Project Vision
Bonterra provides tools that nonprofits use to organize their donor data and make strategic decisions—but knowing what to do with that data can be overwhelming. Users often struggle to translate raw information into clear next steps.
To address this, we designed and tested a prototype experience that surfaces actionable insights—timely, personalized suggestions sourced by artificial intelligence and based on supporter behavior. Whether it’s spotting donors ready to upgrade, identifying lapsed givers, or flagging stale contact info, the goal is to help fundraisers act quickly and confidently, without needing to dig through dashboards or spreadsheets.
By making insights visible and intuitive, we’re aiming to reduce the guesswork and empower nonprofits to deepen relationships and raise more funds with less friction.
Challenges
1. Translate vague business goals to compelling creative solutions
2. Leverage AI to enhance the competitive value of the CRM
3. Designing in ambiguity for an unrealized product ecosystem
My Role
Product Designer
Tools Used
Figma
Condens
Confluence
Zoom
The Goal
User Research & Discovery
User research was conducted to fully realize our ideas. We sent surveys, met with our users, and surfaced customer feedback to inform our discovery process. As we iterated, multiple rounds of feedback were sourced to concept test our ideas to see if they met users needs and expectations for a powerful AI integration.
Leveraging AI to Enhance Data Utilization
A homepage widget was designed to surface actionable insights to users from their homepage. AI was integrated into the homepage widget to analyze user behavior and tailor these insights to each user's unique needs. This personalized approach ensured that the widget provided actionable, context-specific recommendations that helped users prioritize tasks and take immediate action.
Subpages to Support Data Potential
The "Feeds" page in this insights project serves as a dynamic dashboard where users can access a stream of real-time, data-driven insights related to their donor engagement and fundraising activities. While this framework can accommodate some automations, AI presents infinite potential to enhance our tools–so organizing data into "topics" allows for further organization, customization options and
This page houses all the key metrics, trends, and personalized recommendations for a committee. By leveraging AI, the feeds automatically prioritize and present the most relevant insights based on the user’s previous actions, with additional settings provided to curate a more tailored experience. The page is designed to be a one-stop hub for users to easily monitor their progress, track changes, and quickly identify areas for optimization.
Encouraging Optimization
A "learn more" drawer expands upon initial recommendations with deeper context, donor-level specifics, and clear next steps. This drawer not only answers the “why” behind each action but also reinforces the impact of engaging with the insight.
Additionally, we incorporated system-wide data—like how many organizations across the platform have completed a similar task and the resulting uplift in performance. This social proof encourages users to take action by showing the tangible benefits of acting on insights and fosters a sense of collective momentum across the platform.
Tracking the Insight Lifecycle
The activity log was introduced to provide a clear history of an insight from start to completion, creating transparency and accountability within teams. It records when an insight is first viewed, who engages with it, and when it’s marked complete—making it easy to see if multiple individuals have contributed to the same action.
This visibility helps prevent duplication of efforts and streamlines collaboration. By enabling users to mark a task as complete, the system becomes more organized, allowing users to filter insights by status and focus on what still needs attention. Ultimately, this feature supports better data hygiene and helps teams stay aligned on what’s been acted on.
Next Steps
What I learned
Designing for insights taught me the importance of balancing visibility with usability—just surfacing data isn't enough; it has to feel intuitive and actionable to users. I learned that placing insights in high-visibility areas like the homepage, and supporting them with clear activity logs and system-wide context, makes it easier for users to engage and follow through. This project also deepened my understanding of how small UX decisions, like adding a completion marker or expanding detail drawers, can create a more confident and organized user experience.
