Summary Dashboards: Aggregate dashboards that measure campaign performance and ROAS across all campaign types (channels). The platform serves both internal stakeholders and external vendor customers by enabling faceted queering and dimensional analysis across all campaigns, as well as drill-downs to individual campaign performance reports at the SKU level.
Results – The UX exceeded expectations. Behind the scenes, extensive development was necessary to refactor and update systems so they could scale and compile reports in the billions. The dashboards were successfully delivered within six months.
Three Levels – It’s rewarding when UX successfully addresses the design challenge. The solution involves adding extra dashboards tailored to different campaign types. The approach is simple and elegant, offering a clear resolution to the problem. Additionally, the solution scaled well when new campaign types were introduced.
Summary Dashboard – Customers will be able to view high-level metrics across all campaign types in aggregate, as well as key metrics for individual campaigns at a glance. Prioritizing this feature is based on direct feedback from external customers.
Campaign Summary Type – An overall comparison of multiple campaigns provides an overview of key metrics. Customers can quickly view and toggle total Impressions, Clicks, CTR, Delivered Spend, and Revenue, which updates the visualization chart in real-time.
Campaign Performance Report – Able to view campaign ROAS metrics at the individual SKU, keyword, placement, and platform levels. BestBuy Ads offers a unique attribution feature compared to other ad platforms, allowing customers to see (deltas) in-store purchases in addition to online purchases.
Figma Prototype – Completed in just a few months, designed a full end-to-end experience. When a product software team needs to move quickly, I have found that creating a master prototype is the best way to align cross-functional teams. The prototype included multiple design concepts (A/B testing), and stakeholders were able to give feedback on which version best aligned with business and customer needs.
UX Specs – To improve development efficiency, I co-create UX specs for Jira tickets, ensuring the product’s success. Each screen may have 1-10 bullet points and a redline visual with annotations to guide developers on how the UI should function. This encourages the development team to build the correct feature, especially when the team may not have a dev mode for Figma.
Concept Designs – After multiple refinement meetings and negotiations, the stakeholders preferred the two concepts below. In the trenches, I felt close to a UX solution, but the UI model wasn’t fully refined. The team had a significant debate over the use of area charts versus line charts. Playing with the data, we quickly realized that at scale, some line charts would flatline when the data reaches billions of impressions. We ultimately chose area charts as a way to aggregate all campaign types.
Dashboard Ideations – Collaborating with the reporting and insights team (Analytics), we generated several ideas to help customers better understand campaign performance reporting. The design challenge is to evaluate what is practical and achievable, and to leverage existing data for quick delivery. Can we provide a dashboard in 3-6 months without completely overhauling the current database infrastructure?
New Component – A clear addition to the platform was the one-to-many (1:M) multi-select. Previously, the platform couldn’t filter campaigns by a specific brand. Instead, users had to rely on pagination at the footer to find campaigns.
UX Solution – Develop a 1:M component to enable faceted querying, improving efficiency and reducing the time spent searching through campaigns. This component is also used in nine other features across the platform.
System Components – It’s uncommon for a software team to permit a UX designer to rearchitect a platform from scratch. Building trust is essential to foster collaboration within the team to reskin standard controls and develop new components that can scale for enterprise platforms.
UX Observations –My UX journey begins with refactoring the Frankenstein UI. The platform was using multiple frameworks (Material, Kendo UI, and MUI) and lacked a standard UI Style Guide. I created UX improvement Epics and hundreds of Jira tickets to enhance the platform.
Solution – Update to the latest MUI framework. Refactoring the framework will decrease technical and design debt, thereby improving product development efficiency.
The Beginning – When I joined the AdTech team, I was the first embedded designer on the team. The platform looked amateurish, and its UX wasn’t very intuitive or modern. The alpha platform was driven by PMs and developers and wasn’t available to external customers. I was responsible for redesigning the UX and updating the entire end-to-end experience.
