Reveal Video Coaching

UX Research

This piece documents my contributions to developing user-centric driver coaching functionality for Verizon Connect’s product Reveal. This was a high priority roadmap initiative from 2023-2024, and my research initiatives spanned the end-to-end product lifecycle—ideation to post-launch. Beyond the scope of this project, this high impact research continues to support the wider UX, Product, and Engineering teams at Verizon Connect as a foundation of the company’s understanding of fleet/safety manager coaching needs.

Overview

Problem

Verizon Connect Reveal customers receive hundreds of dashcam videos a day documenting potentially hazardous driving events. Sorting through such a large dataset quickly becomes a time consuming and costly part of fleet managers’ day-to-day work. Our team knew from customer feedback that users wanted to efficiently comb through their data, identify improvement areas, and coach their drivers all in the Reveal platform. Such a project required a deep understanding of customer wants, needs, and existing behaviors in order to steer production goals and maximize impact.

Project Goal

  • Explore and validate customer coaching needs to ensure our coaching solution had maximum impact

  • Act as the ‘voice of the customer’ using research in roadmap prioritization

  • Steer the Product and Engineering team’s production priorities

My Contribution & Impact

This was my contribution. It had this impact.

Team

Stephanie Baione, Colin Smith, Mimi Lu

Timeline

2023 - 2024

Tools

Miro, Figjam, usertesting.com, userinterviews.com, Dovetail

 Background

 

Fleet management technology like Verizon Connect’s Reveal tracks expansive amounts of information about company vehicles, doubly so if dashcams are in the picture. Reveal Video aggregates dashcam data as a list of ‘harsh driving events’, rated from minor to critical by an AI engine, and stores the videos for user review. For small fleets with well-behaved drivers, this is a handy tool for reviewing the occasional minor hazard. For medium to large to enterprise fleets, it quickly becomes an unwieldy and exponentially growing repository of videos you don’t have time to watch. We learned from user feedback that this was a common source of lost value among customers, who were too busy with other tasks to devote the necessary time to coaching.

It’s these challenges that led Verizon Connect to seek to do more with Reveal Video’s vast data repository. The team wanted to empower fleet/safety managers to more efficiently comb through their data, identify improvement areas, and coach their drivers all in the Reveal platform. It was a large, multi-year initiative, one that demanded a deep understanding of customer wants, needs, and existing behaviors in order to steer production goals and maximize impact.

This Video Coaching video shows the output of this project. This portfolio piece will tell you how we got there.

Project Goal

  • Explore and validate customer coaching needs to ensure our coaching solution had maximum impact

  • Act as the ‘voice of the customer’ using research in roadmap prioritization

  • Steer the Product and Engineering team’s production priorities

 

Project Timeline

This project spanned two years and over 20 research initiatives split across the team. Post launch work also continued past 2024.

White projects were discovery-focused research roadmap projects. Purple projects were designer-led, centering on design validation.

 
 
 

1. Defining Customer Needs

Research Goals & My Contribution

For the first half of 2023, our research team sought to elevate and validate our understanding of coaching through a combination of safety manager interviews, driver interviews, and quantitative surveys. My contributions to this phase of work focused on semi-structured safety manager interviews covering a broad range of topics to help us assess customer needs. I also provided research support for the designers seeking to validate and iterate on their work through user testing. The following projects from the timeline above were my primary focus at this stage:

Coaching Phase 1 Planning & Discovery

Coaching Phase 1 Concept User Test

Coaching: Driver List & Profile Data

Coaching Phase 2 Planning

Major Research Examples

This is an example of some of the research I did at this stage that is unique or interesting or showcased me utilizing my skillset. One big research piece and one design mentorship piece.

 
 
Findings: In addition to gaining a broad understanding of our problem space, we also identified a number of pain points within the application that reviewers online repeatedly mentioned.

2. Explorative Research to Steer Roadmap Priorities

Research Goals & My Contribution

From Q3 2023 to Q3 2024, our team’s research focus narrowed from foundational to explorative work, as the product and design teams needed help prioritizing the many potential coaching features that the team had slated for the roadmap. This meant our research was focused on a narrower scope and had direct roadmap impact. This phase of research consisted of interviews, surveys, and user tests on subjects like: mobile apps as coaching tools, enterprise customer API needs, safety score customization, and coaching session features. My contributions to this phase of work focused on mobile app coaching and safety score customization needs, the latter also doubling as support for designer-led research. The following projects from the timeline above were my primary focus at this stage:

Mobile Coaching & Driver Experience Interviews

Safety Score - Behavior & Customization Part 1

Safety Score - Behavior & Customization Part 2

Safety Score - Customization - Internal ‘Discovery’

Major Research Examples

This is an example of some of the research I did at this stage that is unique or interesting or showcased me utilizing my skillset. One big research piece and one design mentorship piece.

 
 
Findings: In addition to gaining a broad understanding of our problem space, we also identified a number of pain points within the application that reviewers online repeatedly mentioned.

3. Post-Launch Validation and Future Thinking

Research Goals & My Contribution

Reveal’s coaching features had a rolling release, meaning that there was overlap between the previously mentioned explorative phase and the post-launch validation stage, which began in Q4 of 2023 and continued into 2025. Our team’s focus was now to evaluate the usefulness, effectiveness, and longevity of the new coaching platform through a customer beta, post launch interviews, and a recurring post launch survey. My contributions to this phase of work focused on post-launch interviews for desktop and mobile experience. The following projects from the timeline above were my primary focus at this stage:

 

Coaching ‘Post Launch’ Feedback

Mobile Coaching Post Launch & Mobile Experience

 

Major Research Examples

This is an example of some of the research I did at this stage that is unique or interesting or showcased me utilizing my skillset. One big research piece and one design mentorship piece.

 
 
Findings: In addition to gaining a broad understanding of our problem space, we also identified a number of pain points within the application that reviewers online repeatedly mentioned.

4. Impact

  1. Prioritized the product roadmap.

    Helped w roadmap prioritization throughout the project.

  2. Impact 2

    Impact 2

  3. Supported the coaching product’s release.

    This project made a new feature a reality while minimizing risk via research.

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Designing a Mentorship Program