The Importance of Identifying the “So-What” In Data
Data, when leveraged correctly, drives successful programs. Unfortunately, with so much data out there, it can be hard to make sense of it all. And with the last few years earning the title of polycrisis, it is getting increasingly more difficult to identify true cause and effect.
Fortunately, by leveraging the right types of data, we can begin to see a story that not only allows us to identify WHAT the metrics are reporting, but also the WHY behind them. This in turn allows us to understand HOW our programs may be impacted for the future and WHAT we can do about it today to chart the course in the direction we want to go.
At Fuse, we lovingly refer to this as finding the “So-What” factor in the data - which is achieved by keeping a pulse on the industry, the environment and identifying meaningful data trends across programs.
In this post, we are hoping to spark conversation about finding that ‘so-what’ factor and why understanding what’s going on underneath the hood is so critical to identifying what dials to focus on and prioritize in your program.
So, What Is the Industry Saying?
Recent reports tell us that as an industry we are trending similarly to what was reporting pre-pandemic, with donor counts, gift counts and retention all continuing to drop, while slight improvements to average gift and gifts per donor are helping to drive up donor value and stabilizing revenue.
With many of our client’s trends generally aligning with the industry, we dug into their data to better understand the why behind each trend. What we found was a common story among many clients, indicating their programs weren’t experiencing “problems” in performance trends, so much as they were seeing changes in metrics due to the natural evolution of the audience composition of their donor file.
Consider this … a file’s composition will always naturally impact key metrics, and we have no doubt that you have likely experienced more than one of the trends outlined below:
Drop in new donor counts
Drop in low dollar gifts
Drop in active file counts
Increased reacquired donor counts
Increase in new digital joins
Large influx of emergency donors
Increase in sustainers, or the percentage of the file they represent
Increase in DAF giving
While any one of these might contribute to the changing composition of your file, if more than one has occurred, their combined effect is likely having a significant impact on your KPIs. Only by understanding the natural fall-out of these changes can we decipher if a trend is the natural evolution of a changing file or if we should be sounding the alarm.
But Things Aren’t Always What They Seem
To illustrate this, we are spotlighting retention, which peaked across the industry in 2021 but has been dropping every year since. While this is indeed a reflection of donor performance, it isn’t necessarily the sign of a problem across all files.
To illustrate this, we provide the following example:
A file brings in 20K new donors and retains 30% of them the next year (6K)
That same file mailed 80K multi-year donors and retained 65% of them that same year (52K)
Do the Math … 58K donors retained out of 100K total for a retention rate of 58%
Now, let’s hold retention rates constant, but let’s assume they launched a successful acquisition package that DOUBLED the number of new joins.
A file brings in 40K new donors and retains 30% of them the next year (12K)
That same file mailed 80K multi-year donors and retained 65% of them that same year (52K)
Do the Math … 64K donors retained out of 120K total for a retention rate of 53%
In this example, we have a success story, where a program manager could say:
They DOUBLED acquisition response and grew the program
They maintained first year retention rates & multi-year retention rates
They grew the program and increased revenue
However, despite this example representing success, all too often people focus on the fact that active retention dropped 8%, from 58% to 53%.
Now, let’s consider the opposite, where pipeline, first year retention and multi-year retention all drop, thus leading to a condition where core donors make up a greater percentage of the file’s composition. Keeping in mind that multi-year donors naturally report greater retention than first year donors, if they make up a greater percentage of the file, even with multi-year retention dropping, we might still see overall retention increase.
In both examples we see active file retention trend opposite what is happening among first year and multi-year donors, and these are but two examples of the many combinations of file dynamics. If we were to take these metrics in either scenario at face value, we would be missing critical elements of the story that are needed to develop the right strategies for the program.
Bringing It All Together
As useful as data is in developing trends, we should never take a metric, nor a trend, at face value. Rather, we must take the time to understand WHY they are changing, and truly understand if the change is the sign of a problem (or opportunity) versus just a natural effect of a changing file.
As we look at recent industry reporting, many of the trends may seem a bit worrying at first glance. But we believe file composition is behind much of what we’re seeing, especially as files continue to “settle” following the events of the last few years.
If you have questions about what your data might be telling you, and what it could mean for the future of your program, please reach out to davidj@fusefundraising.com. We love to talk data!
Cover image source: https://www.freepik.com/free-vector/flat-design-business-planning-with-device_19948929.htm
