SAM
MURPHY
DESIGN
SAM
MURPHY
DESIGN
THRIVEWORKS 2024-25
Demystifying insurance
ROLE
Design Lead responsible for discovery, stakeholder alignment, and end-to-end UX/UI design. Partnered with a PM and several engineers.
GOAL
To transform insurance verification from a confusing dead end into a guided experience that sets clear expectations for clients and reduces billing team workload.
OUTCOME
A redesigned booking experience focused on insurance, error prevention, and user guidance. We’re launching a 50/50 test next week!
Office lied that they took my insurance and didn't tell me they didn't until 3 appointments in when I got the bill. The people at the front are inconsistent on answers and overall a bad experience.
Client feedback
Lies about their billing and insurance and has so far taken $202 off my debit card WITHOUT PERMISSION
Client feedback
The burden falls on clients to navigate our complex systems. Clients need extra hand holding and help because they have mental health issues.
Billing team feedback
Intakes that get through without coverage lead to clients getting large, unexpected charges at weird intervals
Billing team feedback
Everything is so bulky and cumbersome and hard for clients to follow
Billing team feedback
Disconnected systems
Thriveworks, a 15-year-old mental health company with a 4-year-old product team, spent years building systems and processes in silos, overlooking the end-to-end user experience. Users who couldn’t verify their insurance were still allowed to book sessions, which resulted in a broken insurance process—one that overwhelmed our billing team and left clients facing either last-minute cancellations or unexpected charges.
To address these issues at the source, I looked at the existing insurance step in our booking flow to understand why verifications were failing, and how to help more users see success.
Swipe
70% of searches did not include insurance
Most users searched for providers without including insurance filters, leading them deep into the booking flow only to hit a dead end when they discovered their provider didn’t accept their plan.
33% of insurance errors resulted in endless loops
Users frequently encountered a vague “not found” error that provided no clarity about whether their carrier, date of birth, member ID, or name was wrong. Left to troubleshoot on their own, most users would try up to 3 times before dropping off.
Inconsistent and confusing language
Primary insured vs policyholder, gender vs sex, carrier vs payer, etc. While insurance is complex, the inconsistent (and often incorrect) language made it worse, both for users going through the flow and communication between teams.
While working through these problems, I realized insurance and our healthcare system is confusing by design—inconsistency across carriers, each company requires different information. Instead of pretending it was simple and hoping users would figure it out, we could acknowledge the complexity while actually helping guide them through it.
Solving for error loops
Working closely with the PM and lead engineer, I help working sessions with our billing and customer service teams to map the most common errors and their root causes, enabling me to design specific troubleshooting flows for each error type.
Through these sessions we discovered our most common error wasn’t always because of mistakes with someone’s name, DOB, or member ID—some users were actually selecting the wrong carrier. Their card showed one recognizable logo but they needed to look for a less prominent one. This was a prime example of the inconsistency across insurance companies.
Guiding through confusion
I realized that no matter how clear I made the flow, users would still hit errors. What mattered was how the UX supported them when errors occurred. I researched how other companies solved complex problems. From TurboTax, I studied how they explain a confusing topic like taxes with friendly, approachable language while using progressive disclosure to layer information gathering. From Airbnb, I looked at their troubleshooting approach—how they pull users out of the main flow to focus their attention and provide guided assistance when something goes wrong.
If I could guide users through inevitable complexity rather than leave them to struggle alone, could I improve error resolution rates and reduce unprocessed claims for our billing team, while improving conversion?
Where I landed
Moved insurance verification earlier in the flow so users could understand their insurance status sooner
Provided clear messaging about each insurance status and what to expect once someone booked
Split insurance and policyholder details into guided steps that reduced cognitive load
Offered guided troubleshooting for common errors within a focused experience to improve the chance of correcting an unverified status
Used plain language with helpful tips and created an insurance-specific FAQ section
Interactive desktop prototype showcasing insurance onboarding flow with built-in troubleshooting for common user errors.
What I learned
We recently completed a canary launch with 100 users to reveal any critical errors or sticking points before moving forward with a 50/50 launch.
In the 50/50 launch we plan to track error rates, conversions, and billing team handling time to quantify the impact of the project.
Drove a 35% lift in searches that included insurance
By testing a pre-search questionnaire that guided users through insurance selection, I made it more discoverable. It wasn’t that people didn’t want to select their insurance—it was that they didn’t see it.
Turned a major drop-off point into 54% conversion
By creating a redirect for users whose insurance wasn’t accepted by their chosen provider, I helped those that slipped through the cracks. Instead of leaving them to figure out what to do, we provided them clear options whether they wanted to find a new provider or continue with the one they chose.
No conversion blocking bugs were found
No users were blocked by bugs that appeared. Anyone who wanted to complete a booking was able to do so successfully!
Small technical issues need to be ironed out
Our insurance section wasn’t rendering the insurance list properly, causing occasional display errors. Loading delays in some sections created friction points throughout the flow.
