Verizon →
As an Optimization UX Designer at Evolv AI, I created optimized user experiences by leveraging analytics data, competitive analyses, and heuristics evaluations, while employing Verizon's design systems. I structured multivariate user tests while utilizing an AI testing platform and created UI mockups to communicate testing variants across Verizon's websites and mobile apps.
Tools
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Sketch
InVision
Figma
ContentSquare
Adobe Analytics
JIRA
InVision
Figma
ContentSquare
Adobe Analytics
JIRA
Overview
Verizon is a well-known telecom company who wanted to test different user experiences based on KPIs prioritized by key stakeholders. Utilizing Evolv AI's platform, we wanted to pin-point certain changes to the user experience that increased click-through rate, checkout rate, and add to cart rate.
First, we wanted to focus on revenue-generating pages in the funnel on their website and mobile app. These pages included their Shop page, device gridwall, product pages, and checkout flows.
First, we wanted to focus on revenue-generating pages in the funnel on their website and mobile app. These pages included their Shop page, device gridwall, product pages, and checkout flows.
Shop Page (Control)
Research
Looking at competitors and utilizing tools such as Adobe Analytics and ContentSquare, we were able perform a heuristic analysis of what to prioritize in our testing efforts.
Looking at heatmap data on their Shop page, we noticed a higher click-through rate for the Plans section that's lower on the page (About 5% on desktop and 7% on mobile) while also seeing a significantly higher attractiveness rate for that section (Approximately 25% on desktop and 48% on mobile).
These findings told us that users had a high intent to shop for plans on this page, however the section was the least visually appealing, and lower on the page.
Looking at heatmap data on their Shop page, we noticed a higher click-through rate for the Plans section that's lower on the page (About 5% on desktop and 7% on mobile) while also seeing a significantly higher attractiveness rate for that section (Approximately 25% on desktop and 48% on mobile).
These findings told us that users had a high intent to shop for plans on this page, however the section was the least visually appealing, and lower on the page.
Design
First, we created a variant simply bringing plans higher on the page (After the deals section but before the rest of the device-specific sections).
Next, we focused on creating UI designs that brought more information directly to the Shop page that users would otherwise have to clickthrough to view. The hypothesis: Since users have a high intent to shop for plans, showing relevant information directly on the page would reduce friction.
Lastly, we wanted to test UI that was more visually appealing and caught user's attention to increase engagement.
Results
Evolv's AI was able to determine that combining moving the section higher on the page, and changing the user experience to include drop-downs for visitors to have the option to clickthrough for each plan performed best for clickthrough rate.
