Medikou
Enabling seamless clinic discovery with confidence
Role
Product Designer
Deliverables
User Research, Product Strategy, Journey Mapping, High Fidelity Prototyping, A/B Testing
Project Timeline
1 year
Medikou
Enabling seamless clinic discovery with confidence
Role
Product Designer
Deliverables
User Research, Product Strategy, Journey Mapping, High Fidelity Prototyping, A/B Testing
Project Timeline
1 year
Medikou
Enabling seamless clinic discovery with confidence
Role
Product Designer
Deliverables
User Research, Product Strategy, Journey Mapping, High Fidelity Prototyping, A/B Testing
Project Timeline
1 year
Overview
The Japanese health system for patients is overwhelming because users have 180,000 clinics to choose from. Medikou helps young Japanese citizens find the best-fit medical clinics in Japan. The goal was to increase user satisfaction by improving users’ interaction to discover new clinics measured by an NPS of 7 through conducting data-informed user interviews, prioritization mapping, rapid prototyping and A/B testing to measure our design impact.
Overview
The Japanese health system for patients is overwhelming because users have 180,000 clinics to choose from. Medikou helps young Japanese citizens find the best-fit medical clinics in Japan. The goal was to increase user satisfaction by improving users’ interaction to discover new clinics measured by an NPS of 7 through conducting data-informed user interviews, prioritization mapping, rapid prototyping and A/B testing to measure our design impact.
Overview
The Japanese health system for patients is overwhelming because users have 180,000 clinics to choose from. Medikou helps young Japanese citizens find the best-fit medical clinics in Japan. The goal was to increase user satisfaction by improving users’ interaction to discover new clinics measured by an NPS of 7 through conducting data-informed user interviews, prioritization mapping, rapid prototyping and A/B testing to measure our design impact.
Challenge
Time and Mental Strain involved in finding doctors in Japan
In 2021, users have access to over 180k clinic options ranging from preventative to specialty healthcare. These options are overwhelming and users spend an average of 12 minutes to inspect a clinic’s homepage, learn about their services and book an appointment for visitation.
Users are frustrated with the current clinic discovery process
Members are physically burdened with clicking through 1M+ search results to find a suitable clinic to address their needs
Time and Mental Strain involved in finding doctors in Japan
In 2021, users have access to over 180k clinic options ranging from preventative to specialty healthcare. These options are overwhelming and users spend an average of 12 minutes to inspect a clinic’s homepage, learn about their services and book an appointment for visitation.
Users are frustrated with the current clinic discovery process
Members are physically burdened with clicking through 1M+ search results to find a suitable clinic to address their needs
Time and Mental Strain involved in finding doctors in Japan
In 2021, users have access to over 180k clinic options ranging from preventative to specialty healthcare. These options are overwhelming and users spend an average of 12 minutes to inspect a clinic’s homepage, learn about their services and book an appointment for visitation.
Users are frustrated with the current clinic discovery process
Members are physically burdened with clicking through 1M+ search results to find a suitable clinic to address their needs
Research
Understanding Clinic Search Patterns in Japan
Upon concluding our research study, we determined our primary target users were young adults (age 22-35) when considering factors related to digital maturity and technological competency.
In order to identify who our targets were and their pain points, we structured our research interviews after reviewing a medical publication that surveyed 1000 participants nationwide regarding existing patient problems with clinics. To understand user behaviour, 20 user interviews were conducted by inquiring about users’ current search flow, information prioritization and decision-making during their clinic discovery phase.
Research Takeaways
55.8%
Users used Google as their main discovery channel
75%
Users focused on clinic reputation as a means of filtering
72.1%
Users displayed similar clinic information prioritization patterns
80%
Users don’t book an appointment within their first search attempt
Collecting Insights
Customers are physically burdened with clicking through 1M+ search results to find a suitable clinic to address their needs
Defining core user flows
To ensure a user-friendly and efficient mobile experience for customers, research insights were used to inform the visualization of the appointment flow to be designed.
