Bike Sales Analysis Report

Introduction

This project focuses on analyzing bike sales data from a bike shop to better understand customer purchasing behavior. The aim was to explore patterns in sales based on gender, marital status, and age brackets. These insights will help the shop know who their main customers are and guide decision-making for future marketing and sales strategies.

Objectives

The key objectives of this analysis were:

  1. To determine the average income of purchases per gender.
  2. To identify the marital status of customers who purchase bikes more often.
  3. To categorize customers into age groups and analyze which group buys bikes more.

Methodology

The dataset was carefully reviewed and analyzed by grouping the data into categories:

Gender (Male, Female)

Marital Status (Married, Single)

Age Bracket (Adolescent – below 31, Middle-aged – 31 to 54, Old age – 55 and above)

Statistical summaries and comparisons were made to identify patterns in purchases.

Findings

  1. Average Income of Purchases per Gender

    Males were found to purchase bikes more often than females.

    This may suggest that men have a higher interest in bike usage, possibly for commuting or leisure.

  2. Marital Status per Purchase

    Married customers purchased more bikes than singles.

    This could mean that married people buy bikes not only for themselves but also for family use.

  3. Age Bracket per Purchase

    Middle-aged (31–54 years old): This group makes the highest number of bike purchases.

    Old age (55 years and above): This group also buys bikes, but less than the middle-aged.

    Adolescents (below 31 years): Surprisingly, this group purchases the least compared to the other two groups.

Insights and Implications