[GUEST POST] Understanding Fundraising Analytics: A Descriptive Guide
Nonprofit staffs work hard to conduct the best possible fundraisers. But many organizations get stuck in a rut and their campaigns stagnate. They don’t effectively analyze available data to boost their current and future campaigns.
By understanding and using fundraising analytics, your organization can better appeal to your donors and create more effective campaigns.
When you first consider future campaigns, your mind may jump to the worldwide trends of nonprofit marketing and fundraising. Checking out these trends will help your organization adopt the newest and most effective strategies into campaigns. However, this isn’t our main focus.
We actually want to focus on the analytics you’d collect and store in your nonprofit’s fundraising CRM.
The three types of analytics your organization should look out for in this database include:
- Descriptive
- Predictive
- Prescriptive
By diving deeper into the data surrounding your donors and past fundraising successes, you can better plan for the future. Ready? Let’s get started!
1. Descriptive Fundraising Analytics
Descriptive fundraising analytics include the data that is used to best describe the behavior of your donors and segment them into lists for better outreach.
These analytics include specific metrics such as:
- Frequency of giving
- Gift size
- Location
- Age or age range
- Preferred channels of communication
- Preferred channels of giving
These metrics are used to best appeal to your individual donors. CharityEngine’s article explains how these analytics can help nonprofits make more effective appeals to donors by supporting the donor journey. Essentially, the more you know about your donors, the better you can navigate your relationship with them.
For instance, if you know a donor responds positively to email appeals for online fundraising, you may include a link to your online fundraising page or peer-to-peer campaign page in your next message to them.
Descriptive fundraising analytics help your organization create the all-important donor segments in your CRM to create more personal appeals with supporters.
2. Predictive Fundraising Analytics
Predictive fundraising analytics are those that identify trends in your organization’s fundraising campaigns. If you don’t change up your strategy, you can anticipate the trend to remain unchanged as well.
These trends can be both positive and negative in nature. For instance, you may watch for:
- Donor retention rates. If you regularly make mistakes regarding donor retention, but don’t plan to address these mistakes, you can predict that your retention rates will remain low. However, if you already have high retention rates, you likely have a good starting strategy regarding this important metric.
- Fundraising ROI. This is especially important to consider if your organization has a limited budget. If your ROI is low, it’s time to switch up the strategy. However, if you have a high ROI, be sure to carry over your successful strategies into future campaigns.
- Donation growth. Over long periods of time, have your overall donation amounts increased? This is a good indication of growth within your organization. If they’ve decreased, your organization will likely have some larger issues that need to be addressed.
Remember Newton’s first law of motion? This is the idea that an object at rest will remain at rest, but an object in motion will remain in motion unless acted upon by an outside force.
The same can be said about your fundraising. If you keep to the same routine, you can’t expect a different result in fundraising trends. You need change in strategy to expect change in trends. That’s why these are predictive fundraising analytics. Trends predict the future if you decide to remain on the same path you’re currently on.
3. Prescriptive Fundraising Analytics
Prescriptive fundraising analytics are those used to address the changes in strategy and measure the possible outcome of a change in strategy.
Instead of relying on trends as predictive fundraising analytics do, prescriptive analytics hypothesize the future results of a change in strategy and use measurements to help organizations make decisions.
Prescriptive analytics are informed from your predictive analytics. For instance, if your organization sees a trend of low donor retention rate, you may come up with the following potential fixes:
- Starting an advocacy campaign. This provides a nonfinancial method of involvement, which encourages continued engagement and builds relationships. You may predict this to improve your retention rate by increasing it by 5%.
- Adding a recurring donation button on your donation page. Recurring donation buttons help donors sign up to give more frequently. They can then build their relationship in other ways. You may predict this to increase retention by 10%.
The 5% and 10% estimates here are considered prescriptive analytics. If your organization is faced with a couple of different options to address a strategic issue, you may come up with a prescriptive metric for each option, then choose the one with the best-predicted outcome.
If you want to read more and dive deeper into the subject, check out this comprehensive fundraising analytics guide by DonorSearch.
Of course, your organization also needs access to the best tools to measure analytics such as the ones above. When you have access to an all-in-one fundraising CRM solution, you can streamline data from fundraising campaigns and donor profiles to compile reports including all key fundraising analytics.
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By Leigh Kessler – VP, Marketing & Communications, CharityEngine
Leigh Kessler is VP of Marketing and Communications at donor management software platform CharityEngine and a frequent speaker on branding, fundraising, data and technology. He is a former nationally touring headline comedian and has appeared on numerous TV shows including VH1’s “Best Week Ever”, CNN’s “Showbiz Tonight”, Discovery Channel & Sirius Radio. He has overseen and informed research and branding strategies for some of the most well known brands in America.
