Greenfield – Jobs to be Done
Discovering the 'Discover' Job to be Done. Going beyond personas, the Jobs to Be Done research approach informs a product of what jobs a user 'hires' the product for.
Pitching the Greenfield Team
With over 300,000 unique users, and a B2B and B2C model, using personas to build new features and iterate on an existing product becomes challenging. Instead of personas, I employed a Jobs to be Done (JTBD) approach to inform the UX work of the product.
One of the jobs users "hire" Greenfield to do is to discover visualizations and reports created by Data Product Managers, Data Analysts, and others. By diving the work into different jobs, the Greenfield team used this framework to prioritize the product work.
This was a new approach to the Greenfield team, so I had to pitch the idea of JTBD through education and training the team in user research.
Discovery is a shared problem
Greenfield’s users are Data Product Managers, Analysts, and business partners who need to find work other people made. Understanding how they search, and what they check before they trust a result, shaped the whole Discover experience.
Multi-Method Research Plan
To inform the Discover Job to be Done within Greenfield, I outlined a multi-method research plan over the course of 2 months that included a remote, unmoderated Tree Study with 50 participants, over 20 user interviews, 2 System Usability Scale (SUS) Surveys, and 2 usability studies for the existing Discover experience.
This information was quickly adopted by the Greenfield team and inspired other products within Data Science to request a similar approach.
All Users — Greenfield
The journey map captured user feelings, thoughts, and opportunities across three main discovery tasks: Find a Dataset, Find a Card, and Find a Dashboard. Insights revealed that the journey does not differ significantly from user to user — a key finding that streamlined the design direction.
Discover Dev Prototype
Discovering data visualizations and reporting is a complex task for users, often requiring a combination of search queries, sorting, filtering, and navigation. I designed this mid-fidelity prototype as a proof of concept in Figma, and discovered the interaction nuances a prototype could reveal to test concepts with users and complete a deep dive into the navigation.
I led a Design Sprint and worked with the Greenfield team to create an ephemeral environment that can be updated and tested by users. The dev environment allowed for rapid testing, reducing my design and research time down from 6 months to 2 months.
Want to learn more about this case study? Get in touch today.
Get in Touch