DETAILS
Project Timeframe : 3 years for MVP Launch & 2 product revisions
Problem Space
Data is hard. If there's one truism I've learned in my almost eight years designing data products for enterprise customers, it's that data is hard. Especially when data is not a user's full-time job. In this product, our goal was to design easy-to-use data products for marketing users in companies such as Nike, Microsoft, Lyft, and Fitbit. Our users needed to be able to create and modify their data model, join tables, import and export data, and create queries in a no-code environment.
Approach
I was the design lead and researcher on the product suite for three years, from the initial launch of core functionality (screenshot 1, above), design revisions into the Constellation view (screenshot 2), data filtering functionality in email (screenshots 3 and 4), and data sync functionality between Salesforce Sales Cloud data objects and the Marketing Cloud data model.
I was the primary UX representative for the design team with product and dev partners. I managed deliverable timelines and work quality for designs while conducting formative and evaluative research.
Results
We designed, tested, iterated, and released key UI updates to the data modeling component over an 18-month period after the beta launch, resulting in increased usability and customer satisfaction. Current customer pain points around Contact Builder center on product suite integration and performance with large data sets.
Much of our work from 2015 continues to incorporated into a newly-announced (2019) Salesforce Audiences product. Findings from the learnability study have been used to guide other UX teams who are working to increase self-service capabilities for our more complicated user task flows.
Lessons Learned
On this project, I learned how UX can truly be a part of a well-functioning product team. We were incorporated in every aspect of the product development, from product roadmap to engineering sprint reviews. I upleveled my agile skills, helped discover and write requirements, and gathered user data to guide the product from the initial MVP launch through two redesigns.