Understanding Clinic Search Patterns in Japan
Upon concluding our research study, we determined our primary target users were young adults (age 22-35) when considering factors related to digital maturity and technological competency.
In order to identify who our targets were and their pain points, we structured our research interviews after reviewing a medical publication that surveyed 1000 participants nationwide regarding existing patient problems with clinics. To understand user behaviour, 20 user interviews were conducted by inquiring about users’ current search flow, information prioritization and decision-making during their clinic discovery phase.
Research Takeaways
55.8%
Users used Google as their main discovery channel
72.1%
Users displayed similar clinic information prioritization patterns
75%
Users focused on clinic reputation as a means of filtering
80%
Users don’t book an appointment within their first search attempt
Collecting Insights
Customers are physically burdened with clicking through 1M+ search results to find a suitable clinic to address their needs
Defining core user flows
To ensure a user-friendly and efficient mobile experience for customers, research insights were used to inform the visualization of the appointment flow to be designed.
Understanding Clinic Search Patterns in Japan
Upon concluding our research study, we determined our primary target users were young adults (age 22-35) when considering factors related to digital maturity and technological competency.
In order to identify who our targets were and their pain points, we structured our research interviews after reviewing a medical publication that surveyed 1000 participants nationwide regarding existing patient problems with clinics. To understand user behaviour, 20 user interviews were conducted by inquiring about users’ current search flow, information prioritization and decision-making during their clinic discovery phase.
Research Takeaways
55.8%
Users used Google as their main discovery channel
72.1%
Users displayed similar clinic information prioritization patterns
75%
Users focused on clinic reputation as a means of filtering
80%
Users don’t book an appointment within their first search attempt
Collecting Insights
Customers are physically burdened with clicking through 1M+ search results to find a suitable clinic to address their needs
Defining core user flows
To ensure a user-friendly and efficient mobile experience for customers, research insights were used to inform the visualization of the appointment flow to be designed.
Exploration
Translating our findings into opportunities
By prioritizing the core features using our insights, mid-fi prototypes were created to conduct A/B testing and inform design iterations.
With our target user group in mind, the collected insights were used to prioritize features to design for MVP.
Clinic Ratings
From data that showed hospital reputation was highly valued among users, we ideated on 2 variations of representing credibility and prioritized on increasing visibility of well-reviewed clinics to increase users’ confidence.
Search and Filtering
Research data on user search patterns led to prioritizing a home-screen where users could select their preferences to reduce search results pool based on clinic type, location and availability. As a secondary means of searching, a standard search bar for users to manually input their symptoms and location.
Appointment booking
Our data insights regarding clinic availability led us to prioritize ideating on surfacing information that meets users’ minimum needs to book an appointment first such as services provided, address, clinic websites alongside the appointment booking flow itself.
Touch-point visualization
With emphasis on core functionality of features to deliver to customers, we quickly jumped from lo-fi to mid-fi wireframe to quickly explore multiple ideas without over-investing in visuals.
Home-page Content
Keeping users involved throughout the ideation phase helped us validate our ideation from research data-points, reducing un-necessary features that don’t deliver value to our customers.
Information hierarchy
Heavy exploration on clinic cards and corresponding visual hierarchy that closely aligns with user mental models to reduce cognitive load and surface key information that brings users closer to finding relevant clinics.
Translating our findings into opportunities
By prioritizing the core features using our insights, mid-fi prototypes were created to conduct A/B testing and inform design iterations.
With our target user group in mind, the collected insights were used to prioritize features to design for MVP.
Clinic Ratings
From data that showed hospital reputation was highly valued among users, we ideated on 2 variations of representing credibility and prioritized on increasing visibility of well-reviewed clinics to increase users’ confidence.
Search and Filtering
Research data on user search patterns led to prioritizing a home-screen where users could select their preferences to reduce search results pool based on clinic type, location and availability. As a secondary means of searching, a standard search bar for users to manually input their symptoms and location.
Appointment booking
Our data insights regarding clinic availability led us to prioritize ideating on surfacing information that meets users’ minimum needs to book an appointment first such as services provided, address, clinic websites alongside the appointment booking flow itself.
