table:

  1. Filter for the score combination you want (for example, everyone with an M score of 5).
  2. Sort by Frequency, then by Recency, to prioritize within that group.
  3. You now have a ready-to-work prospect list, segmented by actual giving behavior rather than guesswork.

Step 6: Starting Fresh (Clean Slate)

To start a new RFM run from scratch:

  1. Paste your data into a new sheet, or select an existing sheet already in your workbook.
  2. Tell the tool whether this is gift-level data or demographic/summary data.
  3. If it’s demographic/summary data, assign the gift summary fields as described in Step 3. If it’s gift-level data, the tool will compute recency, frequency, and monetary directly.
  4. Click Build My Overall RFM, then Append RFM if you want the scores merged into your existing table.

Getting Help

If you get stuck, run into an issue, or hit an unexpected pop-up, reach out directly: marianne@staupell.com

We’d also love to hear how your segmentation is going once you’ve put the tool to work.