SAM
MURPHY
DESIGN
SAM
MURPHY
DESIGN
THRIVEWORKS 2024-25
Demystifying insurance
ROLE
Design Lead responsible for discovery, stakeholder alignment, and end-to-end UX/UI design. Partnered with a PM and several engineers.
GOAL
To transform insurance verification from a confusing dead end into a guided experience that sets clear expectations for clients and reduces billing team workload.
OUTCOME
A redesigned booking experience focused on insurance, error prevention, and user guidance. We’re launching a 50/50 test next week!
Office lied that they took my insurance and didn't tell me they didn't until 3 appointments in when I got the bill. The people at the front are inconsistent on answers and overall a bad experience.
Client feedback
Lies about their billing and insurance and has so far taken $202 off my debit card WITHOUT PERMISSION
Client feedback
The burden falls on clients to navigate our complex systems. Clients need extra hand holding and help because they have mental health issues.
Billing team feedback
Intakes that get through without coverage lead to clients getting large, unexpected charges at weird intervals
Billing team feedback
Everything is so bulky and cumbersome and hard for clients to follow
Billing team feedback
Disconnected systems
Thriveworks, a 15-year-old mental health company with a 4-year-old product team, spent years building systems and processes in silos, overlooking the end-to-end user experience. Users who couldn’t verify their insurance were still allowed to book sessions, which resulted in a broken insurance process—one that overwhelmed our billing team and left clients facing either last-minute cancellations or unexpected charges.
To address these issues at the source, I looked at the existing insurance step in our booking flow to understand why verifications were failing, and how to help more users see success.
70% of searches did not include insurance
Most users searched for providers without including insurance filters, leading them deep into the booking flow only to hit a dead end when they discovered their provider didn’t accept their plan.
33% of insurance errors resulted in endless loops
Users frequently encountered a vague “not found” error that provided no clarity about whether their carrier, date of birth, member ID, or name was wrong. Left to troubleshoot on their own, most users would try up to 3 times before dropping off.
Inconsistent and confusing language
Primary insured vs policyholder, gender vs sex, carrier vs payer, etc. While insurance is complex, the inconsistent (and often incorrect) language made it worse, both for users going through the flow and communication between teams.
While working through these problems, I realized insurance and our healthcare system is confusing by design—inconsistency across carriers, each company requires different information. Instead of pretending it was simple and hoping users would figure it out, we could acknowledge the complexity while actually helping guide them through it.
Solving for error loops
Working closely with the PM and lead engineer, I help working sessions with our billing and customer service teams to map the most common errors and their root causes, enabling me to design specific troubleshooting flows for each error type.
Through these sessions we discovered our most common error wasn’t always because of mistakes with someone’s name, DOB, or member ID—some users were actually selecting the wrong carrier. Their card showed one recognizable logo but they needed to look for a less prominent one. This was a prime example of the inconsistency across insurance companies.
Guiding through confusion
I realized that no matter how clear I made the flow, users would still hit errors. What mattered was how the UX supported them when errors occurred. I researched how other companies solved complex problems. From TurboTax, I studied how they explain a confusing topic like taxes with friendly, approachable language while using progressive disclosure to layer information gathering. From Airbnb, I looked at their troubleshooting approach—how they pull users out of the main flow to focus their attention and provide guided assistance when something goes wrong.
If I could guide users through inevitable complexity rather than leave them to struggle alone, could I improve error resolution rates and reduce unprocessed claims for our billing team, while improving conversion?
Where I landed
Moved insurance verification earlier in the flow so users could understand their insurance status sooner
Provided clear messaging about each insurance status and what to expect once someone booked
Split insurance and policyholder details into guided steps that reduced cognitive load
Offered guided troubleshooting for common errors within a focused experience to improve the chance of correcting an unverified status
Used plain language with helpful tips and created an insurance-specific FAQ section
Interactive desktop prototype showcasing insurance onboarding flow with built-in troubleshooting for common user errors.
What I learned
We recently completed a canary launch with 100 users to reveal any critical errors or sticking points before moving forward with a 50/50 launch.
In the 50/50 launch we plan to track error rates, conversions, and billing team handling time to quantify the impact of the project.
Drove a 35% lift in searches that included insurance
By testing a pre-search questionnaire that guided users through insurance selection, I made it more discoverable. It wasn’t that people didn’t want to select their insurance—it was that they didn’t see it.
Turned a major drop-off point into 54% conversion
By creating a redirect for users whose insurance wasn’t accepted by their chosen provider, I helped those that slipped through the cracks. Instead of leaving them to figure out what to do, we provided them clear options whether they wanted to find a new provider or continue with the one they chose.
No conversion blocking bugs were found
No users were blocked by bugs that appeared. Anyone who wanted to complete a booking was able to do so successfully!
Small technical issues need to be ironed out
Our insurance section wasn’t rendering the insurance list properly, causing occasional display errors. Loading delays in some sections created friction points throughout the flow.
