Community engagement is necessary to the success of community planning and project implementation, and the data collected through this process serves as both a record of community input and the foundation for the plans and policies that follow. Each community has its own relationship with data: how the data is collected, stored, and managed; what is done with it to inform decision-making and outcomes, and how the community perceives their perspectives are integrated throughout the process. But too often, the systems used to collect and interpret this data are impersonal and rigid, failing to reflect the diversity of lived experiences.
(Above) Community values engagement in Leadville and Lake County as part of the One Community Project.
Cracks form when engagement is treated as a checkbox instead of a relationship. Surveys that never reach historically excluded communities. Community meetings held in inaccessible spaces. Feedback gathered but never revisited. Insights translated into decisions without context, nuance, or accountability. When engagement is rushed, transactional, or overly academic, people slip through the cracks, especially those who already feel disconnected from the decision-making process in their communities. At Community Builders (CB), we are rethinking how we collect, interpret, and apply community engagement data in a way that is both rigorous and relational.
We’re Conner and Steven, a fellow and intern who joined CB nine months ago to explore and support the organization’s already thoughtful, community-specific approach to data. In collaboration with the CB Technical Assistance team, we worked to understand the nuances and best practices of complex and human-centered data collection and analysis. Our goal was to create a data system that could be more easily adapted and deployed across future projects without sacrificing the nuance or rigor.
In doing so, we explored questions such as “How do we collect data that provides an accurate cross-section of the community’s perspective?” and “What does it mean to quantify feelings?” Answering these questions helped us to develop a data system and process that is rigorously human.
(Above) Conner & Steven present and discuss their lessons learned with the CB Team.
Designing a Human-Centered Data System
Gathering representative feedback from a community is crucial for building plans and policies that genuinely reflect people’s lived experiences. Yet, even the richest data is just a sample, not a complete picture. We worked to standardize a data system that does more than just track inputs and outputs. A system that allows us to surface deeper questions: Who did we reach? Who are we still missing? Which patterns and themes are emerging? It reminds us that a spreadsheet doesn’t capture the full story, but can show patterns worth exploring with the communities themselves.
Our process involves two main steps:
- Coding: Carefully analyzing and categorizing comments to identify shared ideas and themes
- Distilling: Synthesizing those ideas into a set of core community values
These steps create a delicate balance, allowing us to maintain the rigor of verified methods while maintaining the essential element of nuance that comes from community engagement data. When we code, our aim is to discern the “color,” or core idea, of each “brushstroke” of feedback. We don’t rely on a rigid, pre-set list of codes; instead, our codes are reimagined for each unique project.
This flexible approach allows us to capture the essence of what’s being shared. For example, the code “community involvement” recently showed up in two different projects. In one project, it was referencing nonprofit and civic engagement, but in the other, it was focused on neighborliness and coming together in hard times. Coding notes captured these differences, ensuring we didn’t flatten the meaning behind each comment.
Our qualitative analysis software, Quirkos, helps visualize these trends and filter them by demographics to see patterns emerge. This visualization becomes the basis for a collaborative synthesis, involving team members both close to and new to the project. Together, we refine these patterns into authentic community values.
But even that isn’t the final step. We then return to the community with a preliminary set of values. Through workshops and feedback loops, we check our work: Do these values reflect what you told us? Are we getting it right?
(Left) Overview of CB’s qualitative data analysis process that was shared with WE Vision project stakeholders to increase transparency.
(Right) A community meeting in Nucla, Colorado (February 2025) where the Community Builders team invited residents to review draft community values and share their thoughts on whether we “got it right.”
Building Trust Through Relationship-Centered Engagement
Designing a thoughtful data system is only one part of the equation. How we engage community members to contribute their opinions and lived experiences, and how we identify and address gaps in engagement, determines whether the data system truly reflects the diverse voices of a community. Community engagement and data management are deeply intertwined, and both must be approached with care, intention, and a commitment to the voices behind the numbers. To do that, we have to slow down.
At CB, we’ve learned that consistently showing up, listening deeply, and building relationships and trust through informal conversations matter just as much as structured outreach. One example of this is the Community Connectors model, which involves partnering with trusted community members to reach those who might otherwise be left out of traditional public processes. By partnering with trusted community members who already have strong local ties, we reached people who might otherwise be left out of traditional public processes. Meeting people in familiar spaces and engaging in culturally meaningful ways helped us gather richer, more representative insights.
(Below) Steven Garcia-Machuca presenting in Spanish about the One Community Project to a group of Spanish-speaking community leaders in Leadville.
This approach is part of a broader philosophy: effective engagement is relational, not transactional. Whether it’s hosting dialogues in community gathering spaces, showing up consistently at local events, or inviting feedback throughout the process, the goal is to create conditions where people feel seen, heard, and reflected in the outcomes. When trust is centered in our engagement, the data becomes more than input; it becomes a reflection of lived experience. This trust lays the groundwork for data that is not only more inclusive but also more meaningful and ultimately shapes plans and policies that are genuinely rooted in community voice.
(Below) The community input gathered through CB’s values engagement shapes future planning efforts. In some cases, these shared values are even brought to life through artwork.
Painting with Data
Analysis of qualitative community engagement data is like painting. Each comment, each survey response, is a brushstroke. A few brushstrokes might not shift the image, but changing a whole color on the palette can transform the picture.
Our job is to see how these individual strokes come together to form a cohesive, thematic image of a community’s voice. This image is only as accurate as the care we put into each step and our willingness to step back, reflect, and revise.
At each stage of the process, we are reminded that data is not just information. It reflects people’s lived experiences, full of complexity and emotion. Analyzing it well requires not only technical skill but also patience and creativity.
Through our work with CB, we’ve learned that the most powerful insights come from blending technical precision with human connection. By listening deeply, circling back, and getting feedback on our analysis, we build a more complete canvas—one that doesn’t just document community input but honors community voice.
Community engagement data is ultimately about people. And when we treat it that way, our systems become more inclusive, our engagement more meaningful, and our communities more connected.
(Left) Conner Borkowski (top left) at a Community Builders team retreat in January 2025. (Right) Steven Garcia-Machuca (front row, center) at the Community Builders team retreat in May 2025.
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