MICROSOFT AZURE Machine Learning

Sr. Lead UX, Interaction & Visual Designer
2014 - 2015



Azure Machine Learning is a powerful cloud-based predictive analytics service for Data Scientists that makes it possible to quickly create and deploy predictive models as analytics solutions. 

After the products Public Preview announcement the telemetry numbers came in with a conversion rate of 1.18% which was extremely below Azure's benchmark standards to allow a product to launch as General AvailabilityHaving not worked on the product before, I was asked by leadership to evaluate and determine where the product needed UX improvement.


After I evaluated the product I identified a huge speed bump in the adoption rate for the products 1st time UX. It took a total time of 30+ minutes to sign up for the product and to actually use it. I worked with my Director of Design to create a adoption funnel presentation of findings which was presented to leadership at a all hands offsite.

View Findings >

Our presentation gained a great deal of traction as a action item and a task force was spun up. I worked with the task force by evaluating the initial 1st time UX and drove new UX designs to improve service adoption and retention.

We discovered one of the main reason why users were having such a hard time signing up for the service was they needed a Azure Subscription before they could even install and evaluate the product. Creating a Azure Subscription unfortunately is a daunting task on its own and something that we could communicate to the Azure team but nothing we could address ourselves in the near term. Our focus was to create a friction free "Try it now" option for users so they could immediately try our product without too many barriers.

I developed several UX wire-frame decks that outlined proposed solutions. Each iteration was presented to the task force for feedback. 

View Wire-Frame Deck >

Once several scenarios were finalized I worked on turning them into visual designs and teamed up with my Design Researcher on our team to run several user research sessions. We tested language and interactions to determine which flows resonated best with our customers.



Designs were finalized and implemented into the product. The end result was a new improved UX that resulted in a increased conversion rate of 29% which was a huge bump from the original 1.18%. This exceeded all expectations and met Azure's benchmark standards.