Comparing by fit
Two ways of thinking, side by side. There is no winner here — read across each row and choose the one that fits your situation.
Innovation
Not all features are equal: some delight, some merely satisfy, and some only hurt when missing.
By 6days
Product
People don't buy products, they hire them for a job — find out what the job is.
By 6days
When to use — Kano Model
Use it when a roadmap needs to balance table-stakes against differentiation, when entering an established category where expectations are already set, or when heavy feature investment is somehow producing no measurable satisfaction gain.
When to use — Jobs To Be Done
Use it when demographic segmentation has stopped generating insight, when you cannot explain why customers churn or convert, when entering an adjacent market, or when a roadmap has become a queue of the loudest requests with no organising logic.
When not to use — Kano Model
Avoid it in a genuinely new category, where customers have no expectations to classify against and the survey returns noise. It is survey-based, so it inherits every weakness of stated preference — people are poor predictors of their own delight. It is also expensive to run properly and stale quickly; a three-year-old Kano study is a historical document.
When not to use — Jobs To Be Done
Avoid it for incremental optimisation of a well-understood product — you know the job, and reopening it is procrastination. It is weak for infrastructure and compliance work with no discretionary hiring decision. Done badly it collapses into vague poetry about customer aspirations, and 'the job' becomes whatever the loudest person already wanted, now with better rhetoric.
Teams treat features as a single list ranked by how much customers say they want them. But customer satisfaction does not respond linearly to features. Some things generate no goodwill when present and fury when absent. Some delight now and will be unremarkable in two years. Ranking everything on a single 'wanted' axis guarantees you will over-invest in things that cannot make anyone happy and under-invest in the ones that can.
Teams describe customers demographically and build for the description. But 'marketing managers aged 30-45' do not share a need; they share a census category. So the roadmap fills with features requested by whoever asked loudest, competitors are defined as companies that look like you, and the actual reason people started or stopped using the product remains a mystery — because nobody asked about the situation that triggered the switch.
The Kano model sorts features by how their presence and absence affect satisfaction, producing distinct categories rather than one ranking. Must-be features are invisible when present and damaging when missing — nobody praises an aircraft for landing. Performance features scale: more is better, roughly linearly. Attractive features delight when present but are not missed when absent, because customers never expected them. Indifferent features move nothing. The model's sharpest insight is temporal: today's delighter becomes tomorrow's expectation, so categories decay and must be re-measured.
Jobs To Be Done reframes demand around the progress a customer is trying to make in a particular circumstance. People 'hire' a product to get a job done, and 'fire' it when something does the job better. The job is stable over time while the solutions churn — the job of getting a household's laundry clean has outlived every washing technology that ever served it. The reframe has two sharp consequences: your real competitor is anything else hired for the same job, including a spreadsheet or doing nothing at all, and the useful research question is not 'what do you want?' but 'walk me through the last time you switched.'
List the features to evaluate in customer-meaningful terms. If a customer cannot tell whether they have it, it cannot be classified — internal work does not belong in this exercise.
For every feature ask two questions: how would you feel if it were present, and how would you feel if it were absent? The pair is the entire mechanism. Asking only the first turns the survey into a wish list, which is the thing you are trying to escape.
Map each respondent's pair to a category. 'Like it if present, expect it if absent' is attractive; 'expect it if present, dislike if absent' is must-be; 'like if present, dislike if absent' is performance. Contradictory answers usually mean the question was ambiguous rather than the customer confused.
Look at the distribution rather than the average, and split by customer type. A feature that is must-be for enterprise buyers and indifferent to individuals will average to 'performance' — a category that describes nobody and misleads everyone.
Worked example — Kano Model
A hotel books group evaluates features. Hot water and a clean room: must-be — no guest has ever left a five-star review for functioning plumbing, and every guest leaves a one-star review for its absence. Wi-Fi speed: performance, and now the primary driver of business-traveller ratings. A handwritten note from the manager: attractive, delights disproportionately, costs almost nothing, and nobody misses it if it is absent. Same-day laundry: indifferent for this segment. The finding that changes behaviour is that Wi-Fi has migrated from attractive to performance in under a decade and is drifting toward must-be — the investment case for it is not about delight any more, it is about avoiding damage.
Worked example — Jobs To Be Done
A team building invoicing software for freelancers assumes the job is 'create professional invoices' and invests in templates and branding. Switch interviews tell a different story: nobody switched for a nicer invoice. They switched after a client paid late and an awkward chasing conversation followed. The real job is 'get paid without having to ask twice.' The competitors are not other invoicing tools but the freelancer's own dread of chasing. The roadmap turns to automated reminders, payment-status visibility, and gentle escalation wording — none of which was on the template-driven plan, and all of which address the trigger that actually moves people.
The model was developed by Noriaki Kano and colleagues at the Tokyo University of Science around 1980, within the Japanese quality management tradition that also produced much of modern quality function deployment. Its academic origin gives it an unusually explicit methodology — the paired question format and classification table are part of the original work rather than later additions.
The framing is most associated with Clayton Christensen, who popularised it from the mid-2000s alongside collaborators including Bob Moesta and Rick Pedi, and it connects to earlier outcome-driven work by Anthony Ulwick. Several schools now interpret it differently — some treating jobs as functional specifications, others as situational narratives — and the disagreement between them is genuine rather than cosmetic.
Cover every must-be adequately before investing anywhere else — they are hygiene and no amount of delight offsets a missing one. Then compete on selected performance features and invest in a small number of attractive ones. Re-run periodically, because the categories will have moved.
Find customers who recently started or stopped using something, and reconstruct the episode in detail: what happened, what they tried, what finally pushed them. Anchor on a specific event. General preference questions produce a plausible story rather than a true one.
Identify the circumstance that made the old way intolerable on that particular day. People tolerate bad solutions for years; something specific changed. That trigger, not the feature comparison, is what actually created the sale.
State it as circumstance plus motivation plus desired outcome — 'when a client emails a change at 6pm, help me update the quote without reopening the whole file, so I can leave on time.' No product nouns. If your solution is in the sentence, you have written a feature request instead.
List everything currently hired for that job — rival products, a spreadsheet, an assistant, an established habit, doing nothing. The incumbent is almost never the company you benchmark against, and the status quo is the most common winner.
For each planned feature, ask which job it serves and whether it beats the current hire for that job. Features that serve no articulated job are the ones to cut, and the exercise usually finds several.