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Using RFM Analytics in your Organization

By: Robert H. Lane, MBA, Ph.D., CiP
Chief Executive Officer
Lane Services, LLC

Do you ‘know’ your donors?  Are you able to confidently state that you are not asking a $5 donor for $500 or a $500 donor for $5 when you send your appeals?  Utilizing the tools and techniques of RFM (Recency, Frequency, Monetary) Analytics to more effectively segment your database, will help you invite your prospects and donors to make a gift that is within their means, and to a campaign that will pique their interest.

RFM Analytics is a tool that provides rankings for your contacts based upon their financial participation with the organization. It is a very commonly used tool for fundraising, but its applications are not limited to the fundraising marketplace. Any organization that targets contacts based on past participation on events, engagement, or purchases may benefit from RFM Analytics.  RFM may also be used to segment prospects based on input from external sources such as wealth engines, alumni associations, family history, etc.  If you can quantify it, you can use RFM. 

With RFM Analytics you can:

-Rank and organize your donor population into specific groups manually or automatically.
-Define ranking scores for recency, frequency, monetary, combined (calculated), and total (calculated) values.
-Create groups, such as quintiles, that reflect the relative ranking of donors according to all RFM measurements.
-Analyze transaction patterns to accurately predict future behavior.
-Define different donor population and transaction queries to include in each analysis.
-Use ‘n-select’ or A-B testing to create test groups
-Offer special premiums or incentives to certain segments to encourage participation

The key to successfully using RFM Analytics in any organization is having the patience to watch how people perform over a long period of time. Remember that anything can impact behavior, and do not react immediately to changes. RFM buckets tend to remain stable.

Depending on the donor management software your organization uses, it is recommended that you create two queries to prepare for RFM.  The first is a population query which is the ‘universe’ of records.  This may be everyone who made a gift within the past 5 years or everyone on a rented list if this is a campaign to reach potential donors.  For association foundations, this may include engaged members who have never donated to the foundation. 

The next step is to create a transaction query.  Make sure the transaction query Includes Quantity, Amount, and Transaction Date. These properties are used for the ranking. You can alias other properties if you wish, such as aliasing ‘Date Received’ or ‘Effective Date’ as the Transaction Date.  This query contains the specifics for the R, F, and M. 

RFM rankings can be used as the basis for segmentation. Segmentation assists with targeting the market or the segment of the database who is most likely to respond to the marketing effort. For example, if your marketing department is trying to mail the company contact of their best conference attendees, they might look for:

-Recency going back 5 years
-Frequency of attendance being greater than ten times attending (because this would imply that at least two attendees from that company attended within those 5 years)
-Value equal to increments of conference registration because that is the value of their attendance (anyone with a value higher than that might have purchased books at the conference or made a donation above and beyond the registration fee).
-You can use the same ranking model against different groups or populations within your database to be able to make predictions and better target who is most likely to respond to a particular marketing effort. The RFM rankings might look the same, but the numbers within each rank can be quite different.

For example, Segment 1 may include those who donated between $1 & $10 within the last 12 months but not within the past 90 days.  Segment 2 may contain those who gave between $11 & $20.  Segment 3 may be those who contributed between $1 and $10 between 13 & 24 months ago. 

Segmentation drives the criteria that will be used to select and segment those donors who will receive your marketing messages. A segmentation job is a set of queries that are run in a specific order and result in the selection of the first occurrence of each matching record.

Segmentation data is prepared and run before the data is attached to its source code and the final output is generated. This allows for data criteria testing, n-select or dummy selects, or to get counts before the final list is prepared. Because the data can be purged and lists can be run again, you can continue to target your message.

Research has proven that RFM Analytics will significantly improve the net result of a campaign, as opposed to sending the same message to everyone in your ‘universe’. 

 

 

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