HELPING SMALL SHOPS STAY
How can we reimagine the onboarding and our first impressions to cut churn and make Fullbay feel like home for every repair shop.
THE PROBLEM
There are high churn rates among small to medium-sized shops during their first year. Defined as users leaving between 30 days and 12 months, this churn threatened the company's growth goals, with leadership setting a north star objective to cut churn in half by the end of 2025.
My role was clear: investigate why these users were leaving and propose actionable solutions to create a stickier, more supportive onboarding experience.
THE PROBLEM
There are high churn rates among small to medium-sized shops during their first year. Defined as users leaving between 30 days and 12 months, this churn threatened the company's growth goals, with leadership setting a north star objective to cut churn in half by the end of 2025.
My role was clear: investigate why these users were leaving and propose actionable solutions to create a stickier, more supportive onboarding experience.
THE PROBLEM
There are high churn rates among small to medium-sized shops during their first year. Defined as users leaving between 30 days and 12 months, this churn threatened the company's growth goals, with leadership setting a north star objective to cut churn in half by the end of 2025.
My role was clear: investigate why these users were leaving and propose actionable solutions to create a stickier, more supportive onboarding experience.
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THE RESEARCH
We initially aimed to conduct live onsites with users in the target segments. However, finding qualified participants proved difficult . Many of our candidates operated informally out of their homes, limiting our ability to generalize findings.
Adapting quickly, I shifted to mining Salesforce data collected over the past three years, which included a mixture of exit interviews, sales notes, and customer support records.
We initially aimed to conduct live onsites with users in the target segments. However, finding qualified participants proved difficult . Many of our candidates operated informally out of their homes, limiting our ability to generalize findings.
Adapting quickly, I shifted to mining Salesforce data collected over the past three years, which included a mixture of exit interviews, sales notes, and customer support records.
We initially aimed to conduct live onsites with users in the target segments. However, finding qualified participants proved difficult . Many of our candidates operated informally out of their homes, limiting our ability to generalize findings.
Adapting quickly, I shifted to mining Salesforce data collected over the past three years, which included a mixture of exit interviews, sales notes, and customer support records.
Using affinity mapping, I categorized qualitative feedback into themes and leading causes of churn. In parallel, I initiated a System Usability Scale (SUS) survey to establish a product usability baseline, ensuring future product changes could be measured for impact.
This methodical blend of historical and proactive research allowed us to piece together a clear picture despite the recruitment challenges.
Using affinity mapping, I categorized qualitative feedback into themes and leading causes of churn. In parallel, I initiated a System Usability Scale (SUS) survey to establish a product usability baseline, ensuring future product changes could be measured for impact.
This methodical blend of historical and proactive research allowed us to piece together a clear picture despite the recruitment challenges.
Using affinity mapping, I categorized qualitative feedback into themes and leading causes of churn. In parallel, I initiated a System Usability Scale (SUS) survey to establish a product usability baseline, ensuring future product changes could be measured for impact.
This methodical blend of historical and proactive research allowed us to piece together a clear picture despite the recruitment challenges.
Our synthesis revealed six leading causes of churn, ranging from overwhelming product complexity to poor fit with specific shop types. One powerful realization emerged: many users didn't necessarily churn because Fullbay lacked features.
Fullbay didn't "feel like theirs" immediately after signup. This sparked a major strategic insight: instead of forcing users to mold themselves to Fullbay, how could we mold Fullbay to fit users?
Our synthesis revealed six leading causes of churn, ranging from overwhelming product complexity to poor fit with specific shop types. One powerful realization emerged: many users didn't necessarily churn because Fullbay lacked features.
Fullbay didn't "feel like theirs" immediately after signup. This sparked a major strategic insight: instead of forcing users to mold themselves to Fullbay, how could we mold Fullbay to fit users?
Our synthesis revealed six leading causes of churn, ranging from overwhelming product complexity to poor fit with specific shop types. One powerful realization emerged: many users didn't necessarily churn because Fullbay lacked features.
Fullbay didn't "feel like theirs" immediately after signup. This sparked a major strategic insight: instead of forcing users to mold themselves to Fullbay, how could we mold Fullbay to fit users?
HOW MIGHT WE MAKE FULLBAY FEEL FAMILIAR AND VALUABLE TO ALL NEW USERS?
THE GOAL
Transform Fullbay’s onboarding experience to feel simple, personalized, and instantly valuable for small and medium-sized repair shops, reducing early churn.
THE GOAL
Transform Fullbay’s onboarding experience to feel simple, personalized, and instantly valuable for small and medium-sized repair shops, reducing early churn.
THE GOAL
Transform Fullbay’s onboarding experience to feel simple, personalized, and instantly valuable for small and medium-sized repair shops, reducing early churn.
CONFUSING
>
CLEAR
Help users confidently start by surfacing only the most critical, relevant features at signup.
CONFUSING
>
CLEAR
Help users confidently start by surfacing only the most critical, relevant features at signup.
CONFUSING
>
CLEAR
Help users confidently start by surfacing only the most critical, relevant features at signup.
OVERWHELMING
>
STEPS
Lead users through an adaptive, bite-sized onboarding flow that matches their shop type and goals.
OVERWHELMING
>
STEPS
Lead users through an adaptive, bite-sized onboarding flow that matches their shop type and goals.
OVERWHELMING
>
STEPS
Lead users through an adaptive, bite-sized onboarding flow that matches their shop type and goals.
