I analyzed bike sales dataset, and created a Bike Sales Performance Dashboard using Excel.
The bike company want to know what influenced Individual customers that got a bike, what's attributes customers that got bikes and the ones that didnt possess. The dashboard consists of various charts and slicers that provide insights into bike sales performance based on parameters such as customer demographics, customer distance, occupation, income, and age bracket. In this report, I will present the trends and insights obtained from the dashboard, draw conclusions and provide recommendations.
Steps I took are highligted below:
- Data Cleaning: Removed 26 duplicate values, to avoid data redundancy. Left with 1000 unique values.
- Data Processing & Manipulation: I changed some columns data to what we can easily comprehend in visualization. In the marital status column, M text was replaced with Married, while S text was replaced with Single. In the Gender column, M was replaced with Male, while F was replaced with Female. I added a new column for Age Bracket (<31=adolescent, >=31 =middle age, >50 = Old).
- Data Visualization and Reporting: Used Pivot to create the dashboard.
Trends and Insights
Based on the data analyzed from the dashboard, the following trends and insights can be observed:
- Bikes are popular among customers who live within a 10-mile radius of our stores. Customers who live beyond a 10-mile radius tend to purchase bikes less frequently.
- Customers who are married tend to purchase bikes more frequently than those who are single. However, customers who are homeowners tend to purchase bikes more frequently than those who are not homeowners.
- Customers with higher education tend to purchase bikes more frequently than those with lower education.
- Customers in the age group of 31-49 tend to purchase bikes more frequently than customers in other age groups.
- Customers who have children tend to purchase bikes less frequently than those who do not have children.
- Customers who stay in the Europe region tend to purchase bikes more than customer in the North America, and Pacific regions.
- Sales of bikes are higher among customers with higher income levels, particularly among male customers.