Bicycle Business Intelligence

Tools used in this project
Bicycle Business Intelligence

Power BI Dashboard

About this project

Remember April 2020? Covid lockdowns and beautiful spring weather- when you dusted off those handlebar streamers and all the kids in the neighborhood finally learned how to ride a bike? Bicycle sales were going gangbusters.

But what if you opened a bicycle store that year- no name recognition, new business growing pains, missing out on the brand loyalty established shops were garnering at the time? This is a multi-page BI dashboard of three years of sales data from a manufacturer of bicycle equipment that opened in 2020.

The first page is a high-level overview showing sales KPIs, Revenue trending over time, monthly metrics compared to the month before, Total Orders by Product Category and by individual Product, as well as the most ordered and most returned product type. Revenue has continued to increase over time, but the rate of that growth is slowing.


Monthly Revenue is up from last month and Monthly Returns are down from last month, but Monthly Orders (in red) are lower than the month before.

undefinedThis page can be filtered by Region from the side panel, by Year with the slider on the Revenue chart, or by category by selecting a bar on the Orders by Category chart. Any product in the Top 10 table can be selected (right-click > Drill through> Product Detail) to display its Product Detail page, which shows Sales Gauges with targets 10% above the prior month, Profit over time, and all other metrics over time for the selected product. this allows us to identify which individual products are under-performing and how.

undefinedWe can also compare regional performance on a map, with bubble size indicative of Orders, which can be filtered by region.

undefinedThe last page, Customer Detail, shows Total Customers and Revenue per Customer over time, as well as a breakdown of customer by Income Level and Occupation. Regardless of demographics, Revenue per Customer is decreasing. We can use the Top 100 Customers table and slicers to view high-value customers for targeted advertising or rewards.


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