product design

Sell Process redesign

I led the redesign of Trade Me’s sell process to make it easier, faster and smarter to list an item, This project involved working closely with developers, product managers, legal and research teams to ensure the project would reduce the hassle of listing an item for Trade Me users.

The old sell process took a minimum of 26 taps to list an item. I managed to decrease this down to just 7 taps, by implementing smart defaults and reconfiguring the flow to create a more intuitive user experience.

User Research

Existing user research from our repository revealed some key pain-points about the existing sell process and insights into how users list items on Trade Me.

Ideation

I went wide and explored a variety of ways in which we could improve the sell process, taking inspiration from typeform, chatbots, diagnosis tools and other modern ways of collecting information. This revealed two main options..

1. A stepped process

This method would allow users to focus on making one decision at a time, reducing the cognitive load. This approach used natural language that could take conditional information from previous steps, making each task relevant and personal to the item you were selling.

2. A one page process

This method would allow users to have a complete overview of their listing before making it live. Though there would be more decisions presented to a user at once, it would give them the opportunity to make changes more easily, and prevent blockages when reaching a part of the process they needed more information for before continuing. It would help new users to understand exactly what information they're going to need from the get-go.

*Note, example below is iterations of the same page not a flow.

Usability testing

I led usability testing with a range of participants. The goals of testing were to understand users’ perception of the speed and simplicity of the new sell process. I also looked to understand the impact of removing previous fields on users, explore what future ideas are likely to be desirable features. I also looked at how users might re-engage with promotions through post-listing experiences.

Key Findings

  • Visually separating out selling methods in UI made it easier for users to understand the options  available to them.
  • Users expect their previous selections in listing an item to become their defaults
  • Users are delighted by AI being used to pre-fill their listings, providing it is accurate.
  • Sellers value adding a description in the sell process.
  • Sellers like price suggestions, but find them to be inaccurate sometimes.
  • Users expect dismissing a bottom sheet to clear their selection, provided there is a save button they haven’t pushed.
  • Users expect the chips/tags in the sell process to correspond to buyer filters.

Outcomes

This project is currently rolling out to users. Check back soon to see how it went! 

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