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Case study

AI Software Pricing Strategy for a Healthcare Startup

How a cancer detection AI doubled expected prices and unlocked new market segments

About the project

A healthcare startup had developed innovative AI software designed to reduce false positives and negatives in critical cancer detection. The technology was groundbreaking, but the team was uncertain about its perceived value and the optimal pricing strategy. Getting this right mattered for revenue and for demonstrating market potential to Series A investors.

The challenge
  • Unclear perceived value among the target audience of healthcare professionals.
  • No data on the optimal price point or packaging to maximise adoption.
  • Needed to validate pricing potential for both investors and commercial success.
The solution

Three strategic moves.

Action
Impact
Established value hypotheses from internal evaluations and healthcare research
Created a data-driven foundation for pricing decisions.
Conducted an external market survey with advanced research methods
Tested various packages and price points with potential users.
Focused on the expected primary market's preferences
Kept pricing aligned with real-world adoption drivers.
Validation

The market survey delivered exceptional insights:

  • The concept test generated extraordinarily high interest, ranking in the top five the consultant had ever seen.
  • Optimal pricing was found to be roughly twice as high as initially anticipated.
  • Identified an opportunity for a lower-value tier to capture a broader segment.
The results
Metric
Result
Price potential
Doubled initial expectations
Market interest
Top 5 concept test result
Market reach
Expanded with a new lower-tier option

We knew our AI could make a difference, but we had no idea how much value healthcare professionals would assign to it. The data showed we could price it far higher than we dared hope, and still capture even more of the market.

CEO, Healthcare AI Startup

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