RIGIDITY
>
FLEXIBLE
Empower shops to customize core workflows early, making Fullbay feel tailor-made from day one.
RIGIDITY
>
FLEXIBLE
Empower shops to customize core workflows early, making Fullbay feel tailor-made from day one.
RIGIDITY
>
FLEXIBLE
Empower shops to customize core workflows early, making Fullbay feel tailor-made from day one.
PHASE 1 SOLUTION
Before proposing structural changes, I needed to establish a clear foundation. I defined the critical difference between "preferences" (individual user tweaks) and "settings" (business-wide system rules). Understanding this distinction helped clarify where flexibility was possible without risking operational integrity.
I audited Fullbay’s complex settings infrastructure, sorting it into key operational areas: user permissions, customer management, parts inventory, and system hierarchies.
Before proposing structural changes, I needed to establish a clear foundation. I defined the critical difference between "preferences" (individual user tweaks) and "settings" (business-wide system rules). Understanding this distinction helped clarify where flexibility was possible without risking operational integrity.
I audited Fullbay’s complex settings infrastructure, sorting it into key operational areas: user permissions, customer management, parts inventory, and system hierarchies.
Before proposing structural changes, I needed to establish a clear foundation. I defined the critical difference between "preferences" (individual user tweaks) and "settings" (business-wide system rules). Understanding this distinction helped clarify where flexibility was possible without risking operational integrity.
I audited Fullbay’s complex settings infrastructure, sorting it into key operational areas: user permissions, customer management, parts inventory, and system hierarchies.
Then, I mapped these configurations to different shop personas — internal fleets, independent repair shops, dealerships, and others — highlighting which settings mattered most to each.
This work uncovered the path forward. The Phase 1 solution was to personalize the onboarding experience through targeted questions at signup. Based on their answers, new users would be routed into a curated configuration that felt intuitive, fast, and relevant to their needs.
Then, I mapped these configurations to different shop personas — internal fleets, independent repair shops, dealerships, and others — highlighting which settings mattered most to each.
This work uncovered the path forward. The Phase 1 solution was to personalize the onboarding experience through targeted questions at signup. Based on their answers, new users would be routed into a curated configuration that felt intuitive, fast, and relevant to their needs.
Then, I mapped these configurations to different shop personas — internal fleets, independent repair shops, dealerships, and others — highlighting which settings mattered most to each.
This work uncovered the path forward. The Phase 1 solution was to personalize the onboarding experience through targeted questions at signup. Based on their answers, new users would be routed into a curated configuration that felt intuitive, fast, and relevant to their needs.
It was also extremely important to me to make sure our delivables actually moved the needle. So creating a baseline data around our SUS surveys helped makes sure any iterations we made in Phase 1 had a measurabel impact.
I even made a web tool to handle the resuts of our SUS survey in the future as we continue to get data in during these iterations.
Everything was in place for Phase 1.
It was also extremely important to me to make sure our delivables actually moved the needle. So creating a baseline data around our SUS surveys helped makes sure any iterations we made in Phase 1 had a measurabel impact.
I even made a web tool to handle the resuts of our SUS survey in the future as we continue to get data in during these iterations.
Everything was in place for Phase 1.
It was also extremely important to me to make sure our delivables actually moved the needle. So creating a baseline data around our SUS surveys helped makes sure any iterations we made in Phase 1 had a measurabel impact.
I even made a web tool to handle the resuts of our SUS survey in the future as we continue to get data in during these iterations.
Everything was in place for Phase 1.
UNTIL…
THE PIVOT
Midway through the project, strategic priorities shifted. Leadership decided that the onboarding and customer engagement teams would own churn reduction efforts moving forward. I transitioned my research, frameworks, and recommendations to the newly formed Customer Engagement team, supporting them with knowledge-sharing sessions and documentation.
Although it was tough to step away, it was clear that embedding our findings within the teams closest to users would have the biggest long-term impact.
Midway through the project, strategic priorities shifted. Leadership decided that the onboarding and customer engagement teams would own churn reduction efforts moving forward. I transitioned my research, frameworks, and recommendations to the newly formed Customer Engagement team, supporting them with knowledge-sharing sessions and documentation.
Although it was tough to step away, it was clear that embedding our findings within the teams closest to users would have the biggest long-term impact.
Midway through the project, strategic priorities shifted. Leadership decided that the onboarding and customer engagement teams would own churn reduction efforts moving forward. I transitioned my research, frameworks, and recommendations to the newly formed Customer Engagement team, supporting them with knowledge-sharing sessions and documentation.
Although it was tough to step away, it was clear that embedding our findings within the teams closest to users would have the biggest long-term impact.
Not every project wraps up with a bow. Sometimes success means laying strong foundations for others to build upon. This project reinforced a key lesson: adaptability is critical, especially when timelines, ownership, and business goals pivot.
Above all, I'm proud that the work done here positioned Fullbay to rethink how they scale their experience for all users, not just their largest accounts.
Not every project wraps up with a bow. Sometimes success means laying strong foundations for others to build upon. This project reinforced a key lesson: adaptability is critical, especially when timelines, ownership, and business goals pivot.
Above all, I'm proud that the work done here positioned Fullbay to rethink how they scale their experience for all users, not just their largest accounts.
Not every project wraps up with a bow. Sometimes success means laying strong foundations for others to build upon. This project reinforced a key lesson: adaptability is critical, especially when timelines, ownership, and business goals pivot.
Above all, I'm proud that the work done here positioned Fullbay to rethink how they scale their experience for all users, not just their largest accounts.