Welcome to the Bike Sales Project! This project analyzes sales data of bikes from different regions. The dataset contains 13 columns:
Martial status Gender Income Children Education Occupation Home Owner Cars Commute Distance Region Age Purchased Bike
The main objective of this project is to analyze bike sales data and derive insights to inform business decisions. The analysis includes data cleaning, categorization of age groups, visualization of key metrics using pivot tables, and creation of a dashboard to present the findings.
Age Categorization: A new column "Age Ranges" was added using an IF function to categorize ages into three groups: "Adolescent" (less than 31), "Middle Age" (31 or older), and "Old" (ages over 55). Removal of Duplicates and Null Values: Duplicates and rows with null values were removed to ensure data integrity.
Average Income per Purchase: A pivot table was created to visualize the average income of customers who purchased bikes. Customer Commute: Another pivot table was used to analyze the commute distance of customers. Customer Age Ranges: A pivot table was generated to display the distribution of customers across different age ranges. Ratio of Buyers and Non-Buyers by Region: A pivot table showcased the ratio of customers who purchased bikes versus those who did not, categorized by region.
The analysis of bike sales data provides valuable insights into customer demographics, purchasing behavior, and regional trends. These insights can be used to optimize marketing strategies, target specific customer segments, and drive business growth.