Ticket reduction through self-serve support

Six systems, one problem, one designer

Geotab's support ecosystem was — and still is, mid-migration — six independent systems: the Support site, Community, Academy, Dozuki, RightAnswers, and Geotab.com. Users had to guess which one to visit. Support agents had no unified workspace. There was no shared metric, no shared roadmap, and no shared ownership of the problem.

The company launched the Digital Self-Service Support (DSSS) initiative in 2024: a multi-year, COO-sponsored programme to consolidate everything into a single, AI-powered Central Support Hub. I was the sole UX resource across the full initiative — responsible for research, strategy, design, and delivery from Phase 1 through the current Phase 4.

The product UX layer is manufacturing support tickets

The conventional narrative blamed hardware and external complexity. The data said otherwise. I pulled ticket volumes from Superset (dashboards 3141 / 4205 / 11412) and the pattern was unambiguous: the MyGeotab UX layer generates nearly as many tickets as all hardware categories combined.

Source: Superset "Top 10 Ticket Trends - MoM" (chart 25825), May 2026. Blue = hardware categories.

On top of the ticket data: a 2023 support survey (544 responses) showed 50% of users unable to find what they were looking for — and 52% of those then contacted human support, cascading a self-service failure directly into operational cost. The same pattern appeared in 2,197 more recent survey responses (Superset chart 64417), including verbatims like: "I have even used outside AI to help with Geotab questions." Users were leaving the product to solve product problems.

Building the evidence base before touching a frame

The first deliverable wasn't a design — it was a Support UX Insights report: a prioritized, costed breakdown of the support problem that made the revenue-at-risk visible and gave product and operations a shared, fact-based roadmap instead of a wishlist. This became the P0/P1 alignment tool for the entire initiative.

Alongside the data work, I ran a structured research phase covering the user journey, the competitive landscape, and the platform's baseline UX quality.

1. UX Scorecard. Evaluated the Central Support Hub against defined criteria across the full user journey. The verdict: Grade D — a baseline score that gave stakeholders a common reference for "how bad is it?" before anyone could say "it's fine."
2. Competitive analysis. Built a full feature matrix comparing Geotab's support stack against Figma, Semrush, Salesforce, and Atlassian — across self-service, technical support, account management, proactive support, and advanced UX. Mapped gaps across 18 feature categories. Followed up with an effort/impact prioritization matrix to sequence the work.
3. Service blueprint. Mapped the full 7-stage support journey: Problem Encounter → Accessing CSH → Search Level 1 → Search Level 2 → Search Level 3 → Resource Review → Outcome. Across Goals, Actions, Touchpoints, and Experience for each stage, plus Frontstage / Backstage / Support Process layers. Exposed the drop-off points and backstage dependencies that the ticket data couldn't show.

Three surfaces, all shipped

1. Central Support Hub — launched January 2026

The support site homepage was redesigned from the ground up into a single, AI-powered entry point. Natural language search ("Describe your issue or ask a question…") replaces the old fragmented navigation. Popular topics surface the top ticket categories (Getting Started, Device Setup, Password Reset) — chosen from the ticket data, not guessed. Resource cards consolidate all six systems (Help Articles, Academy, Community, Known Issues, Development, Installer Finder) into one screen.

2. In-app Help panel — contextual support inside MyGeotab

The Help panel slides out from within MyGeotab — no tab-switching, no leaving the workflow. It has two modes: Ask AI (natural language query with suggested prompts contextual to the current page) and Help (curated articles). It surfaces recent conversations, open support tickets, and a direct path to submit a new ticket — all without leaving the application. The contextual prompt suggestions ("How do I create a rule?", "Explain exception rules", "Export data") are generated from the page the user is currently on.

3. GIA for Support agent console — shipped to all regions

The agent-side of the loop. Before GIA for Support, agents juggled three separate windows (Salesforce, MyGeotab, and the knowledge base) while on a call — copying case details by hand, searching KB manually, and relying on memory for resolution steps. The GIA for Support console replaced that with a single panel: AI-drafted case notes, session-based handle-time tracking, AI-detected safety and priority signals, and the KB surfaced inline. From v1 to v17 across multiple months of iteration with the Support Operations team. Mandatory rollout to all regions.

The work continues

The initiative moved into Phase 4 execution in July 2026. The Community migration to the Central Support Hub went live on July 15, 2026, with 15,000+ URLs redirected across 10 languages. Vertex AI Search is being rebuilt across Heretto, Strapi, and Dozuki content pipelines. And I'm running two new research tracks:

• Comparative research: AI-driven vs self-serve support. 5-participant study comparing user outcomes across the two modalities — feeding the next generation of Help panel design.
• Live chat UX audit. Partnered with Alastair McGregor's team (AVP, Support Ops Business Transformation) to audit the current live chat interaction model ahead of the contact center migration (target: EOM June / early July). Scope includes interaction model review, automated-to-human handoff design, and GIA integration into the agent workflow. Authentication from MyGeotab (80% of support volume) is the first use case.

A shipped platform, a shared metric, and a live migration

Central Support Hub launched January 2026 — live at support.geotab.com, serving all regions. GIA for Support shipped with a mandatory rollout — all agents, all regions. The Support UX Insights report became the shared, costed P0/P1 roadmap with Support Operations, establishing CES + revenue-at-risk as the joint success metric for support UX — not just a design metric, but an ops metric.