From In-House Efficiency to Enterprise Power: Scaling for the Future
Tekion is a cloud-based platform that helps automotive dealerships manage everything, from sales and service to operations, in one unified system. It replaces outdated, clunky dealership software with modern, fast, and intuitive tools built for today’s digital world.
Tekion powers 3,000+ dealerships and is trusted by multiple OEMs. Over 440,000 vehicles have been sold through the platform.
With a baseline understanding of the requirements, research surfaced two primary personas and their pain points.
- Had to undergo separate training to use third-party tools that aren't integrated with Tekion, leading to extra time and learning effort.
- In case of bugs or issues, has to manually switch between platforms, increasing the chance of errors and slowing down response times.
- Struggles with clunky, non-intuitive interfaces that aren't optimised for the dealership context.
- Moves between the showroom, service floor and delivery areas. Third-party tools that aren’t built for mobile or tablet disrupt this on-the-go workflow and delay real-time responses.
- Third-party tools may not show complete interaction history, previous service records, or deal context.
The second persona represents Tekion’s new target group.
- Often lack access to full customer history, past service interactions, or vehicle details, forcing them to piece information together manually.
- Frequently switch between the support tool, dealership systems (like DMS/CRM), and internal portals.
- Struggle with clunky, non-intuitive interfaces that aren't optimised for the dealership context.
- Support tools lack real-time collaboration like tagging technicians or looping in sales/service advisors, forcing agents onto email or Slack.
- Tickets get misrouted or poorly prioritised, leading to longer resolution times and frustrated dealer users.
Picking up the Pieces
In just four years since 2018, the internal tool grew from a minimal support portal into a slew of disparate features that made the experience slow and complex to use.
I realised it would struggle to scale alongside the company’s hyper-growth. Fundamental usability was challenged, features and experiments competed for focus, and reliability and performance issues were alarming.
- Fragmented communications
- No visual hierarchy
- No knowledge base or Jira integrations
- Lacks ticket context for the agent
- Separate module for chat, apart from tickets
- Has to redirect for every action
- Cluttered UI
Benchmarking our internal portal against market leaders
I broke ideation into focused modules. I’d sketch ideas, discuss them with the PM, then iterate and refine, from user flows to UI concepts.
I prototyped multiple concepts, tested usability with Maze, and ran usability sessions with users before converging on a solution. I documented every finding as pros and cons, which brought clarity to stakeholder meetings.
Ticket created
Our dealer John can’t turn off the brand filter. As we tackle this issue, let’s look at the revamped portal.
Meet your SLAs
SLAs help agents prioritise. Admins customise them by ticket type and priority. Here, we have 2 hours to get back to John.
Past interactions
John’s history sits beside the ticket, new and solved, so agents never open another tab to find context.
Connecting the dots
The bug already exists in Jira. Agents search and link the issue without leaving the ticket, and the status moves to Pending with Engineering.
Side conversations
Message engineering on Slack, Teams or mail from inside the ticket. Collaboration no longer means switching tools.
One hub for all configurations
A hub-and-spoke model: every setting branches from one central page, so admins always have a single place to come back to.
Discoverability
Every widget carries a plain description, so admins understand its purpose before they open it.
Personalised experience
Each brand switches features on or off, from thread comments and escalation to SLAs, Jira and the CRM plugin, to fit how that customer works.
Live and AI dashboards answer the finding that managers couldn’t see performance.
Since early 2024, we have been adding AI features that prioritise automation and reduce manual dependency.
Gather essential info to kickstart resolution
- Capture new ticket requests
- Prioritise and triage each request
- Less back-and-forth between requestor and agent
Auto-generated agent resolution
- Resolution captured from conversation history
- Replaces manual entry, saving time
- More accurate knowledge base articles
Smart ticket summary
- Summarise key actions from ticket logs
- Highlight key parameters
- Suggest next steps from previous actions
We helped them manage tickets well, but customers faced a new challenge: high ticket volume and over-stretched resources.
How did we solve that?
Read the Auto Resolution Bot case study →