Implementing analytics for a driver app.
At Verizon Connect, our team added analytics to the Logbook app, boosting engagement by 74% and NPS by 4 points.
01/ Summary
The Product
ELD (Electric logging device) Logbook
ELD Logbook is an app that helps drivers track and manage their driving hours. It records their driving, breaks, and off-duty periods to ensure compliance with national driving regulations for both long and short-haul drivers. Currently, the ELD Logbook is used by 40,000 drivers each month.
The Problem
We frequently introduce new features and bug fixes, but we lack accurate data on how often these features are used or how users are impacted by the bug fixes.
What we want to achieve
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Make Logbook a data driven product
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Have accurate, clean, and actionable data
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Understand customer/user behavior
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Understand the experience of the users/drivers
My Role
As the lead UX designer for this project, I worked alongside two engineers and one product owner to implement analytics for the ELD Logbook. Our goal was to create a data-driven product and regularly measure the outcomes of the features and implementations we introduced.
02/ Process
Auditing the product
To understand the depth of the problem, I conducted a thorough audit of the logbook, examining each page and all interactions. This allowed me to assess the level of effort required to implement the analytics.
02 / 01
Page & button interaction audit of Logbook app
Summary of workshop outcome to display in analytics dashboard
Workshop with cross functional teams
Using Google’s HEART framework, which includes:
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Goals: What are the analytical goals that we want to ensure we are achieving with Logbook?
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Signal: What ensures that we are moving closer or further from our goals?
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Metrics: These should be measurable, trackable over time, and actionable as a result.
I gathered insights and ideas from engineers and the product team, invited contributions from the design team, and summarized the outcomes of our workshop.
02 / 02
Action steps
After clarifying goals with cross-functional teams and using the product audit, I wanted to tag the pages and buttons. To better understand its features, I decided to learn Pendo analytics and got certified. Our team chose Pendo to easily track and measure Logbook users. Here are my steps:
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Tagging Pages:
Mark pages and buttons to track clicks and usage. -
Refine Data:
Convert data into measurable metrics to evaluate performance. -
Actionable Insights:
Use data insights to create dashboards and identify user behavior.
02 / 03
Tagging process in Pendo analytics tool
After tagging all the pages, I separated the sections into Android and iOS. Most users are on Android, so we need to understand their behavior and apply the insights to iOS. To ensure testing accounts don't mix with actual user data, I created “Logbook Android Production” and “Logbook iOS Production” sections.
iOS tagged page
Android tagged page
02 / 04
03/ Outcome
ELD Logbook iOS Dashboard (same as the Android dashboard) with all the metrics mentioned in the workshop.
With all tagging and get accurate data, I put together dashboard for Android & iOS. Tracking key metrics such as Account overview, visitor overview, device usage, number of users login and logout per day Version updated by the users.
Everyone in the business started using Pendo to access accurate, actionable data when problems arise. Instead of relying on gut feelings, we now have data to support our decisions.
What we achieved
Make Logbook a data driven product ✅
Have accurate, clean, and actionable data ✅
Understand customer/user behavior ✅
Understand the experience of the users/drivers ✅
Impact
74%
business in NZ use analytics for data
There has been a significant shift towards data-driven product development.
The team can track and analyze user behavior, feature adoption, and overall engagement patterns more effectively. This approach allows the team to identify pain points, understand user preferences, and make informed decisions to enhance the product’s usability and functionality.