In today’s virtual fundraising landscape, data should inform all of your nonprofit’s strategies from the top down. Being able to rely on data to guide decisions has played a key role in helping many nonprofits maintain and regain their momentum amid the pandemic.
Your organization likely already has an infrastructure in place for generating and tracking the most important fundraising metrics or key performance indicators (KPIs) that you need. But the new frontier of AI-driven fundraising has created opportunities to generate and act on even more valuable data.
Specifically, AI technology enables you to proactively predict future donor behavior by measuring individuals’ likelihoods to take particular actions. Rather than using your data solely to make assumptions based on their past actions, you can instead take a more forward-thinking approach with predictive metrics.
At Dataro, we specialize in AI software for nonprofits, so we help organizations get up and running with AI-driven data strategies every day. Let’s walk through three of the most important metrics that nonprofits can (and should) start generating using AI to improve their strategies.
Likelihood Individual Donor to Give
How likely is an individual donor to give right now if you asked them?
AI tools can screen your entire database of historical donor interactions to identify all of the complex relationships and patterns that lead to a donation. From there, you can use predictive metrics in the form of propensity scores and ranks to directly guide your strategies.
For example, let’s say you’re planning a new direct mail appeal. Using AI, you can identify:
- Current donors who’d likely give in response to your appeal now
- Donors who’d specifically be likely to give over $500 to your appeal
- Lapsed donors who could likely be re-engaged by a direct mail appeal
With predictive scores in hand, you can easily sort your donors by these likelihoods. From there, adjust your appeal strategies to maximize impact—quickly build a mailing list, identify who needs premium mailers or custom appeals, and easily add lapsed donors who are worth including.
By understanding your donors’ likelihood to give, you can significantly refine your appeals. This saves you money on printing and postage while also securing more donations, resulting in an overall ROI boost. Compounded over the long run, generating and tracking metrics related to each donor’s likelihood to give can completely change your nonprofit’s day-to-day fundraising effectiveness.
Likelihood of Donor Churn
Donor churn is a serious issue for nonprofits, but many organizations treat it as an unfortunate reality that can’t be easily predicted or prevented. Not true! AI can predict your donors’ likelihood to churn, giving you another valuable metric to shape your outreach strategies, encourage your donors to stick around, and help you raise more.
Predicting likelihood to churn is especially helpful for your nonprofit’s regular or recurring giving program. Losing these donors is very costly in terms of lost revenue and the cost to acquire a new ‘sustainer’. They’re typically much harder to acquire than one-time donors, so it makes sense to invest in retention.
By measuring regular givers’ likelihood to churn, you can immediately identify at-risk donors. From there, proactively engage them with new messages that express your gratitude and explain the impact they’ve had on your mission. Include program updates, event invites, or whatever else you think will effectively re-engage that individual based on their previous engagement history.
If growing your recurring giving program is a strategic priority for your organization, AI-driven insights can be extremely beneficial. In addition to helping you re-engage at-risk recurring donors, an AI-backed understanding of your churn rates can help you:
- Set more accurate goals for your program’s growth based on data rather than assumptions or hopes
- Dig into the root causes of churn from a more useful starting point, donors who are currently at-risk, rather than trying to piece together factors that led to churn in the past
- Make more persuasive cases to your nonprofit’s board about what you need to strengthen your retention program and why
Without AI doing the heavy lifting of identifying at-risk donors, you’d instead have to rely on overwhelming data analysis and segmentation. Part of the reason that nonprofits often think churn is difficult to combat is because this traditional approach only allows you to react after churn has occurred. With AI-driven likelihood metrics that flag churn risks in advance, you can get ahead of the problem with more proactive strategies.
Likelihood Donoros will Convert or Upgrade
On a similar note, many organizations struggle to pursue donation growth opportunities strategically. They instead cast wide nets asking for donation upgrades from broad audiences. This approach can work, but it’s not particularly effective. Asking the wrong donor for too much too soon can also harm your relationship, which should definitely be avoided.
AI software can help you strategically pursue donation conversion and upgrade opportunities by measuring your donors’ likelihoods to take those actions. For instance, our AI software can measure how likely your donors are to:
- Upgrade their recurring donation to a higher amount
- Reactivate their canceled recurring donation
- Join your regular giving program
With a solid understanding of these propensities, you can develop all kinds of strategies to tap into new donation opportunities. The most direct and immediate improvement is that you’ll be able to quickly build email lists to target donors based on their propensities. In these messages, you can specifically ask them to upgrade, reactivate, or start a recurring donation.
From there, you can build new regular giving or membership engagement plans based on what you’ve found to work best at converting the donors identified above.
These tactics could include things like adjusting your suggested donation amounts, improving your online experience, hosting exclusive virtual events, or offering new membership perks. The main idea is that building these strategies on a foundation of AI-driven data gives your team a head start to understand who’s upgrading or converting and why.
Why These Fundraising KPIs Matter
The bottom line: AI has made it possible for nonprofits to generate and use new types of fundraising KPIs in smarter, more proactive ways.
These likelihood metrics, also called predictive analytics, have historically been very difficult to determine in accurate or truly useful ways. Traditional data segmentation involves sorting your donors by various characteristics or past actions in order to make assumptions about how they’ll act in the future. This approach has major limitations. It’s often inaccurate because it lumps donors into vague groupings, and it can be extremely time-consuming.
AI technology makes it possible to generate predictive scores for all kinds of donor actions, like the ones discussed above.
With a steady stream of incoming likelihood metrics, the process of building mailing lists, reducing churn, and securing new recurring donors is drastically simplified. Most importantly, AI-generated metrics make it easy to be proactive with your strategies and pursue opportunities in real-time rather than respond to them after they’ve already passed.
Tim is the co-founder and CEO of Dataro. He holds a PhD in Cognitive Neuroscience and a Bachelor’s degree in Psychology. Following roles in academia and startups, he co-founded Dataro in 2018 alongside schoolmate David Lyndon. The company’s mission is to help charities improve fundraising using the latest machine learning and predictive modelling techniques.