Project Overview

Client: TigerData
Industry: Software Development (Developer Tools, Cloud Data Infrastructure)
Timeline: 4 weeks (2024)
My Role: Product designer

Tiger Cloud provides cloud-based database infrastructure and management tools, helping teams deploy, monitor, and scale their databases with ease. A key differentiator of the platform is hypertables — once set up correctly, they unlock the platform’s full capabilities.

Our Hypothesis

At the time, hypertables were underutilized despite being a core feature of Tiger Cloud. My team hypothesized that increasing hypertable adoption would drive greater usage of other features. This project aimed to test that idea and see whether higher hypertable adoption would lead to increased data ingest.

My Role

I led the design of this experiment, working closely with the PM and front-end engineer to shape a workflow that would maximize adoption and guide users in a meaningful way. My responsibilities included:

• Designing the hypertable creation flow and interactions

• Identifying the optimal moment in the post-service creation flow to introduce hypertables and maximize adoption

• Validating the workflow through QA and internal testing

Solution

We introduced a "hypertable creation wizard" that appears immediately after a user creates a service, while the service is spinning up. This moment serves two purposes:

• Educates users about hypertables and their benefits

• Lets users run queries in real time to see hypertables in action

The flow then naturally leads to the data ingest screen, allowing users to start uploading their data as soon as the service is ready.

Key improvements:

• Contextual learning at the moment of need

• Reduced friction in adopting a core platform feature

• Clear path from service creation to active data use

Below is a demo of the feature:

Impact

The experiment drove a 50% increase in hypertable adoption, with 87% of those users ingesting 10GB of data. While this specific experiment is no longer in production due to a reimagined workflow, it provided valuable insights for future iterations.