Bunnings Filters Research
I led a primary research discovery piece to understand why the current filters usage on the Bunnings website was so low.
Data and Analytics
I first engaged the Data Analytics team around some current data in regards to filter usage on the current Bunnings website. I found some staggering numbers which I confirmed and shared with some members of the squad. In summary, there was extremely low usage of filters. Of those customers that used filters, there was a higher conversion rate.
Research Board
I started putting together a board of data, numbers, landscape review and industry best practises from the likes of The Baymard Institute. With this, I formed some hypothesis which I wanted to validate with some customer interviews and testing.
Customer Research
I worked together with a User Researcher to set up remote customer interviews to understand why customers weren't engaging with filters and to validate what would increase filter usage.
Synthesis
Together with the User Researcher, we focused on key questions we wanted to answer.
Reporting and Playback
I created a final report of findings which I then organised playback sessions with stakeholders and the squad.
Outcomes
This piece of research helped paved the way for first change to the products collections/search results pages. Surfacing the Sort By filter helped decrease drop off rates on these pages. It will play a major role in forming upcoming roadmaps and to improve the Bunnings e-commerce filters experience for customers. Things around more product specific filters and the exploration of key/popular filter selections.