Buy a Feature Results · November 19, 2025 · 15 Participants
Traditional prioritization produces misleading results - everyone votes "high priority" and the loudest voices win. This Buy a Feature analysis forced real trade-offs with constrained budgets, validated across two independent groups. When both groups fund the same features (6 achieved this), you have cross-validated priorities you can trust. This page shows what customers prioritized, why it matters, and how consensus formed over 60 minutes, giving you confidence to allocate development resources. Learn why this methodology is trusted.
What the data reveals about priorities, surprises, and cross-group patterns
This analysis combines behavioral evidence (what customers actually funded) with discussion context (what customers talked about) to reveal patterns you can't see from either data source alone. By mapping features across both dimensions, you gain confidence in your decisions - understanding where customers show strong consensus, where behavior and conversation align, and where passionate voices may not represent broader needs. This integrated view helps you make customer-aligned choices backed by multiple forms of validation. See pattern detection methods.
Point size represents funding percentage. Hover over any feature for detailed metrics. ⭐ = Exceeded expectations | 📉 = Below expectations
Silent Priorities (high funding, limited discussion) reveal strong consensus - features customers want without needing convincing.
Aligned Priorities (high funding, strong discussion) show validated decisions where behavior and conversation reinforce each other.
Vocal Minorities (limited funding, significant discussion) help you understand passionate perspectives that may not represent broader customer needs.
Overlooked Features (limited funding, limited discussion) are not currently prioritized by the group.
Ranked by Area Under Curve (AUC) - a measure of sustained funding over time
Area Under Curve (AUC) measures sustained commitment over time, not just final percentages, filtering out tactical gaming and last-minute adjustments. High AUC means participants allocated budget early and kept it there through 60 minutes of discussion. Consensus indicators show cross-group validation: when both groups independently prioritize the same features, that's as close to "safe bet" as prioritization gets. Six features achieved 100% funding with high consensus. See the AUC methodology.
| Rank | Feature | AUC Score | % Funded |
|---|
How feature funding evolved throughout the 60-minute session
Features funded early and consistently show genuine conviction - no persuasion needed. Features funded late might indicate negotiation or compromise. This distinction matters: features with strong early consensus are safer roadmap investments with built-in stakeholder support. Volatile or late-shifting patterns warrant investigation before committing resources. This temporal dimension is unique to event-tracked Buy a Feature sessions. Learn about temporal validation.
6 themes emerged from customer feedback and discussion
Two features might both reach 100% funding, but if one addresses urgent pain (retention risk) and another enables differentiation (growth opportunity), they deserve different implementation approaches. This systematic thematic analysis, coded across facilitator notes, feedback forms, and transcripts, reveals the why behind the numbers. Seven themes emerged, each grounded in direct participant quotes, not analyst interpretation. See our thematic coding process.
Each finding met three criteria: (1) statistically significant across groups, (2) actionable for roadmap planning, and (3) validated through multiple methods. Trustworthiness comes from triangulation - when quantitative funding, qualitative themes, and temporal patterns all point the same direction, you can confidently act. These findings give you permission to make investment decisions and explain them to leadership. Understand our synthesis approach.