“Is this a must-have, a nice-to-have, or something you don't really care about?”
From Madhavan Ramanujam · Partner at Simon-Kucher; author of Monetizing Innovation
Why it works
This is the value-tiering question behind Ramanujam's feature classification: every product is a bundle of unequal features, and they fall into leaders, fillers, and killers. Leaders are the high-value features that drive the purchase decision and willingness to pay — your must-haves. Fillers enhance the product but aren't why anyone buys — nice-to-haves. Killers are features people don't value and that can even sour the offer if they're forced to pay for them — the 'don't care' answers, and the ones to keep out of the core. Asking people to sort a feature into those three buckets is faster and more honest than asking them to rank a long list, because the verdict is categorical: a must-have is a different kind of thing from a nice-to-have, and the split tells you where to concentrate the product and the price.
When to ask
While deciding what to build, package, or charge for. Ask it of each feature or concept you're weighing, with people who'd actually use them — the answers tell you which features to lead with and which to drop.
Good follow-ups
- If it's a must-have, what would you do without it?
- Which one feature, gone, would make you walk away?
- What did you assume it does when you answered?
Watch out for
Confusing this with the price question — it sorts value, not dollars; a must-have still needs the willingness-to-pay conversation to become a number. Watch for everything-is-a-must-have inflation: when people pay nothing to answer, they over-claim, so weight the signal toward features almost nobody calls a must-have (likely killers) and the few that almost everybody does (your leaders). And don't ask it about a feature so vaguely described that 'nice-to-have' just means 'I didn't understand it.'
Where to ask
- In-product surveygreat
A three-option pick reads instantly and tallies cleanly across a sample — exactly the shape you want for sorting features by value.
- Long-form surveygreat
Travels well in an emailed study; ask it per feature or per concept and the must-have share is a comparable number you can rank.
- User interviewworkable
Useful live to force a verdict and then ask why — but a single person's must-have is anecdote; the value test only sorts at sample size.
Stage: Consider · A question popularized by Madhavan Ramanujam
Source: https://www.simon-kucher.com/en/insights/value-monetization-age-ai