Archive

An in-house digital destination that customers can search through to find active in-production styles similar in fit to their favorite Levi Jean

My role

UX Designer, Visual Designer, Intercation Designer

Team

Joanna K. -UX Designer

Joana C. -UX Designer

Luisa R. -UX Designer

Alex A. -Front End Developer

David D. -Front End Developer

Mindy M. - Marketing

Tools

Figma, Photoshop, Illustrator, Asana, Figjam

Overview

Levi Strauss & Co. Denim Decoted Hackathon was a competition open for the first time to the public that gathered 12 startups and visioners to generate innovative and scalable business solutions that enhanced the online shopping experience.

Our team was the only one that was created in the first few days of the hackathon from scratch and competed against teams that have dedicated years to the size and fit problem faced by the clothing industry.

Problem

42% of online returns are attributed to fit and size, which continue to be one of the primary reasons for returns

People are disappointed when they buy a product that doesn't fit.

1 in 3 Levi customers return items they purchased the online store

Solutions

Help comsumers indentify their right size

Increase consumers's satisfaction

Decrease the % of online returns

Market research

The first step was to understand the needs of customers shopping online and learn about their problems related to shopping and returns. My goal was to determine how we could help Levi's customers of all shapes and sizes to confidently find products that match their style and fit preferences.

Despite the need for AR tools, 88% of shoppers still rely on photos, reviews, descriptions, and sizing guides.

Source: Narvar Costumer Returns Study, 2021.

Understanding the users

After reviewing market research and conversations with Levi's team, I conducted user interviews to gather qualitative and quantitative information on people’s shopping online.

I conducted 3 in-person and 1 virtual user interview to gain perspective from current and prospective Levi Strauss & CO customers located in the US.

I compiled all the data received into an affinity map. This gave us insights and common trends for users. As a team, this was key to prioritizing our design.

Levi's customers

User interviews

24-38

Age range

Interview insights

It’s tricky because it also goes hand in hand with the body type, not everything looks good on every body type.

Still finds it difficult to shop online because dimensions vary so much.

I would like to have easier and faster options to buy jeans than finding measurement charts.

I wouldn't feel comfortable taking pictures of myself to use an AI/AR tool because I don't know where else this data will be used for.

Key findings

Who are we designing for?

Based on my research conclusions, I was able to create a user persona to help establish the problem that needs to be solved, focus and inform our design decisions, and further empathize with our users. Persona Returning customers emerged from our affinity map.

Customers shop for items on the online store with a general fit and style in mind, usually the same fit and style as the current Levi jeans they own. There is a general confusion about different styles and most customers shop for themselves.

Levi's customers struggle with picking the right size and fit without the physical experience of the product.

Ideation/ Reality

Our focus had been primarily on finding solutions to find the best fit for all clothing products as a shirt, jeans, and jackets. However, due to time constraints and limited access to Levi's design guide, we decided to focus on jeans only.

We came up with an in-house solution called “Archive” where Levi’s customers will be able to scan or plug in the product code (PC9) of their best-fitting jeans and find similar jeans by fit, color, material, etc.

First-time customers will be able to input their measurements in the archive page and receive recommendations based on their desired fit, color, etc.

Flow diagram

To outline all the necessary functionality I created a simple diagram of the main task that Levi's customers can do. One of the flows shown below is dedicated to returning Levi's users who want to find the best-fitting jeans on the website as quickly as possible.

Low-fi wireframes

Once the flow diagrams were established, I started creating the low-fidelity wireframes for all oh the flows. Screens below have been created for returning Levi's customer.

Usability test result for Lo-Fi wireframes

I facilitated 3 rounds of usability testing. Each round has five tests to discover any issues that might arise for the users in the proposed prototypes. This was tested over the Maze platform where I introduced the user to the app and asked questions regarding the tasks.

77%

Set up preferences to receive personalized recommendation

70%

Finalized purchase of a recommended product based on tag

58%

Found a product that they like and is close to their size.

Style Guides & Assets

In preparation for the high-fidelity prototype, I studied Levi’s website and native mobile app to create a style guide. I discovered that the site is product image-heavy, has very few illustrated graphics, and primarily only uses red and shades of black throughout the site.

With this in mind, I created a logo and icons for Archive that match the style and colors of the existing UI kit.

The Algorithm

I collaborated with developers to create an algorithm solution using data that was given to us by Levi's team. Because of the proprietary nature of the data, we received I presented only a part of the outcome.