Overview
Threaded Relief is an e-commerce website dedicated to raising awareness towards today’s most prevalent issues and events. The proceeds for all t-shirts sold go towards various charities, relief funds, and awareness programs.
Project Timeline
March 2019 - Ongoing
Problem
Visitors to the mobile website are not continuing to click through
Most of Threaded Relief’s traffic currently comes through social media paid advertising. Currently the bounce rate from this traffic is 62% and they hope to increase engagement with their visitors.
Solution
Make it easier to continue shopping through campaigns while applying best practices to increase usability
(1st pass solution, this project is ongoing)
Breadcrumb feature
“Shop by campaign” suggested products feature
Apply heuristics to make minor changes and increase findability
The process
Usability testing
I began by conducting some usability tests, asking online shoppers how they would go about evaluating a specific product and what they would do if they wanted to continue browsing the website.
5 out of 6 scrolled to the bottom, skimming the information
3 of 6 scrolled down, then went to the navigation to continue to shop
1 of 6 scrolled to the bottom and decided they would have just left at this point because they didn’t like the current product offering. They identified themself as a big amazon.com shopper and jumps from page to page using amazon’s various recommendation features
Key Insight: Attention span is short with mobile online shoppers, and many want to be guided along their browsing journey.
current website Analysis
Looking at the customer’s e-commerce journey, we can see their experience consists of everything from awareness until loyalty. This project focuses on the website touchpoints in that process: Evaluation and Ordering.
If I break up these two phases further, there are a number of attributes that contribute to a user’s experience while on the website.
Guided by usability test results, I conducted a heuristic analysis with 6-10 targeted questions in each of these sections. We can see that the Threaded Relief website has some strong points, specifically in the transaction space, but is falling short in the evaluation phase.
Heuristic Analysis Results
Specifically, the “Purchase Decision Making” section is especially weak. This section is evaluated on how easy it is for the user to have all the information on a product they need to make a decision, based on questions like:
Is there enough information about the product displayed?
Does the user have a way to compare products?
Does the user have a way to read customer testimonials?
Are there suggested or featured items?
Current User Flow
Focusing on purchase decision making, what is the current customer user flow at this point?
I am addressing the exit point when users are deciding on the individual item they are looking at. How can design help users who decide against a particular design on the item, towards continuing to engage and browse the other items on the page.
Design Hypothesis
Competitive Analysis
One of the features utilized to address this hypothesis is breadcrumb navigation. Below are two different methods of using a breadcrumb on the webpage.
Best Buy’s breadcrumb navigation only shows one step back in the breadcrumb, allowing users to orient themselves without taking too much real estate. The Etsy breadcrumb shows a more holistic view of where the user is on the site, but because of the long text, gets cut off.
A second feature that can address our design hypothesis is a recommended products section. Looking to these examples below, I focused on comparing header copy & tone, photo style, content displayed, and scrolling affordances.
The Design
Consolidating our findings, I’ve come up with the first iteration of the updated design.
Results & Next steps
The results of usability tests on the updated design so far seems reasonable; those tested generally agreed that the experience matched their mental model of an e-commerce site. I am working with the business owner and a developer to implement these changes.
Once updated, we will take a look at the analytics to see if our changes have made a difference to the bounce rate. From there we will work to iterate and test again.