Creating a CX Research Tool Vision for Amazon
UX Strategy
In January 2020, I was hired at Amazon Customer Service to lead an effort to redesign a set of internal tools used to analyze research data at scale across Amazon - from Devices and Digital Services to transactions on the Shopping website internationally.
The original version of the base analysis tool was created in 2014 and over the years had organically evolved to include serval tools ranging from data aggregation to data visualization. However, the growth was not strategically planned and the development team behind the internal tool was looking for help to restructure the application to be more usable.
The business team supporting this tool saw challenges in Amazon teams adopting their data-secured tool to understand Customer Experiences and wanted guidance on what types of research Amazonians were trying to accomplish and how we can meet their needs.
The version demonstrated to me in January of 2020 was a dashboard tool with complex database-like instructions meant to help anyone at Amazon explore the data that Amazon Customer Service was collecting about their Customer Experience. However, based on a series of interviews conducted in March of 2020, it became clear that most owners of Amazon business lines were not aware of the tool or were too intimidated by the experience to feel comfortable exploring on their own.
In fact, there had been a growing set of Amazonians who had become experts in the tool and had spent significant time learning how to navigate the interface to create reports. These VOC Experts mentioned in interviews that they were constantly being flooded with requests for one-off reports and felt that most Amazonians were disconnected from their real-world Customer Experience because of the steep learning curve and inability to simply explore data on their own time.
Based on this initial March 2020 series of interviews, the team took time to consider other styles of Customer Experience and User Experience research. We observed how people used more commercially-available tools such as Enjoy HQ and Sprinklr. We also considered the evolution of other internal tools and ways they had evolved to gather more adoption throughout the enterprise. This led to insights about how data visualization and exploration of Natural-Language Processing from textual information was different from quantitative analysis and how the process of quantifying qualitative behavior needed more flexibility to try new ways to analyze and share reports.
The initial redesign began in earnest in July 2020, with a focus on how to help Non-Technical Users feel comfortable exploring data sources containing 400+ data fields. Challenges in these workflows included things such as understanding where the augmented data was coming from, translating technical system terms into terms that related to the Amazon business owner's point of view, and allowing for more flexibility when it came to building out dashboards and trying out different data visualizations.
The long term vision focused on the core insights we gathered from the Discovery Research and first build of the redesigned data visualization experience.
Namely, these fell into three distinct types of behaviors when it comes to analyzing Customer Experience datasets: Discovery of new insights and trends, Analyzing the impact in quantitative terms using both segmentation and trends over time, and Sharing these reports with colleagues in ways that encouraged collaborative work.
Do you have an idea? Do you work with emerging technology or want to help reach underserved populations with digital tools?
Reach out and let me know what your passion is and let's make the future happen together!
