The Challenge

With the customer support staff straining under the number of enquiries, our client was looking for a way to reduce the load on the customer support team and provide better online self-service for customers.

GOAL

To reduce the number of calls regarding product faults and increase the number of online installation/repair bookings.

MY ROLE

- User research
- Prototyping
- UX design
- UI design

Data analysis

I started analysing website and call centre data to understand what customers were trying to resolve and where they were going to do so.
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The call centre data revealed the majority of the support requests revolved around technical advice, faulty items or spare parts - so the efforts were concentrated here first. When analysing the website data two distinct customer behaviours became apparent. The first wanted to get in contact with the support team straight away while the other searched for a self diagnosis to their issue before proceeding.
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Data collected from the site analytics revealed a high number of users where dropping off through the fault diagnosis flow and there was no clear link to the service booking products. This analysis gave us a solid hypothesis which led the next phases of the research:
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“Customers are dropping off because they are struggling to diagnose their issue which is leading to them simply calling customer support instead.”

Customer Support Team Survey

Around the same time I sent out a survey to the customer support team which gave us more insight into the specifics of customer support requests and common themes/patterns which the team encountered. The survey results corroborated the site analytics and also revealed interesting insights into what exactly the customers were asking.

Usability Testing

After gaining an understanding of the problem through the quantitative data, it was time to analyse qualitative data to better understand the why behind the issue. I conducted usability testing in which I gave each participant example product information and a scenario in which their product would be faulty. This test would help us to identify key issues with important parts of the support flow.

80%

Could not identify their shower unit

100%

Could not locate the correct spare part

50%

Could find the repair landing page, although 80% expressed an interest in the service

Customer journey maps

With the research insight I created new customer journey flows. These proposed flows would not only make it much easier for a customer to diagnose a problem, but would also better connect and drive more conversion to the online repair & service service.

Prototype creation and user testing

To test and validate the designs as early as possible, I created a prototype based on the key support flow which allowed us to validate our design with real users before writing a line of code.

Fault diagnosis

Introduced functionality which helps user identify their exact product
Freetype search for users who already have unit information
Common faults ordered by survey results and analytics review
Step by step approach to fault solutions to reduce cognitive load on user

Contact flow

Introduced subcategory selection to filter users to the relevant support team member and reduce time spent transferring calls
Encourage users toward self service features before showing contact details
List common faults to reduce repetitive support calls

Spare parts selector

Spare part finder functionality to help users identify which part they need.
Step by step identification process functionality which is shared with the fault diagnosis
Ability to pass a user through directly to the spare part from diagnosis flow
Signposts to online repair booking to encourage service booking conversions