Analyzing sales data of Nike Products
Analyzing sales data plays a crucial role in the success of a company or business. Higher sales of a product or service brings in revenue and hence contributes to higher growth.
Analyzing sales data means looking at current or past sales data to come up with information or insights about customers’ demographics, behavior, which products they buy, when they buy, how much revenue they generate, how well they respond to promotions, and more.
Here we will analyze Nike’s USA sales data to gather information or insights about their products and customers.
Here is the data after performing initial data cleaning.
The data has around 4000 records and 12 columns or fields. Non we will analyze the data to come up with insights about product sales.
To analyze the data, we will use pivot tables. Let us find the revenues by region also finding the total revenue from sales.
We find that total revenue from sales is around 868 million dollars with the Western region contributing the highest amount (around 32 percent of total revenue)
Let us analyze regional revenue for the month of October by inserting timeline in the invoice date using pivot table.
We find that total revenue for the month of October is around 62 million dollars with west contributing the highest amount (around 31 percent).
Let us find the revenue of the top 10 states.
We can see that New York produces the highest revenue followed by California and Florida.
Let us find the revenue brought in by product category.
We can see that men’s street footwear brings the highest revenue followed by women’s apparel.
Let us dive deeper and analyze the number of units sold in various unit price ranges and product category using slicers and pivot charts.
Here, in men’s apparel category, number of products sold in price range 40–60 is the highest. We can do the similar for other product categories as well.
Let us finish this analysis by creating visualizations and build a report using Power BI which is a business intelligence tool by Microsoft.