SAM
MURPHY
DESIGN
SAM
MURPHY
DESIGN
THRIVEWORKS 2024-25
Demystifying insurance
ROLE
Design Lead responsible for discovery, stakeholder alignment, and end-to-end UX/UI design. Partnered with a PM and several engineers.
GOAL
To transform insurance verification from a confusing dead end into a guided experience that sets clear expectations for clients and reduces billing team workload.
OUTCOME
A redesigned booking experience focused on insurance, error prevention, and user guidance. We’re launching a 50/50 test next week!
Office lied that they took my insurance and didn't tell me they didn't until 3 appointments in when I got the bill. The people at the front are inconsistent on answers and overall a bad experience.
Client feedback
Lies about their billing and insurance and has so far taken $202 off my debit card WITHOUT PERMISSION
Client feedback
The burden falls on clients to navigate our complex systems. Clients need extra hand holding and help because they have mental health issues.
Billing team feedback
Intakes that get through without coverage lead to clients getting large, unexpected charges at weird intervals
Billing team feedback
Everything is so bulky and cumbersome and hard for clients to follow
Billing team feedback
Disconnected systems
Thriveworks, a 15-year-old mental health company with a 4-year-old product team, spent years building systems and processes in silos, overlooking the end-to-end user experience. Users who couldn’t verify their insurance were still allowed to book sessions, which resulted in a broken insurance process—one that overwhelmed our billing team and left clients facing either last-minute cancellations or unexpected charges.
To address these issues at the source, I looked at the existing insurance step in our booking flow to understand why verifications were failing, and how to help more users see success.
70% of searches did not include insurance
Most users searched for providers without including insurance filters, leading them deep into the booking flow only to hit a dead end when they discovered their provider didn’t accept their plan.
33% of insurance errors resulted in endless loops
Users frequently encountered a vague “not found” error that provided no clarity about whether their carrier, date of birth, member ID, or name was wrong. Left to troubleshoot on their own, most users would try up to 3 times before dropping off.
Inconsistent and confusing language
Primary insured vs policyholder, gender vs sex, carrier vs payer, etc. While insurance is complex, the inconsistent (and often incorrect) language made it worse, both for users going through the flow and communication between teams.
While working through these problems, I realized insurance and our healthcare system is confusing by design—inconsistency across carriers, each company requires different information. Instead of pretending it was simple and hoping users would figure it out, we could acknowledge the complexity while actually helping guide them through it.
Solving for error loops
Working closely with the PM and lead engineer, I help working sessions with our billing and customer service teams to map the most common errors and their root causes, enabling me to design specific troubleshooting flows for each error type.
Through these sessions we discovered our most common error wasn’t always because of mistakes with someone’s name, DOB, or member ID—some users were actually selecting the wrong carrier. Their card showed one recognizable logo but they needed to look for a less prominent one. This was a prime example of the inconsistency across insurance companies.
Guiding through confusion
I realized that no matter how clear I made the flow, users would still hit errors. What mattered was how the UX supported them when errors occurred. I researched how other companies solved complex problems. From TurboTax, I studied how they explain a confusing topic like taxes with friendly, approachable language while using progressive disclosure to layer information gathering. From Airbnb, I looked at their troubleshooting approach—how they pull users out of the main flow to focus their attention and provide guided assistance when something goes wrong.
If I could guide users through inevitable complexity rather than leave them to struggle alone, could I improve error resolution rates and reduce unprocessed claims for our billing team, while improving conversion?
Where I landed
Moved insurance verification earlier in the flow so users could understand their insurance status sooner
Provided clear messaging about each insurance status and what to expect once someone booked
Split insurance and policyholder details into guided steps that reduced cognitive load
Offered guided troubleshooting for common errors within a focused experience to improve the chance of correcting an unverified status
Used plain language with helpful tips and created an insurance-specific FAQ section
Interactive desktop prototype showcasing insurance onboarding flow with built-in troubleshooting for common user errors.
What I learned
We recently completed a canary launch with 100 users to reveal any critical errors or sticking points before moving forward with a 50/50 launch.
In the 50/50 launch we plan to track error rates, conversions, and billing team handling time to quantify the impact of the project.
Drove a 35% lift in searches that included insurance
By testing a pre-search questionnaire that guided users through insurance selection, I made it more discoverable. It wasn’t that people didn’t want to select their insurance—it was that they didn’t see it.
Turned a major drop-off point into 54% conversion
By creating a redirect for users whose insurance wasn’t accepted by their chosen provider, I helped those that slipped through the cracks. Instead of leaving them to figure out what to do, we provided them clear options whether they wanted to find a new provider or continue with the one they chose.
No conversion blocking bugs were found
No users were blocked by bugs that appeared. Anyone who wanted to complete a booking was able to do so successfully!
Small technical issues need to be ironed out
Our insurance section wasn’t rendering the insurance list properly, causing occasional display errors. Loading delays in some sections created friction points throughout the flow.