Touch-point visualization
With emphasis on core functionality of features to deliver to customers, we quickly jumped from lo-fi to mid-fi wireframe to quickly explore multiple ideas without over-investing in visuals.
Home-page Content
Keeping users involved throughout the ideation phase helped us validate our ideation from research data-points, reducing un-necessary features that don’t deliver value to our customers.
Information hierarchy
Heavy exploration on clinic cards and corresponding visual hierarchy that closely aligns with user mental models to reduce cognitive load and surface key information that brings users closer to finding relevant clinics.
Translating our findings into opportunities
By prioritizing the core features using our insights, mid-fi prototypes were created to conduct A/B testing and inform design iterations.
With our target user group in mind, the collected insights were used to prioritize features to design for MVP.
Clinic Ratings
From data that showed hospital reputation was highly valued among users, we ideated on 2 variations of representing credibility and prioritized on increasing visibility of well-reviewed clinics to increase users’ confidence.
Search and Filtering
Research data on user search patterns led to prioritizing a home-screen where users could select their preferences to reduce search results pool based on clinic type, location and availability. As a secondary means of searching, a standard search bar for users to manually input their symptoms and location.
Appointment booking
Our data insights regarding clinic availability led us to prioritize ideating on surfacing information that meets users’ minimum needs to book an appointment first such as services provided, address, clinic websites alongside the appointment booking flow itself.
Touch-point visualization
With emphasis on core functionality of features to deliver to customers, we quickly jumped from lo-fi to mid-fi wireframe to quickly explore multiple ideas without over-investing in visuals.
Home-page Content
Keeping users involved throughout the ideation phase helped us validate our ideation from research data-points, reducing un-necessary features that don’t deliver value to our customers.
Information hierarchy
Heavy exploration on clinic cards and corresponding visual hierarchy that closely aligns with user mental models to reduce cognitive load and surface key information that brings users closer to finding relevant clinics.
Iteration
Using Data to lead our Design Decisions
In order to quickly evaluate high priority deliverables within a short timeframe, we went through 4 prototyping iterations and 12 A/B testing sessions.
Testing the limits of information capacity
Iterating on clinic cards were prioritized as they reflect key details such as rating, location and availability that guide users to appointment booking. After user testing, we found 80% of users weren’t convinced by rating score alone and sought out review counts to support the rating validity.
Factoring the situation at hand when designing
We deprioritized presenting clinic cards early in the search flow as “recommended clinics” to increase booking rates because 90% of users did not trust the suggestions due to the timing within the task flow.
Booking with clinics was not feasible
Based on a survey feedback that was sent to 8 clinics in Tokyo during the research phase, we deprioritized the appointment booking flow. Since medical facilities across Japan had varying appointment management software, we prioritized providing users with the information to contact and book with directly clinics for this development phase.
Descope on Homepage content
Ensuring that all copy was informative and instructive resulted in an increase in search conversion by 70%. Utilizing usability testing insights, we were able to iterate on an alternative search method that further improved search conversion rates and reduced time on task by 30%.
Refining Clinic Card Hierarchy
Surfacing relevant information that closely aligned with user mental models based on feedback resulted in users finding helpful clinics quicker, resulting in a 30% increase in booking rate.
Pivoting Appointment Booking Flow
Adapting quickly to new research data, bringing users to the clinic help-desk quickly and aligning the visual hierarchy of information based on user feedback resulted in 40% increase in booking rates from the 1st iteration.
Using Data to lead our Design Decisions
In order to quickly evaluate high priority deliverables within a short timeframe, we went through 4 prototyping iterations and 12 A/B testing sessions.
Testing the limits of information capacity
Iterating on clinic cards were prioritized as they reflect key details such as rating, location and availability that guide users to appointment booking. After user testing, we found 80% of users weren’t convinced by rating score alone and sought out review counts to support the rating validity.
