How to Choose an AI Solution for Nonprofit Fundraising
Nonprofit organizations that are prepared to innovate today have a wide variety of technical products and services to consider. However, as Yale Insights from the Yale School of Management highlights, the unique challenges facing nonprofits striving to make the right technology investments:
“Done effectively, technology adoption isn’t gadget chasing; it’s strategically selected digital tools that empower staff and stakeholders to deliver on the organization’s mission… For-profit organizations use technology strategically to maintain their profit margins, increase market share, and enhance shareholder value. But, for nonprofits, the mission is to create public value. It requires a different calculus to figure out how technology heightens their effectiveness…[It’s] a more difficult assessment but essential.”
One key technology that nonprofits must assess is artificial intelligence (AI). Forbes reported last year that “89% of nonprofit professionals believe that AI can make their organization more efficient.”
The promise of AI to boost nonprofit fundraising performance is exceptional, as it enables fundraisers to deliver personalization at scale, especially for the individual donors solicited through direct response channels. Nonprofit leaders should know which factors to consider when making critical AI technology decisions for fundraising optimization, and, therefore, should select an AI service that meets these key criteria.
Utilize Behavioral Data to Eliminate Bias
Fundraisers must select an AI service that avoids bias by ethically modeling donor behaviors within the context of a single organization at a specific moment in time.
An AI service for nonprofit fundraising must:
- Intentionally exclude most demographic and other personally identifiable information (PII).
- Capture and model demonstrated philanthropic behaviors within a single, specific nonprofit organization. Model from unfiltered, unmanipulated datasets and avoid employing algorithms that have negative bias.
- Generate real-time giving insights from observed donor behavior at the moment of solicitation.
An AI service that eliminates both implicit and confirmation biases additionally benefits fundraisers by motivating them to continually and authentically gather insights about their donor base. They must consistently test new messaging, issue donor surveys and assist in the development of new or improved programming that inspires donors to philanthropic action. High performing AI services are those that bolster and deepen the core relationship-building insights of fundraising.
Prioritize Donor Privacy
When collaborating with an AI services organization, the services should be applied only to those individuals who have willingly shared contact information and have not opted out or unsubscribed. The service provider should not share nonprofit donor data with a third-party without express written consent.
The AI service providers fundamentally rely on each nonprofit partner to ethically collect, manage and use their data in accordance with security and privacy best practices. This includes General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA) and other privacy regulations.
Ensure Data Security
Nonprofits should never expose their data by collaborating with partners that are not able to demonstrate a comprehensive security strategy that drastically diminishes the risk of a data breach. AI services vendors should use secure, encrypted, anonymized donor records and maintain their own technology infrastructure, personnel training practices and internal policies to safeguard each organization it serves. They should also be willing to participate in a rigorous security audit.
Further, although AI is data dependent, it should not always require PII to be effective. The safest AI services depend on techniques such as behavioral economics modeling (BEM) to offer actionable insights without the need for PII. There is always a danger to donors when PII is shared with a vendor because of possible data breaches. However, that security risk is minimized if the data is solely centered on anonymized behavioral analytics.
Be Easy to Use
One goal of using an external AI services provider is to eliminate the need for a nonprofit to change existing processes, practices and fundraising systems. The nonprofit AI services provider should have a well-defined, collaborative approach to working with the existing fundraising practices; a seamless process of accepting donor data; and provide unique, understandable insights on giving performance.
Have a Track Record of Success at Material Scale
A nonprofit needs strong, tangible financial results to advance their mission. A credible AI services provider should be able to provide data and reports from previous work that demonstrates improvements versus legacy methods in the following metrics:
- Increased giving amounts both in the short term and through the donor lifecycle.
- Improvements in both giving levels and cost reductions.
- Donor advancement accelerating faster than existing methods.
Additionally, ask the AI services provider how many records they have processed and how many learning cycles their clients have experienced. AI models improve as they process more data. These two metrics demonstrate volume (cumulative number of records processed) and frequency of learning cycles, which are the core objective drivers of AI services maturity.
Fundraisers should select an AI service that has proven it can optimize both revenue and cost in direct response fundraising. Leading providers of these AI services can help a nonprofit meet their revenue growth aspirations, while minimizing the brand damage and operating expenses caused by excessive solicitations. This should all be done securely, without PII, in the context of an individual donor’s giving behavior, at a single nonprofit organization, in real-time.
Michael Gorriarán is a globally experienced technology sector executive with an extensive 30-plus-year career at Microsoft, Xerox, and early-stage, high-growth business ventures. He has held executive leadership roles in advanced cloud services, enterprise software, business process outsourcing and professional services businesses.
Prior to his current role as president of Arjuna Solutions, Gorriarán was most recently general manager of worldwide commercial markets strategy group at Microsoft. He has either led, been chief operating officer, general manager or a key executive in businesses ranging from less than $10 million to more than $77 billion in annual revenues. His responsibilities have included developing and implementing new business strategies and financial models, executing turnarounds, and launching new lines of business and go-to-market plans to gain a sustainable competitive advantage around the world.
Gorriarán holds an MBA from the Kellogg School of Management at Northwestern University, and a bachelor of science in marketing, with concentrated studies in economics and Spanish, from The University of Rhode Island. He is an avid distance runner, outdoor enthusiast and active parent with his wife Kris of their two children.