Prioritization Games - Buy a Feature

In Brief

Buy a Feature is an Innovation Game developed by Luke Hohmann where participants receive a limited budget of play money and must decide which features to purchase from a priced list. By giving each participant only enough money to buy one-third to two-thirds of the available features, the exercise introduces economic scarcity that forces genuine trade-offs. The most revealing dynamic occurs when expensive features require multiple participants to pool their money, sparking negotiation and coalition-building that surfaces true priorities and the reasoning behind them.

The conversations that happen during the game — the debates, the compromises, the lobbying — are as valuable as the final purchasing decisions. These conversations reveal not just what customers want, but why they want it and how much they are willing to sacrifice for it.

Description

Buy a Feature works by introducing the core mechanism of economic decision-making: scarcity. In real markets, customers cannot have everything — they allocate limited resources toward their highest priorities. By simulating this constraint with play money, the game produces behavior that mirrors real purchasing decisions far more closely than any rating scale or ranking exercise.

The design of the game creates three distinct layers of insight:

1. Individual priorities. What each participant chooses to buy with their own money reveals their personal must-haves.
2. Negotiation behavior. When expensive features require pooling money, participants must persuade others to join them. The arguments they make and the compromises they accept reveal the depth of their commitment.
3. Feature abandonment. What participants choose not to buy — even when they could afford it — reveals features that sound nice but are not worth the trade-off.

How to

Prep AI Prompt

1. Build the feature list.

Write fourteen to thirty candidate features on cards, a poster, or a handout. Each feature gets a clear name, a one-sentence description, and a price. Hohmann’s Innovation Games recommends keeping the list in this range — long enough to force trade-offs, short enough that participants can hold the whole set in their head. Use customer-facing language, not internal codenames.

2. Set prices to provoke trade-offs, not to model engineering cost.

Pricing is the single most important design choice. Hohmann’s rule: at least one or two features should be priced high enough that no single customer can buy them alone. That forces coalition-building, which is where the richest insight lives. ProductPlan’s practitioner glossary frames the same rule qualitatively — features should be priced to push customers into negotiation, not to teach them about your engineering effort.

A workable distribution for a fourteen-to-thirty feature list:

• Five to ten low-priced features that any participant can afford.
• Five to twelve medium-priced features that require trading off other purchases.
• Four to eight high-priced features that require two to four participants to pool money.

Use round numbers so participants can do the math in their heads.

3. Distribute play money.

Each participant receives the same budget — enough to buy roughly one-third to two-thirds of the total feature value if they spent only on cheap features. Hohmann’s original framing: scarcity is the mechanism that produces honest signal, so the budget must be tight enough that participants cannot have everything. Print bills, use poker chips, or hand out paper certificates — whatever holds up to being passed back and forth on a table.

4. Recruit four to seven participants per group.

Hohmann recommends four to seven customers per group: small enough that everyone has to talk, large enough that coalitions can form. UX for the Masses’ practitioner walkthrough echoes the same range. Run multiple groups if you have access to more than seven customers — convergent results across groups carry far more weight than a single session.

5. Draft the rules sheet.

Write the rules out so the facilitator can read them verbatim. The core rules:

• “You have $X to spend on the features in front of you.”
• “You can buy any feature you can afford on your own.”
• “You can pool money with other participants to buy a feature together.”
• “You do not get change. Leftover money has no value.”
• “You have forty-five minutes.”

Analysis AI Prompt

Analyze results across several dimensions:

• Most-purchased features are clear priorities. If a feature was bought across multiple groups, it is a strong roadmap candidate.
• Features that inspired pooling are aspirational and high-value. These often represent capabilities that could become key differentiators — and the negotiation around them tells you which segments will fund them.
• Features no one bought are candidates for cutting from the roadmap, regardless of how much engineering effort has already been invested.
• Negotiation patterns reveal segment dynamics. If certain participants consistently lobbied for the same features, they may represent a distinct customer segment with shared priorities.
• Leftover money tells you about satisfaction with the available options. If participants consistently had unspent money at the end, the feature list may be missing something important — go back to generative interviews to find it.