Tools used in this project
Analyzing bike customers

Bike customers dashboard

About this project

Project to practice data cleaning and visualization skills in Excel. The data is from a fictitious bicycle company that seeks to analyze its customers in each region where it has branches, they were obtained through a survey made to them when visiting a branch, the data was unified through an Excel file. The following questions are raised:

  • Who buys more bikes? Men or women? What is your average income?
  • What is the most requested occupation or type of bicycle and what is the average income of the customers who purchase them?
  • How far do customers usually travel by bicycle?
  • In what age range are the customers who purchase a bicycle?
  • How much influence does the number of vehicles that the client has to acquire a bicycle?

As part of the process, duplicates were eliminated, values were replaced, the data was standardized and a nested IF function was used to categorize the ages of the clients. Pivot tables were made to find insights and plot data. Filters were also added to analyze whether marital status, education and home ownership are determining factors when purchasing a bicycle, as well as an analysis by region.

Some conclusions:

  • In general, men with an average income of $60,000 tend to be more decisive when purchasing a bicycle
  • The preferred occupation or type of bicycle is professional, and the average income of customers who acquire one is $90,000 - $100,000 per year
  • The age range of customers who purchase a bicycle is middle age (32-53)
  • As expected, greater the distance customers travel less they purchase a bicycle. A similar behavior is observed between the number of vehicles they own, more vehicles less chance there is of purchase and if there are, they look for a professional bike.
  • In Europe the clerical bike is purchased more, while in North America and in the Pacific a Professional bike.
  • The filters considered if they are determining factors when purchasing a bicycle, it is proposed to collect more information from customers to assess the degree of impact they have.

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