The essential
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Use AI to learn more about your customers. The insights provided by generative AI can help you understand your customers’ wants and needs.
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Apply data for personalization. Use AI-generated data to create meaningful, personalized experiences.
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Know the risks involved. Be prepared to tackle uncharted territory when implementing new technologies.
Customer experience leaders across industries are looking for innovative ways to deepen engagement and personalize interactions. The giving community, with its unique challenges and opportunities, has begun to integrate generative AI to improve the giving experience – a strategy that holds valuable lessons for CX professionals around the world. Let’s take a look at donor experience with generative AI.
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 using AI to gain deep donor insights, applying donor data for personalization at scale, the importance of understanding the inherent risks of new technologies and the role of AI in segmentation and predictive analytics.
Specifically, lessons for CX leaders in the giving community include:
- Leverage AI for deep 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 also sets a benchmark for customer interaction across different industries.
- Raising awareness of the risks associated with technology adoption. The introduction of AI requires a careful approach, balancing innovation and risk management – essential to maintaining trust and compliance.
- Strategic resource allocation. AI’s predictive capabilities enable more efficient use of resources, which is fundamental for CX managers operating in budget-conscious environments.
As we delve 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 creating exceptional customer experiences. Whether your organization is in the nonprofit or corporate sector, understanding the nuances of implementing AI in donor relations can illuminate new avenues for customer engagement and retention.
Related article: Customer data analysis and AI: the smart way
Generative AI Donor Experience: Improving Donor Segmentation Using AI
As a first step, using AI to better understand your donor segments and their communication preferences will enable streamlined communication. It will also help you better allocate your limited time by focusing on groups and events that will drive deeper engagement and support, leading to an improved donor experience.
If you’ve generated a donor or invite list based on data like donation history, attendance, interests, demographics, etc., you know it can be a long, tedious, and manual process . By leveraging donor experience with generative AI, you can better analyze large amounts of donor dataidentify 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 provide” more than a personalized message highlighting the fund they are contributing to, the amount of the donation and the impact it is having? While managing this type of information takes time, AI can help us establish communications to ensure donors get the recognition they deserve while giving us the freedom to focus on other tasks (or to change hats). This type of technology can be useful in the following ways:
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Generative AI helps send personalized messages, generate personalized emails, thank you notes and campaign materials.
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For resource-poor nonprofits, it can execute effective, targeted communication with less manual effort, allowing them to spend more time on fundraising.
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By relieving other tasks, AI gives us more time to nurture current, old, and new donor relationships, which is a win for donors, the organization, and employees.
Related article: How AI is changing e-commerce personalization
Predictive Analytics
HAS boost personalization, we want to know our current donors and what their mindset is. Through the generative experience of donors, we can discover the causes they are most passionate about, assess their ability and willingness to contribute, predict their next campaign goals, and determine which programs and events will interest them most.
Generative AI’s ability to predict donor behavior, such as likelihood of giving, retention risk, or preferred communication channels, can help eliminate uncertainty about which campaigns or events to focus on. This helps nonprofits be more strategic in allocating resources (time, talent, budget) that will generate stronger engagement and donations. Additionally, predictive insights can help guide fundraising strategies, improving donor retention and acquisition.
Voices of donors/supporters
Have you ever found yourself digging through the CRM looking for themes from the last communication chain with a major donor or volunteer? Or how about trying to understand what fans think about a particular location on campus or a program they have an affinity for through social media? Wouldn’t it be amazing to quickly sift through this data and discover sentiment, new donor segments, or a new fund? With generative AI and sentiment analysis, it’s possible!
AI models can process unstructured data, including donor voice survey feedback, email, and social media, while sentiment analysis can understand donor feelings, concerns, and preferences. As a result, nonprofits can use this feedback to refine their approaches and meet 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 a lack of resources, caution around donor or employee data, or due to not knowing where to start. If so, there are myriad ways to address these challenges with AI:
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Start small by training existing staff in basic AI concepts and tools.
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Collaborate with faculty, staff, advisors, or volunteers to gain expertise. Valuable tips and insights 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 look for inexpensive proprietary AI sources.
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Prioritize high-impact use cases to efficiently allocate limited funds.
Ethics and Privacy Issues
Several ethical concerns need to be considered when relying on AI. THE European Fundraising Association (EFA) writes: “(AI) is not yet ready to make ethical fundraising decisions,” he goes on to note that “human oversight is necessary to ensure that its use in fundraising practices is done ethically and in accordance with best practices and regulatory codes.”
To navigate these uncharted waters, explore areas where current systems use AI. You may find that much of your technology has been leveraging AI for years. In this case you have a foundation and can therefore start exploring LLMs (large language models) such as ChatGPT or Genesis or other forms of artificial intelligence. When you start implementing AI, make sure to verify its product before putting it into use. Be aware that biases, for example, could be built into the models. Ask questions about the data and verify it. Also be sure to address ethics and privacy concerns by establishing guidelines for AI-based decisions.
Related article: The role of AI in ensuring data privacy
Start by consulting your organization’s AI governance council to understand existing guardrails. Then, efficiently optimize your limited resources. Learn how generative AI donor experience can augment your resources, such as time and budget. Start with small pilot projects that can be easily evaluated. Focus on the most critical areas and define your success metrics, 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 evaluate the tangible differences brought by AI integration.
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