The automatic mileage tracker helps small business owners and sole-props maximize their tax deductions by leveraging smartphone sensors and machine learning to build accurate and tax compliant mileage logs.
Showing TLDR.
Outcomes
0.0 Billion
Business miles tracked
+$0M
Taxes saved
0
Patents granted
Research & Findings
For small businesses, tracking mileage for tax deductions is a high-friction, manual task with real financial consequences.
Tracking mileage is manual
Most used calendar apps, gas receipts, and pen & paper to maintain a mileage log. But these are often inaccurate due to the tedious nature of tracking every trip.
On the go & Mobile friendly
Users in this segment are often on the go, distractible, and expect to run their business from their phones.
Audit is an ever-present fear
Since these users often have to estimate their business mileage, they constantly worry about getting audited by the IRS.
Designing a digital mileage log
Swipe cards to left to review tracked business tripsSwipe cards to right to review tracked personal tripsGroups for similar tripsHandling no trip route informationHandling no trip route informationTrip route rendered on mapBulk review control for rideshare drivers
Phase 1 launch outcomes
0.0 M
Business trips tracked in 1 year
0%
Trips reviewed
Real world usage
Once the usage for mileage tracking reached a critical mass, to identify key opportunities to improve user retention, my PM lead and I decided to do an audit of the E2E product experience, both from a user perspective and an internal process perspective via usage metrics across onboarding, active usage and behavior pattern as well as, qualitative user feedback.
I then created a service blueprint with the key areas of opportunities highlighted across the online and offline experiences:
Move over the blueprint to magnify.
Grouping trips
I began looking at ways to group trips based on commonalities between them
With the grouping variables identified, I conducted a brainstorming session with the design, product and engg teams to explore grouping layout options.
Concept testing for groups
Concept 1
A familiar grouping pattern. Prominent section at the top of the page. Users felt it was easy to discover and understand. At a glance, they could see how large the group, and the pay off were.
Concept 2
Group is contextual to the trip in focus. Users felt this pattern was intuitive, and easy to understand. However, there was some confusion around multiple access points to review the same trip. There were also feasibility concerns from the engg team.
Concept 3
Group is exposed based on user action. Users mentioned that this felt like a pop-up, and overall this pattern made the groups hidden.
Testing the accuracy of the grouping algorithm
Metrics measured: Avg review rate, review rate in groups, and accuracy in prediction.
Test results
Avg trip review rate increased by 8%
Review rate for trips in groups was measured at 80%
Accuracy of predictions was ~87%
Trip review engagement increased by 15%
Smart groups concept was patented and the grouping pattern & interactions were added to the Intuit design system
