Zero Motorcycles Ride Dashboard App

Zero Motorcycles manufactures all-electric motorcycles known for silent power and immediate torque. The bikes were extraordinary, but they offered minimal data feedback to riders — a critical gap for customers trying to manage battery range, track performance, and understand their electric riding experience.

I designed a mobile dashboard app that connected to the motorcycle via Bluetooth. The moment the kickstand goes up, the app locks into a live ride. It tracks speed, battery state-of-charge, torque, motor temperature, and rider-defined stats in real time. Off the bike, it becomes a trip planner and historical data log. The app shipped for both iOS and Android, and was received with enthusiasm by Zero’s rider community.

Riding blind on an electric machine

Zero Motorcycles make extraordinary bikes. Silent, fast, and exhilarating — the electric powertrain delivers instant torque with zero mechanical noise. But that silence came with a cost: riders had almost no visibility into what was happening beneath the bodywork.

The physical dashboard showed only basic data. Battery range anxiety was real and common. Riders couldn’t track their performance stats, configure what they saw, or review their trips after the fact. For customers who were paying a premium for a technology-forward motorcycle, the data gap felt like a broken promise.

The app needed to solve this by becoming the rider’s digital cockpit — an intelligent, Bluetooth-connected extension of the bike that worked both on the road and off it.

Understanding the electric rider

Research began with direct access to Zero Motorcycles riders — early adopters who were deeply invested in the technology and vocal about what they needed. We conducted interviews, rode alongside participants, and studied how they currently compensated for the dashboard’s limitations.

Key findings: riders wanted control over what they saw during a live ride. They wanted to set up their dashboard before departure, not while moving. They tracked their stats obsessively and wanted historical data to compare trips. Battery state-of-charge was the single most important data point — range anxiety was the defining pain of the electric experience.

We also studied how riders interacted with other performance tools — GPS devices, cycling computers, sports watches — to understand what conventions translated and what needed to be rethought for a motorcycle context.

A significant part of this research phase was spent understanding the technology itself — how electric motorcycles operate, how their powertrains differ from combustion engines, what the onboard sensors expose, and how existing dashboard instruments communicated data to riders. Understanding the machine was inseparable from understanding the rider’s experience of it.

From objects and actions to a structured app

Research outputs fed directly into the information architecture work. The first step was building an Object-Action Model — a rough framework mapping what riders cared about (battery, speed, trip, performance) against the actions they needed to take (configure, monitor, review, compare). This anchored every structural decision in actual rider intent rather than assumed feature lists.

The final IA organized the app around two primary contexts: the off-ride state (planning, setup, review) and the live-ride state (active monitoring, glanceable data). Every screen lived in one of these two modes. The live-ride dashboard was intentionally top-level and full-screen — once the kickstand was up, everything else stepped aside.

Major sections: Dashboard (live ride), Trip Setup & Planning, Performance Stats, Battery & Range, Settings & Personalization, and Support.

Charting the rider’s end-to-end journey

Before committing to any structural decisions, the full user workflow was mapped out — every touchpoint from the moment a rider approaches their bike to the moment they review their stats after the ride. This gave the team a shared, concrete picture of where the app lived in the rider’s life and what it needed to do at each step.

The workflow surfaced a critical split: the rider’s needs before a ride (setup, configuration, planning) are fundamentally different from their needs during one (glanceable data, zero cognitive load). Designing for both required a clear mode separation baked into the core architecture.

Mapping the workflow also revealed the natural triggers in the experience. The kickstand-up moment was identified here as the automatic transition point into live-ride mode — riders should never need to tap a “Start Ride” button. The bike signals the app. This principle, surfaced in the workflow phase, shaped every interaction decision that followed.

Getting ideas onto paper

With the workflow and architecture defined, early sketching brought the interface to life for the first time. These hand-drawn explorations focused on the two most critical surfaces in the app: the gauge dashboard and the splash screen. Sketching at this stage was fast and deliberate — the goal was to explore layout, hierarchy, and the relationship between data elements before committing to pixels.

The gauge screens explored how to tile multiple stats in a single glanceable view — a grid of configurable data tiles that the rider could set up before departure. The splash screen sketch focused on the first impression: a strong brand moment that felt appropriate for a performance motorcycle app without adding friction to the time-sensitive act of starting a ride.

Six frames that tell the whole story

Before a single wireframe was drawn, the experience needed to be felt as a narrative. The storyboard walked through the complete rider journey — from the moment they stand in the garage, helmet in hand, to the live dashboard displaying real-time power and temperature data mid-ride.

This storyboard became the shared language for the entire team. It grounded every subsequent design decision in a concrete human scenario, making it clear what the app needed to do and — equally important — when and how.

Six scenes. One continuous arc: get ready, set up the app, launch it, mount it, ride, and see your machine’s data come alive in real time. The storyboard confirmed the two-mode design split — setup before the kickstand goes up, live dashboard the moment it does.

Hand-illustrated for immediacy and approachability, the frames were used in stakeholder presentations to communicate the vision before any high-fidelity work began.

Iterating on structure before investing in visual design

Wireframes explored the core interaction flows in detail: how a rider sets up their dashboard before departure, how the live ride mode activates and what it shows, how settings are surfaced and organized, and how post-ride data is presented for review.

The ride setup flow was particularly complex — riders needed to select which stats to show, in what arrangement, at what threshold. The wireframes tested multiple approaches to this configuration experience before landing on a drag-and-configurable gauge system.

We ran multiple rounds of wireframe review with the team and Zero’s Head of Design, iterating on the live-ride screen layout most intensively. The challenge: during a ride, the rider’s eyes are mostly on the road. Every piece of information on screen had to justify its presence with immediate, legible value.

The wireframe below specifically documents the live riding settings areas — which stats the rider can configure for their personal live-ride experience.

Staying in dialogue with the rider community

Shipping the app wasn’t the end of the design process — it was the beginning of a more direct and data-rich feedback loop. Post-launch, I continued to work closely with Zero’s team and their customer community to identify friction, surface unmet needs, and prioritize future development.

Riders brought nuanced requests: different gauge configurations for city versus highway riding, the ability to set personal thresholds and alerts for battery percentage, and more detailed trip history with exportable data. These weren’t edge-case requests — they reflected how seriously Zero’s customers engaged with performance data.

The most meaningful insight from post-launch research was about the emotional dimension of the data. Riders didn’t just want information — they wanted to feel connected to their machine. Understanding torque output, seeing energy regeneration in real time, watching the battery recover on a downhill run: these were not merely utility features. They were part of what made riding a Zero different from riding anything else.

This shaped how we thought about future iterations: not just more data, but more meaningful data, presented at the right moment, in a way that deepened the rider’s relationship with the experience.