Using Data for Better Fundraising Asks: 3 Tips for Nonprofits

Boost fundraising success with data-driven strategies. Learn 3 tips for nonprofits.

June 8, 2021

A donor’s journey involves more than simply making a donation. Their gift is typically the last step in a longer engagement process. Before a donor gives they need to connect with your mission, develop an interest, and understand the impact that their gift will have.

Once you’ve built that connection with a supporter, you can’t afford to lose them once the time is right to ask for a donation!

At Dataro, we specialize in AI and machine learning for nonprofits, the new frontier of data-driven strategy. We have a few tips for nonprofits looking to make better fundraising asks. Here’s what we’ll cover:

  1. Use AI to generate accurate donor predictions.
  2. Identify donors who might respond to a larger ask amount or different campaign.
  3. Actively add to and maintain your database.

Don’t forget that the pandemic has been and continues to be a chaotic time for you and your donors—don’t take their passion, attention, and time for granted. Following these steps will help you boost revenue and strengthen donor relationships with more targeted, personalized asks at the right times. Let’s dive in.

Use AI to generate accurate donor predictions.

Artificial intelligence has become an accessible and extremely valuable tool for nonprofits. By generating accurate predictions about the actions that donors are likely to take, AI can shape your fundraising strategies down to the individual level.

AI for fundraising works by identifying deep patterns in your historical engagement and fundraising data and then training predictive models to chart likely outcomes in the future. AI software continually adapts and refines these models over time to improve fundraising performance. Explore the complete guide to AI for nonprofits to learn more about this process and see some real-life examples.

Nonprofits use AI to:

  • Target their fundraising campaigns to the right individual donors based on their likelihood to give at that particular time.
  • Identify donors likely to give larger amounts, mid-level, or major gifts, so they can tailor their ask strategies to these individuals.
  • Identify donors likely to convert from single giving to regular giving or sustainer programs.
  • Proactively identify donors likely to churn out of their recurring giving programs to then target them with extra outreach and engagement opportunities
  • Know when to send special messages and appeals to supporters to upgrade their gift or reactivate a lapsed gift.

The bottom line: If you’re looking to make more informed asks of your donors, you can’t get much more informed than proactively anticipating who’ll be responsive to which types of campaigns. These predictions also help you avoid some major fundraising don’ts, like bombarding donors with too many blanket appeals or asking for donation upgrades before the time is right.

At a deeper level, the value of artificial intelligence is that it replaces the need for outdated donor segmentation strategies, which you likely already use to help plan your appeals and target specific audiences.

Today, surface-level metrics simply don’t go far enough to give donors the more intuitive, personalized interactions that they’ve come to expect. AI and machine learning software has quickly become a standard addition to nonprofit toolkits. It is still important, of course, to have a solid understanding of the common fundraising metrics that nonprofits use to measure the performance of their campaigns. AI is the next step, taking the guesswork out of donor targeting so you can make better fundraising asks and increase fundraising returns.

Identify donors who might respond to a larger ask amount or different campaign.

By examining the full history of your organization’s fundraising, AI can provide critical new insights to help increase the lifetime value of your donors. Here are some key examples.

Convert to regular giving
If your strategy revolves around growing your regular giving or sustainer program, where better to look for new leads than your existing single givers? The challenge is knowing which of your supporters are the most likely to convert, so you can contact them specifically.

With machine learning software, fundraisers can use predictive scores and ranks to easily identify the best prospects each week. This allows you to roll out new ask strategies aimed at converting the right donors from single to regular giving, growing your regular giving program without compromising your appeals.

Increasing ask amounts
A key challenge for fundraisers can be to encourage supporters to increase their gift amounts and support for your mission. Of course, if you push too hard then you risk alienating your supporters and potentially losing donations.

AI allows charities to learn from every single historic occasion when a supporter has increased their gift. Why is this useful? By examining these patterns in your fundraising data, AI enables fundraisers to identify the donors most likely to give a larger gift now. This translates into tangible financial returns when charities use the following strategies:

  • Predictive models can tell you which supporters are the most likely to give more than $500 in response to a direct mail appeal. Using this propensity, you can adapt your ask strategy by asking for a larger gift or sending the donor a premium mail pack.
  • Mid-level predictions will tell you which supporters might give between $500 and $5000 cumulatively over a 12 month period, so you can tailor specific donor journeys aimed at increasing giving amounts over the course of the year.
  • Major giving predictions can help prioritize your prospect research and stewardship efforts by honing in on the supporters most likely to convert. This can be compared against your own major giving metrics to make sure your team is focusing on the right supporters and, most importantly, not missing out on any potential major givers.

Nonprofits often use surface-level donation data to clump donors into similar groups based on their giving patterns, but be aware that you can easily miss important insights with these broad segments. Predictive analytics generated by machine learning or AI software will be your best bet for individualized predictions, which you can then use to create segments and mailing lists.

Actively add to and maintain your database.

Continually adding new fundraising and engagement data to your database is fundamental for improving your fundraising asks over time. You need a clear sense of how your strategies are currently performing and how your key fundraising metrics are tracking in order to stay on top of changing donor trends and preferences.

To ensure a steady flow of up-to-date data into your CRM, integrate your software whenever possible. These connections allow data to flow seamlessly into your CRM. Your donation software and registration or sign-up tools should also ideally integrate with your database, ensuring you’ve got a comprehensive, up-to-date view of how donors are interacting with your campaigns.

For example, our tool at Dataro provides predictive scores and ranks for each donor based on the specific propensity that you’re measuring. When this data flows back into your CRM, you can simply sort your donors by these scores and ranks to find the best prospects for all sorts of fundraising campaigns, rather than relying on complex filters. If a team member is in charge of managing your recurring giving program and reducing churn, they can easily use the scores and ranks to find the most ‘at risk’ donors that month and then design an engagement program for them.

Identifying these at-risk donors manually, by combing through engagement histories and trying to piece together patterns, would be an extremely time-consuming (if not impossible) task.

For on-the-ground donations that you can’t automatically track, like gifts mailed in or made at in-person events, you’ll need to set some clear protocols for manual data entry into your CRM. Standardized date formats are a common example of discrepancies that can cause valuable insights to fall through the cracks.

Once you have a solid system for generating fundraising data and reporting it to your database, you’ll have a foundation to build upon. Comprehensive data is invaluable for day-to-day online fundraising, campaign and event planning, prospect research, and more.

Data-driven fundraising is the new norm for the nonprofit sector. After a year of pandemic challenges, it’s clear that adaptability and solid data management strategies will be more important than ever for organizations of all sizes.

By tapping into new technologies and fully understanding how to use your data, you can better understand your donor journeys and make more informed fundraising asks over time. Then, as you continually refine your approach and learn from past appeals, you’ll be able to contact donors with the perfect approach at the right moments—leading to stronger relationships, more effective campaigns, and more support for your mission.

About the Author

Tim Paris, CEO and Co-Founder

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 modeling techniques.


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