Are Healthtech Companies Underpricing? Using the Kano Model to Find Left-on-the-Table Value

Direct answer: Most digital health companies underprice because they anchor to a single "platform" or "per-seat" number and never separate the features buyers expect from the ones they'll pay a premium for. The Kano Model fixes this by sorting your product's capabilities into must-haves, performance drivers, and delight features — so you stop discounting the delighters and stop over-investing in must-haves nobody rewards. If your pricing is one flat tier and your roadmap treats every feature as equally valuable, you are almost certainly leaving money on the table.

Why Healthtech Pricing Breaks in Predictable Ways

Digital health pricing carries structural traps that don't exist in most B2B SaaS:

• The buyer, the payer, and the user are three different people. A clinician uses it, a health-system CIO buys it, and the reimbursement model (or an employer benefits budget) ultimately funds it. Value that thrills the user may be invisible to the person signing the contract.
• Compliance features feel valuable but rarely command a premium. HIPAA compliance, SOC 2, HITRUST, and audit logs are expected. Buyers don't pay extra for them — they walk away without them.
• Outcomes are the real currency. Reduced readmissions, faster prior auth, higher medication adherence, lower cost-per-episode. Yet many companies price on logins and modules instead of the outcomes those modules produce.

The result: healthtech founders bundle everything into one price, quietly subsidize expensive delight features with revenue from commodity must-haves, and cap their own ceiling.

The Kano Model, Applied to Digital Health

The Kano Model sorts every feature into categories based on how customer satisfaction responds to that feature being present or absent. For healthtech, the useful buckets are:

1. Must-be (Basic) features. Absence causes rejection; presence earns no gratitude. Examples: HIPAA compliance, EHR integration for a clinical tool, uptime, data security. Pricing implication: these belong in every tier. You cannot charge a premium for them, but their absence loses the deal.

2. Performance (One-dimensional) features. Satisfaction scales linearly with how much you deliver. Examples: number of EHR integrations, speed of prior-auth turnaround, breadth of analytics, response time of support. Pricing implication: these are your tiering axis. More of them justifies more money. This is where flat pricing bleeds value.

3. Attractive (Delight) features. Unexpected capabilities that create disproportionate satisfaction. Examples: AI-drafted clinical notes, predictive risk-stratification dashboards, automated payer-specific documentation, patient-facing engagement that measurably lifts adherence. Pricing implication: these are premium-tier or add-on candidates — and they're what you're most likely giving away for free.

4. Indifferent features. Nobody cares. Pricing implication: stop investing; don't build the tier around them.

5. Reverse features. Some users actively dislike them (e.g., excessive alerts creating clinician alarm fatigue). Pricing implication: removing them can be the value.

A concrete walkthrough

Step 1 — Inventory the features that matter to each stakeholder. Build a matrix: features down the side, and columns for clinician-user, economic buyer (CIO/CFO), and funder (payer/employer). A feature can be a delighter for the clinician but indifferent to the CFO — that's the crux of a mispricing.

Step 2 — Ask the Kano question pair for each feature, per segment. For every feature ask both a functional question ("How do you feel if this feature is present?") and a dysfunctional question ("How do you feel if it's absent?"). Answer choices: I like it / I expect it / I'm neutral / I can tolerate it / I dislike it. The combination of the two answers maps the feature into a Kano category. Run this with real buyers and users — not internally.

Step 3 — Cross-reference with willingness-to-pay. Kano tells you satisfaction sensitivity, not price. Pair it with a simple Van Westendorp or Gabor-Granger question for your delighters and performance features to bound the premium.

Step 4 — Redesign tiers. Must-bes anchor the base tier. Performance features scale the mid/enterprise tiers. Delighters become premium tiers or usage-based add-ons.

What "good" looks like: a base tier that no compliant buyer can refuse, a clear performance axis that maps to segment size or clinical complexity, and at least one delight feature you were previously giving away now packaged as a paid upgrade with a defensible willingness-to-pay range.

Where Percision Fits — and Where It Doesn't

Full disclosure: I write for Percision, an AI strategic intelligence platform, so weigh that accordingly.

Percision runs your business context through structured reasoning steps across 27+ frameworks — including Kano — and produces board-ready output in roughly 7–15 minutes rather than the weeks a pricing engagement typically takes. For a healthtech pricing question, it's useful for: structuring the Kano categorization across your stakeholder segments, stress-testing tier logic, modeling the revenue impact of repackaging delighters (with Excel-exportable models and audit trails), and generating the board deck to defend the change. It's a co-pilot — your leadership team makes the pricing call.

When you don't need it: If you have one product, one buyer persona, and three features, a spreadsheet and a week of customer calls will do the job. Kano's real leverage shows up when you have multiple stakeholders and a feature set complex enough to hide the mispricing — which is where speed and structure earn their keep.

When to hire a human consultant instead: If your pricing change hinges on payer contract renegotiation, value-based care economics, or reimbursement code strategy, you need a domain specialist who lives in CMS rules and payer dynamics. No AI tool replaces that. Use the framework to structure the product-value question; use a consultant for the reimbursement question.

On the AI-productivity question generally: a 2023 Harvard Business School / BCG field study found consultants using GPT-4 completed tasks faster and at higher quality within the tool's capability — but performed worse on tasks outside it. Pricing strategy needs the human in the loop, which is the posture we take.

You can run a first-pass Kano and pricing analysis at percision.app.

FAQ

Q: How many customers do I need to survey for a valid Kano analysis? There's no fixed threshold, but you want enough responses per segment to see stable category patterns — often a few dozen per key segment. In healthtech, segment by stakeholder role, not just company, because their answers diverge.

Q: Won't repackaging existing free features anger current customers? Grandfather existing accounts and apply new tiering to renewals and new logos. The risk is real; the fix is sequencing, not avoidance.

Q: Can Kano tell me the actual price to charge? No. Kano tells you what to charge extra for. Pair it with a willingness-to-pay method (Van Westendorp, Gabor-Granger, or conjoint) to set the number.