Editorial
The Gist
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Use AI to learn about your customers. Insights provided by generative AI can help you understand your customers' wants and needs.
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Apply data for personalization. Use data generated from AI to create meaningful, personalized experiences.
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Know the risks involved. Be prepared to face uncharted waters when implementing new technologies.
Customer experience leaders across industries are looking for innovative ways to deepen engagement and personalize interactions. The donor community, with its unique challenges and opportunities, has started to integrate generative AI to enhance donor experiences — a strategy that holds valuable lessons for CX professionals everywhere. Let's take a look at generative AI donor experience.
This article will explore how generative AI is revolutionizing the donor experience and what broader implications this has for CX. We’ll discuss key takeaways including the utilization of AI for in-depth donor insights, the application of donor data for personalization at scale, the importance of understanding the inherent risks of new technology and the role of AI in segmentation and predictive analytics.
Specifically, lessons for CX leaders from the donor community include:
- Leveraging AI for Deepened Understanding. By analyzing donor data, AI provides a nuanced understanding of customer needs and preferences, a principle that can be transferred to any customer base.
- Personalization Through Data. The use of AI-driven data not only creates individualized experiences for donors but sets a benchmark for customer interaction across different sectors.
- Risk Awareness in Technology Adoption. Introducing AI requires a careful approach, balancing innovation with risk management — crucial for maintaining trust and compliance.
- Strategic Resource Allocation. AI's predictive capabilities enable more effective use of resources, which is fundamental for CX leaders operating in budget-conscious environments.
As we dive into the generative AI donor experience, these key points will serve as a guide for CX leaders to harness the full potential of AI in crafting exceptional customer experiences. Whether your organization is in the nonprofit sector or a corporate entity, understanding the nuances of AI implementation in donor relations can illuminate new pathways for customer engagement and retention.
Related Article: Customer Data Analytics and AI: The Smart Path
Generative AI Donor Experience: Enhancing Donor Segmentation With AI
At a baseline, using AI to further understand your donor segments and their communication preferences will allow for streamlined communication. It will also help you better allocate your limited time by focusing on the groups and events that will drive deeper engagement and support, thus leading to an improved donor experience.
If you've generated a donor or invitation list based on data such as giving history, participation, interests, demographics and so on, you know it can be a long, tedious and manual process. By leveraging generative AI donor experience, you can better analyze vast amounts of donor data, identify hidden patterns and relationships and use segmentation models to group donors based on this data.
Personalized Communication
Donors expect personalized interactions and communications. What says "I appreciate you and the support you give" more than a customized message highlighting the fund they’re contributing to, the donation amount, and the impact it has? While managing this type of information is time-consuming, AI can help us build communications to ensure donors get the recognition they deserve while giving us the freedom to focus on other tasks (or switch to a different hat). This type of technology can be helpful in the following ways:
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Generative AI enables customized messaging, generated personalized emails, thank-you notes and campaign materials.
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For resource-poor nonprofits, it can execute efficient and targeted communication with less manual effort, creating more time to spend fundraising.
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By alleviating other tasks, AI allows us more time to cultivate current, lapsed, and new donor relationships, which is a win for donors, the organization and the employees.
Related Article: How AI is Changing Ecommerce Personalization
Predictive Analytics
To boost personalization, we want to know about our current donors and what their mindsets are. With the help of generative AI donor experience, we can uncover causes they are most passionate about, assess their capacity and willingness to contribute, predict their next campaign's goals and determine which programs and events will resonate best with them.
Generative AI’s ability to predict donor behavior — such as likelihood to give, retention risk, or preferred communication channels — can help take the guesswork out of what campaigns or events to focus on. This helps nonprofits be more strategic in allocating resources (time, talent, budget) that will yield more robust engagement and giving. Additionally, predictive insights can help guide fundraising strategies, improving donor retention and acquisition.
Voice of Donor/ Supporter Feedback
Ever find yourself digging through the CRM searching themes from the last communication string with a major donor or volunteer? Or how about trying to understand how supporters feel about a particular place on campus or a program they have an affinity towards through social media? How amazing would it be to quickly go through that data and discover sentiment, new donor segments, or a new fund? With generative AI and sentiment analysis, you can!
AI models can process unstructured data, including voice of donor feedback from surveys, emails, and social media while sentiment analysis can understand donor sentiments, concerns and preferences. As a result, nonprofits can use this feedback to refine their approaches and address donor needs more effectively.
Related Article: Why Real-Time Feedback is Crucial for Modern CX Strategies
Managing Risk-Averse or Resource-Poor Organizations
You may work in an organization that is slow to adapt to change — perhaps due to lack of resources, caution around donor or employee data or a matter of not knowing where to start. If that’s the case, there are a myriad of ways to address these challenges with AI:
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Start small by training existing staff on basic AI concepts and tools.
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Collaborate with faculty, staff, advisers or volunteers for expertise. Valuable advice and information can be gleaned by asking donors and supporters about their feelings and experiences with AI.
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Explore open-source AI libraries and tools to overcome financial constraints or search for inexpensive proprietary AI sources.
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Prioritize high-impact use cases to allocate limited funds effectively.
Ethical and Privacy Concerns
There are several ethical concerns that should be considered when relying on AI. The European Fundraising Association (EFA) writes, “[AI] is not yet ready to make ethical fundraising decisions” it goes on to report that “human oversight is needed to ensure its use in fundraising practice is done ethically and in accordance with best practice and regulatory codes.”
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To navigate these uncharted waters, explore areas where current systems are utilizing AI. You may discover that much of your technology has been leveraging AI for years. In that case, you have a foundation and can therefore begin to explore LLMs (large language models) such as ChatGPT or Genesis or other forms of artificial intelligence. As you begin to implement AI, be sure to check and verify its product before putting it into use. Be aware that bias, for example, could be built into the models. Ask questions of the data, and check through it. Also be sure to address ethical and privacy concerns by establishing guidelines for AI-driven decisions.
Related Article: The Role of AI in Ensuring Data Privacy
Begin by consulting with your organization's AI governance board to understand the existing guardrails. Then, optimize your limited resources effectively. Investigate how generative AI donor experience can extend your resources, such as time and budget. Start with small pilot projects that can be easily evaluated. Concentrate on the most critical areas and define your metrics for success, such as time saved, impact created, or donations received. Establish a baseline by recording these success metrics before implementing AI. This will allow you to compare and assess the tangible differences made by incorporating AI.
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