How to Improve Medibuddy’s Lab Discovery

ℹ️ About the project

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As a hypothetical Product Manager of Medibuddy, I was tasked to improve Lab Discovery of the platform

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🪜 Approach

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Goal → User Intent Segmentation → Decision Friction Identification→ Design Principles→ Dual Path Solution→ Prioritization

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Goal

To reduce decision paralysis and increase successful lab test bookings on MediBuddy, as user confidence in choosing the right diagnostic test is critical for conversion and long term trust in healthcare platforms.

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Problem Statement

MediBuddy's lab discovery experience suffers not from lack of user intent, but from decision paralysis and systematic friction points that cause users to abandon the booking process.

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Users struggle to:

• Understand medical jargon
• Decide between individual tests vs packages
• Trust whether they are booking the right test for their situation </aside>

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As a result:

• Users drop off before booking, OR
• Book incorrect or over inclusive tests, leading to poor experience and low trust </aside>

Key Insight

Lab discovery is a decision-confidence problem, not a search problem.

Users are anxious because medical decisions feel high stakes and irreversible. The product must reduce the fear of choosing incorrectly, not just improve navigation.

Assumptions (Explicit & Testable)

User Assumptions

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🧠 Mental Model

Users do not think in medical test names; they think in symptoms, goals, or doctor instructions.

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🏥Medical Literacy

Most users lack medical literacy and find clinical jargon intimidating.

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😨User Fears

• Booking the wrong test
• Overpaying for unnecessary tests
• Misinterpreting results </aside>

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📜Prescription Users

Users with prescriptions want speed and accuracy, not discovery.

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🤗Trust Drivers

Trust in healthcare products is driven more by clarity and reassurance than by price alone.

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