PitchSide Pro - Revenue Intelligence Dashboard

Hello everyone,

I wanted to share my submission for the Power BI DataViz World Championships - A 5 Page report called PitchSide Pro - Revenue Intelligence, built around five years of sales and traffic data for a fictional football merchandise retailer.

The brief was straightforward:
Explain what’s driving revenue performance, and recommend where the business should focus next.

What made this project interesting wasn’t the complexity of the data - it was how misleading the “obvious” story turned out to be.

Starting Assumption:

Going in, I expected a familiar pattern:

• Tournaments drive revenue
• Major markets dominate performance
• Traffic growth fuels sales

But once I started exploring the data, those assumptions didn’t hold.

What Changed:

Instead of reinforcing expectations, the data challenged them: 

The business behaved more like a seasonal retail brand than a sports-driven one

Growth was already happening in under-invested regions, not just core markets

The biggest opportunity wasn’t traffic -it was conversion efficiency

At that point, the goal shifted.

This was no longer about building a dashboard to summarize performance - it became about building a narrative that explains why the business behaves the way it does.

Approach:

The report is structured as a progression, not a collection of visuals.

Each page answers three questions:

1. What would we normally expect to see?
2. What does the data actually show?
3. Why does that change the decision we should make?

This helped keep the focus on decision-making rather than exploration.

Key Design Choices:

• Story-first structure: Every page builds toward a conclusion, rather than standing alone.
• Dynamic decision framework: Recommendations are supported by a Decision Impact Score (built in DAX), combining opportunity size, trend direction, and supporting evidence - so confidence updates with the data.
• Consistent experience: All pages use HTML & CSS-based layouts with a shared visual style to feel like a single product, not separate report pages
• Insight layering: Key metrics include hover-based context to explain why they matter, not just what they are.

Outcome:

The final recommendations weren’t based on new ideas or assumptions. They came from patterns already visible in the data -just not prioritized or fully recognized. This was an incredibly fun dataset to work on.

A big thank you to Microsoft,  & slindsay for organizing this challenge. ✨

I hope you enjoy exploring this dashboard as much as I enjoyed building it. Your feedback and suggestions are always welcome 🙌

eyJrIjoiMzA3ZjA5M2QtZWYwOS00YmY4LTk0NWEtYmQwOGEzYjI1ZWNiIiwidCI6Ijg0MmU0ZTBlLTFjNjMtNDE0Ny1iNWJjLTJiOGJhZWQyZjk5OCJ9&disablecdnExpiration=1782440082