What’s All The Fuss About ROI?
The world of analytics, as well as fundraising in general, is full of daily jargon that we read about in articles, tweets, and blogs, as well as hear at the water cooler or in meetings with our colleagues. But to a novice interested in the field of fundraising analytics, or just understanding what it means for your nonprofit, many terms and acronyms are bandied about. One of the most common terms in fundraising analytics is Return On Investment or ROI. I would like to break down the concept of ROI in terms of how it relates to nonprofit fundraising analytics in two ways:
- Utilizing analytics to measure your overall ROI for each fundraising program or initiative
- Measuring whether or not an analytics project, such as predictive modeling, within your database produced a positive ROI
Let’s look at the first bullet. When utilizing analytics to measure your ROI with events, capital campaigns, annual appeals (mail or online), social media presence, etc., as effective tools to identify, engage, and cultivate prospects as well as ultimately receive donations, you must establish what specific metrics to benchmark throughout the process from beginning to end, as well as on-going. One might want to start with a baseline of the following:
- What is your dollar goal of the event, capital campaign, mailings, etc., (keep in mind that ROI not only means measuring dollars raised, but could simply be the number of newly identified prospects, for example)
- How many initial prospects did you invite to an event, mail to, call on, clicked through in an e-communication and donate online, set up a meeting with, deliver a proposal to, have as “likes” on your Facebook page, etc.?
- How many new prospects do you hope to identify from the mailing, event, etc.?
- How many donors are you targeting to renew?
- How many new prospects are you expecting to donate for the first time, or past donors do you hope to re-acquire?
- Do you have a timeline on which you are going to base your success?
The list can go on and on, and the bottom line is to have some metrics established so that you can benchmark whether or not you are having success with your individual fundraising programs and initiatives.
The second bullet refers to measuring the effectiveness of an analytics project and seeing if there was a ROI. Again, you need to go through the same exercise as above by thinking about not only what you want to measure, but how you wish to measure it. For example, if you decide to build or have built a predictive model for major gifts, and your goal is to identify 250 previously unknown major gift prospects within your pool of 10,000 records for an upcoming capital campaign, then that could be something to measure for ROI. You could also measure in 1, 2, and 3 years how many of those newly identified major gift prospects ended up in a meeting, and eventually how many turned into campaign donors. Don’t forget to look at how many ended up as mid-level donors by increasing their typical annual gift. They may not have given you that capital gift now, but they may transition over time into your major gift threshold, and that could be measured as a successful ROI in itself.
Another example might be if you wish to start up or expand your planned giving program and identify potential planned gift donors from your pool of prospects. If your goal is to find a targeted group of 2,500 prospects for your planned gift marketing efforts, then from there hone in on a smaller group of 250 to reach out to on an individual basis over the next 3 years, and lastly receive 25 bequest gift intentions, then you can measure all these pieces to calculate ROI based on those three metrics for your modeling project.
The bottom line is that effective ROI analysis depends upon clear definitions of where you are now, what your goals are, and the timeline for achieving those goals so that you can benchmark your progress.