Great Expectations (GX) is a data quality web application that helps businesses create flexible rules and apply their industry expertise as Expectations (tests) for their data. Initially started out as a open source tool, GX quickly grew to become one of the fastest growing tool used by data practitioners.
Product Designer, UX Researcher & Designer, Visual Designer
GX Cloud launched in an open beta state, allowing users to sign up and start using immediately. However, we quickly realized that users were not completing the desired user journey and were dropping off before experiencing the product's full value. GX Cloud users were not able to see the expressive tests that were offered. The product relied on open source offerings that had required a steep learning curve to understand and fully take advantage of GX's flexible “Expectations” to run against their data sets.
SOLUTION
Allow users to test out GX Cloud application by offering a demo of the product so users can understand the suggested workflow, features, and value that GX can offer.
GOAL
Increase users adoption rate and use of GX Cloud by allowing users to run and apply Expectations to sample dataset to better understand how GX Cloud can help their organizations.
Launched early during Q1 of 2023, our product team needed to understand how users were interacting with our Cloud product. We spent a few months analyzing user interactions using Sentry replays, conducted users interviews and used user journey mapping to really understand users pains and joys. We mapped out the quickest and ideal path for users to; connect to data, apply expectations, and successfully running the tests to see results.
After a few weeks of analysis, we observed users dropping off at the beginning of the journey due to having difficulty connecting to their desired datasource. The feedback was clear that users were getting frustrated due to:
Having a more clear understanding of our low adoption rate we began to discuss what potential ways GX can quickly showcase the value or "Aha moment" to users. Users would need to achieve this point in the journey to be able to fully understand the value our Cloud product offered.
We quickly spent some time researching both our competitors along with other relevant and similar products within the industry. This was important as the need for data quality has only grown in importance over the past decade. After analysis of similar products we noticed some similarities and slight differences in approaches from product to product.
After some discussion and understanding of the various approaches we reviewed this with our Product team to better improve our MVP flow to reduce drop off rates to allow users to better see the value of GX Cloud. We ultimately landed on a guided path tutorial approach.
CONSTRAINTS
Having alignment on the approach to take our team needed to also take constraints into consideration:
The main goal is to allow users to successfully navigate onboarding and being able to test out the "Expectations" that GX Cloud offered. Code name Demo Data, our team quickly iterated on changes to the MVP flow that would allow users to get to GX Cloud's value moment. In my 3 years of working at GX this was by far one of the most successful feature releases.
You can press "Z" to change the scale of the prototype.
The release of Demo Data was a huge success overall. We successfully increased users' completion rate by 300%, an increase from around 30-40%. This was a huge feature release for us as we were able to observe more users complete the intended journey while being able to better understand critical pain points.
While working on this project I was also simultaneously working on another feature to leverage AI and have Expectations recommended to users based on their data. We needed to make sure the Demo Data release was not conflicting with the parallel AI feature work.\
Considering Constraints
Keeping limitations in mind when working on feature work is very important. Recycling existing components with minimal design changes and tweaks to fit within scope and timing of the feature release.
I very much appreciate the opportunity to work on such an amazing product, taking part in so many different types of work and learning so much along the way. Unfortunately our company workforce was reduced in half in Q1 of 2025.
On April 30, 2025 I welcomed my first born son Ari to the world! I took this as an opportunity to take some extended parental leave and learned so much on the difficulties and joys of being a parent.
