What is Cerebrum?
Cerebrum is an internal tool at Cultfit that serves as a robust analytics platform to enable various teams to analyze user data and event metrics from our consumer app.
Unlocking the full potential of analytics for everyone.
The tool required users to write SQL queries to retrieve meaningful data—something not every user felt comfortable doing. This limited the tool’s effectiveness for users who didn’t have technical expertise.
Additionally, the tool produced single data points or analytics, which in isolation didn’t provide much value. What the users truly needed was the ability to combine multiple analytics that represented a full product flow or user experience.
This tool was used by a wide variety of teams within the company.
Use the tool to analyze product performance metrics.
Very comfortable writing SQL queries.
Use the tool to monitor product flows and gather insights.
Somewhat comfortable writing basic SQL queries.
Use the tool to analyze user behavior on the app.
Not comfortable writing SQL queries.
Use the tool to assess campaign effectiveness.
Not comfortable writing SQL queries.
Empower users to build custom dashboards, allowing them to analyze key metrics from their product areas effortlessly.
Our north-star vision for this project was to create a seamless, code-free experience, enabling users to track and visualize data without technical barriers.
Exploration 1: A visual SQL builder.
To simplify dashboard creation, my initial approach was to introduce a visual SQL builder—similar to tools available on the market. This would allow users to construct queries without writing SQL manually. While this was a step in the right direction, a key realization emerged:
Most analytics users needed were already being created by engineers.
Instead of building queries from scratch, users primarily needed a way to combine existing analytics into dashboards relevant to their workflows.
This insight pushed me to rethink the approach. Instead of just simplifying SQL, what if we could eliminate the need for writing SQL altogether?
Exploration 2: A more intuitive approach.
Before designing solutions, I needed to understand the steps involved in creating a dashboard from scratch. Mapping out this flow helped identify friction points and opportunities for improvement.
Inspired by platforms like Canva, which democratized design through an intuitive drag-and-drop interface, I explored a similar approach for Cerebrum. This new concept focused on:
A Reusable Analytics Library – Users could browse, search, and select from pre-existing analytics rather than creating new ones from scratch.
Drag-and-Drop Dashboard Builder – Instead of dealing with queries, users could assemble dashboards visually, combining different metrics with a few simple actions.
This direction resonated well with all stakeholders, validating the need for a more intuitive experience. With this alignment, I began refining the concept to make it more concrete.
Abstracting Complexity to Empower Non-Technical Users
The first step in solving this problem was to abstract away the technical complexity. Instead of requiring users to write queries, we created predefined, simplified data views that aggregated data into key metrics (such as "Page Views," "User Engagement," and "Conversion Rates"). Think of these as pre-built reports. A view is essentially a simplified version of a query that aggregates complex data and presents it in a way that’s more understandable for users.
Structuring dashboard discovery
With the dashboard creation process taking shape, the next challenge was: Where does this experience start?
Users needed a clear entry point to access both their own dashboards and those shared with them. Since everyone on the team had access to all dashboards, it was essential to provide organization and differentiation to prevent clutter and confusion.
Key Considerations:
How do users find dashboards they’ve created?
How do they access dashboards shared by others?
How do we categorize dashboards to reflect their purpose and ownership?
These explorations did not enhance discoverability at scale and would potentially complicate the process.
The new dashboards section
Housed within the analytics, the new dashboards section allows users to create, view and share dashboards that have important data points about the user within a particular product flow.
New dashboards section housed within the analytics
Contextual icons to help users quickly scan the dashboard's focus.
Expanded list view
Anatomy of an analytics card
Everything coming together
Starting the design process backward.
When I started this project, the stakeholders already had a clear vision for the final solution, which challenged the traditional design process I was familiar with. Although I had creative freedom, most of my effort was spent figuring out how to bring their ideas to life. This experience taught me that real-world design is rarely linear. Starting with a solution rather than the problem wasn’t easier either—it required its own process of understanding the rationale behind the vision and refining it to make it more user-centric. Ultimately, this project helped me realize that the design process is about adaptability, navigating constraints, and finding the best way to solve a problem, even if it means working backward.
