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AI Powered Amazon Listings
Design Leadership • UX/UI • Prototyping • Component Libraries • Responsive Web App
Project Overview
Pattern is an e-commerce accelerator that brings brands to new customers and markets. I worked on their Content Team as a Lead UX/UI Designer to build an AI Content Optimization feature within Pattern's PXM software. This feature streamlined and optimized content syndication across multiple channels like Amazon, Walmart and Shopify for 1,000s of product listings.
My Contributions
I used Figma and FigJam to do UX/UI design, prototyping, and information architecture. I managed a team of two other designers and collaborated closely with the CEO, Chief Brand Officer, and Director of AI. This project also called for new components that I contributed to the design system.
Research & Discovery
When marketing managers, e-commerce managers, and copywriters all want the same thing...
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"I can't possibly keep the 10,000 listings I manage fresh with optimized content. I just focus on the top 10% of performers."
Our users—while different personas—faced significant challenges in manually updating content for thousands of listings. As a result, they often focused on the top 10% of performing listings, leaving the bottom 90% as a missed opportunity for optimization and improved visibility. ​
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There was a clear need for an automated tool to optimize the bottom 90% of listings, which often remained neglected due to resource constraints.
How might we help brands easily optimize thousands of listings in order to boost visibility and performance across e-commerce platforms?
Designing the Solution & Results
Empowering AI with brand voice and competitive keyword data​
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To accurately optimize content for multiple brands, this feature needed to take into account each partner's individual brand voice as well as varying compliance rules across multiple channels.
The AI Content Optimization feature successfully launched, improving product visibility and engagement across multiple platforms. The feature received positive feedback from users for its usability and functionality. Key lessons included the importance of ongoing stakeholder communication and the value of iterative design in responding to user needs and executive feedback.