Factoring the situation at hand when designing
We deprioritized presenting clinic cards early in the search flow as “recommended clinics” to increase booking rates because 90% of users did not trust the suggestions due to the timing within the task flow.
Booking with clinics was not feasible
Based on a survey feedback that was sent to 8 clinics in Tokyo during the research phase, we deprioritized the appointment booking flow. Since medical facilities across Japan had varying appointment management software, we prioritized providing users with the information to contact and book with directly clinics for this development phase.
Descope on Homepage content
Ensuring that all copy was informative and instructive resulted in an increase in search conversion by 70%. Utilizing usability testing insights, we were able to iterate on an alternative search method that further improved search conversion rates and reduced time on task by 30%.
Refining Clinic Card Hierarchy
Surfacing relevant information that closely aligned with user mental models based on feedback resulted in users finding helpful clinics quicker, resulting in a 30% increase in booking rate.
Pivoting Appointment Booking Flow
Adapting quickly to new research data, bringing users to the clinic help-desk quickly and aligning the visual hierarchy of information based on user feedback resulted in 40% increase in booking rates from the 1st iteration.
Using Data to lead our Design Decisions
In order to quickly evaluate high priority deliverables within a short timeframe, we went through 4 prototyping iterations and 12 A/B testing sessions.
Testing the limits of information capacity
Iterating on clinic cards were prioritized as they reflect key details such as rating, location and availability that guide users to appointment booking. After user testing, we found 80% of users weren’t convinced by rating score alone and sought out review counts to support the rating validity.
Factoring the situation at hand when designing
We deprioritized presenting clinic cards early in the search flow as “recommended clinics” to increase booking rates because 90% of users did not trust the suggestions due to the timing within the task flow.
Booking with clinics was not feasible
Based on a survey feedback that was sent to 8 clinics in Tokyo during the research phase, we deprioritized the appointment booking flow. Since medical facilities across Japan had varying appointment management software, we prioritized providing users with the information to contact and book with directly clinics for this development phase.
Descope on Homepage content
Ensuring that all copy was informative and instructive resulted in an increase in search conversion by 70%. Utilizing usability testing insights, we were able to iterate on an alternative search method that further improved search conversion rates and reduced time on task by 30%.
Refining Clinic Card Hierarchy
Surfacing relevant information that closely aligned with user mental models based on feedback resulted in users finding helpful clinics quicker, resulting in a 30% increase in booking rate.
Pivoting Appointment Booking Flow
Adapting quickly to new research data, bringing users to the clinic help-desk quickly and aligning the visual hierarchy of information based on user feedback resulted in 40% increase in booking rates from the 1st iteration.
Outcomes
Goals were met for MVP
The success indicator netted NPS 8 which exceeded our initial goal of NPS 7.
Our results depicted a 20% increased onboarding completion, reduced user’s time on clinic searching by 40% and increased engagement with filter criteria that addressed user needs.
Well-Received User Feedback
Ensuring that all copy was informative and instructive resulted in an increase in search conversion by 70%. Utilizing usability testing insights, we were able to iterate on an alternative search method that further improved search conversion rates and reduced time on task by 30%.
Goals were met for MVP
The success indicator netted NPS 8 which exceeded our initial goal of NPS 7.
Our results depicted a 20% increased onboarding completion, reduced user’s time on clinic searching by 40% and increased engagement with filter criteria that addressed user needs.
Well-Received User Feedback
Ensuring that all copy was informative and instructive resulted in an increase in search conversion by 70%. Utilizing usability testing insights, we were able to iterate on an alternative search method that further improved search conversion rates and reduced time on task by 30%.
Goals were met for MVP
The success indicator netted NPS 8 which exceeded our initial goal of NPS 7.
Our results depicted a 20% increased onboarding completion, reduced user’s time on clinic searching by 40% and increased engagement with filter criteria that addressed user needs.
Well-Received User Feedback
Ensuring that all copy was informative and instructive resulted in an increase in search conversion by 70%. Utilizing usability testing insights, we were able to iterate on an alternative search method that further improved search conversion rates and reduced time on task by 30%.