Buy a feature

Buy a Feature is an innovation game developed by Luke Hohmann for gathering customer input on prioritization. Participants receive a limited budget of play money and "purchase" the features they want most from a list with assigned prices. The constraint forces trade-offs, revealing what people truly value. When done with groups, it also drives collaboration and exposes different perspectives.

Why it matters

Asking customers what features they want typically produces long wish lists where everything is important. This isn't useful for prioritization. Buy a Feature solves this problem by introducing scarcity-participants can't have everything, so they must choose.

The game also surfaces information that surveys miss. When people discuss why they're buying certain features, you hear their reasoning. When they collaborate to pool money for expensive features, you see what they'll sacrifice to get what matters most.

How it works

Create a list of features or potential investments. Each item should be clearly described in terms customers understand. Assign prices based roughly on development cost or strategic importance-expensive items should require collaboration or significant sacrifice.

Give participants play money-typically enough to buy 3-4 average items or collaborate with others for expensive ones. Prices should be set so no individual can buy everything they want.

Let participants shop. They allocate their money to features they want. This can happen simultaneously (everyone places money at once) or through rounds where people make choices and observe what others are doing.

Facilitate discussion. The valuable insight often comes not from where money lands but from the conversations: why did you choose that? What would you give up to get this? Why is this feature not worth it to you?

Running a session

Participants should be actual customers or users, not internal proxies. The insight comes from real customer preferences, not what you imagine customers want.

Group size of 4-8 participants works well for in-person sessions. Larger groups can split into sub-groups. Online versions can handle more participants but sacrifice some of the collaborative discussion.

Feature list should include 15-25 items to provide meaningful choice without overwhelming participants. Include a mix of sizes and prices.

Pricing strategy matters. If everything is cheap, everyone gets what they want and no trade-offs occur. If everything is expensive, collaboration becomes mandatory. Price strategically to force the choices you want to understand.

Facilitation should encourage discussion without leading. Ask open-ended questions: "Tell me why you chose that." "What would have to change for you to buy this one?" "Would anyone give up something to pool money for this?"

What you learn

Feature priority emerges from where money concentrates. Items that receive investment from multiple participants are broadly valued. Items that no one buys may be solutions looking for problems.

Customer segments become visible when different groups buy differently. If enterprise customers consistently buy different features than small business customers, you've learned something about segmentation.

Willingness to sacrifice shows intensity of preference. Someone who spends most of their budget on one feature wants it badly. Someone who spreads money across many items has moderate preferences.

Collaboration patterns reveal what's important enough to work together for. When participants spontaneously pool resources for an expensive feature, it signals strong collective value.

Variations

Online versions use digital tools to run the game asynchronously or with geographically distributed participants. You lose some collaborative energy but can reach more people.

Internal versions use the same mechanic with internal stakeholders. Product managers, sales, support, and engineering each "buy" priorities from their perspective. This surfaces alignment and disagreement.

Budget variations can assign different budgets to different participants, simulating the varying influence of different customer segments.

Multiple rounds allow you to see how choices evolve as participants learn from each other or as options change.

Making results useful

Don't treat Buy a Feature results as votes that directly determine your roadmap. The game provides input, not decisions. Participants don't know everything-technical feasibility, strategic context, or what other customers value.

Instead, use results to:

The conversations around the game often provide more insight than the numerical results.

Limitations

Small samples mean results may not represent your full customer base. Buy a Feature with 6 participants tells you what those 6 people value, which may or may not generalize.

Framing effects influence results. How you describe features and price them affects choices. Be thoughtful about presentation.

Present bias means participants choose based on current needs, which may not match future direction. They optimize for known problems, not emerging opportunities.

Social influence in group settings means some participants follow others rather than expressing independent preferences. Facilitation can mitigate this.

Despite limitations, Buy a Feature provides richer input than simple surveys while remaining accessible to participants without research backgrounds.

Connecting to product process

Buy a Feature works well as one input to product discovery. Combine it with other research methods-interviews, observation, usage data-to build a complete picture.

Klero helps connect prioritization exercises like Buy a Feature to ongoing customer feedback. When you can see how feature requests align with what customers consistently ask for, prioritization becomes more confident.