- Background
- The Challenge
- UX Research & Insights
- Solution
Background
Hastings Deering is Australia’s largest Caterpillar dealership supplying Caterpillar equipment to the construction and mining industries throughout Queensland and the Northern Territory.
The major revenue sources comes from after market parts & services.
In 2022 we launched HD360, the Hastings Deering customer platform, with 3 core features.
- Assets Fleet: Allowed customers to manage their Caterpillar machine fleet
- Finance: gave customers access to the invoices and credit limit statuses
- Parts Tracker: Track the status of their parts orders
The Challenge
Hastings Deering customers had very little visibility on the status of their parts orders which lead to an overload of calls to the customer support phone line. In order to alleviate the pressure on the support lines a proof of concept tool called Parts Tracker was created to allow customer to look up the status of an order.
This was a simple search page however the issue was that many customers had multiple sales orders in progress at any one time which made this feature cumbersome to use.
Customer feedback via phone support and a in-app survey widget that the order statuses were too vague and not enough information was provided on backordered parts.
Original version
UX Research & Insights
Methodologies used
- 1 on 1 interviews
- In-app surveys
- Customer support phone data
- Service safaris
It was determined that a new version of Parts Tracker was needed, one that addressed the needs of the customer that would also cut down phones calls.
Research findings
Order statuses were too vague:
- Existing status, Pending, Completed or Invoiced gave the customer no visibility on whether a parts order was partial ready for pick up.
- Due to parts availability many parts orders were fulfilled incrementally which meant some customers would have to make multiple trips to the parts centre to pick up their parts
Customers need to plan:
- Many regional customers travelled multiple hours to pick up their parts and where frustrated that they had to do this 2 or 3 times in a week to get their whole order fulfilled.
- Large volume customers that ordered multiple times a week found it frustrating trying to get an overall view of what parts were ready and more importantly what was not ready.
- For many small customers, a part of backorder meant their machines was down and they were not making money, knowing when a backorder part would be ready was a crucial part of their day to day planning.
- Customers wanted to know where a part was coming from so they could better plan their time and expectations.
- Large fleet customers with a high volume of orders said the ability to export the parts order data to a CSV for analysis in their own fleet management tools was crucial.
Solution
Based on the research I focused my redesign on 3 key areas.
- Reviewing the order status labels to tell the customer more detailed about the fulfillment on an order
- Presenting the parts by ‘what is ready and not ready’ which would allow the customer to plan their time better
- Creating high level snapshots that gave large volume customers a quick view of where all their parts were.
Wireframes
Low fidelity wireframes were created to work through the flow and to test with customers and stakeholders via a series of workshops.
Improvements: Parts Order Statuses
A new set of order statuses were created to quickly tell if an order was partially or fully ready for pickup or delivery.
Customers with a large volume of orders could filter their orders by status and a color chip system was implemented to allow customers to quickly and easily identity which orders were fully ready or not.
Improvements: Orders details screen
The parts were grouped by their availability status, customers said “I just wanted to know what is ready and not ready”. Parts available now at the top with parts on back order at the bottom.
Improvements: Snapshots
The snapshots were designed to give the customers a quick high level view of where their parts orders are at.
The customer can click on them to give them a filter list of parts that match the category, then export to CSV for further analysis withing their own reporting systems.