Customer Data Visualisation

Customer Data Visualisation

Contents

TOC o "1-3" h z u 1.Introduction PAGEREF _Toc132828598 h 32.About Dataset PAGEREF _Toc132828599 h 33.Dashboard based on profession PAGEREF _Toc132828600 h 34.Male and Female in each Profession PAGEREF _Toc132828601 h 45.Profession, Gender and Avg. Annual Income PAGEREF _Toc132828602 h 56.Profession and work Experience PAGEREF _Toc132828603 h 57.Spending Score Overview Dashboard PAGEREF _Toc132828604 h 68.Family size and Spending score PAGEREF _Toc132828605 h 79.Profession and Spending Score PAGEREF _Toc132828606 h 810.Employees Spending Dashboard PAGEREF _Toc132828607 h 811.Family size and annual income PAGEREF _Toc132828608 h 912.Gender Age and Annual income PAGEREF _Toc132828609 h 1013.Experienced Annual income PAGEREF _Toc132828610 h 1014.Persons in each Profession PAGEREF _Toc132828611 h 1115.Professionals Spending Score PAGEREF _Toc132828612 h 11

List of figures

TOC h z c "Figure" Figure 1: Dashboard based on profession PAGEREF _Toc132828026 h 4Figure 2: Male and Female in each Profession PAGEREF _Toc132828027 h 4Figure 3: Profession, Gender and Avg. Annual Income PAGEREF _Toc132828028 h 5Figure 4: Profession and Work Experience PAGEREF _Toc132828029 h 6Figure 5: Spending Score Overview Dashboard PAGEREF _Toc132828030 h 7Figure 6: Family size and Spending score PAGEREF _Toc132828031 h 7Figure 7: Profession and spending score PAGEREF _Toc132828032 h 8Figure 8: Employee Spending Score PAGEREF _Toc132828033 h 9Figure 9: Family size and Annual Income PAGEREF _Toc132828034 h 9Figure 10: Gender Age and Annual Income PAGEREF _Toc132828035 h 10Figure 11: Experienced Annual Income PAGEREF _Toc132828036 h 10Figure 12: Persons in Each Profession PAGEREF _Toc132828037 h 11Figure 13: Professionals spending score PAGEREF _Toc132828038 h 12

Introduction

In this task we required to create a dashboard to which easily visualize and help us to understand the attributes and their dependencies. For example, Employees Spending behaviour are depends on their salary, family size, gender also their age. It is difficult to finding which factor are more effected spending. In which profession number of males and female more what is highest salary. Persons salary is depending of their work experience. There are many factors which depends each other. Visual representation of that factors easily understandable any person or business man can easily understand through visualisation. So here our aim is to create insightful attractive dashboard.

About Dataset

Data Source - https://www.kaggle.com/datasets/datascientistanna/customers-dataset

The mobile dataset contains information on customer id, spending score, age, gender, profession, annual income, family size and work experience.

Customer Id: Unique customer id.

Gender: Employees gender are given.

Age: Employees age.

Annual Income: Employees Annual Income.

Spending Score: Employees spending score are given in range (0 -100).

Profession: Profession of employee are given.

Work Experience: Employees work experience are given in year.

Family Size: Number of family member.

Business Requirements

The user is a business leads who is interested in understanding the relationship between product / customer attributes and/or demographic variables. Income, work experience, spending score and profession will be used to get more insights and compared at different time horizon and at different categorical/nominal attributes.

They have following specific questions:

What is distribution of customers by gender?

What is distribution of annual salary by gender?

How are sales/profits numbers are changing with time for different demographic attributes?

Design

Here we specify the main requirements in terms of the relationships that must be visualised in order to answer each question. To develop the data visualization tool, Tableau or PowerBI will be used for developing different graphs to answer each question listed above.

An indicative list of graphs is provided below to answer the above questions:

Pie chart

Horizontal Bar chart

Horizontal Bar chart overlaid line chart

16764060960Pei chart will be drawn to understand the customer composition by gender and profession

00Pei chart will be drawn to understand the customer composition by gender and profession

1676405117465Profession-wise average annual income distribution for Male and Female

00Profession-wise average annual income distribution for Male and Female

29870404987925Profession-wise average annual income distribution with average work experience. Here, X axis is the profession and Y axis is average annual income

00Profession-wise average annual income distribution with average work experience. Here, X axis is the profession and Y axis is average annual income

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Dashboard based on profession

Figure 1: Dashboard based on professionThe above dashboard shows professions wise annual income work experience and number of male and female in each profession.

Male and Female in each Profession

Figure 2: Male and Female in each ProfessionIn fig. 2 donut chart shows total 1186 female employees are there and total 814 male employees are there. From this donut chart we can easily see in every profession female employee is more than male employees.

Profession, Gender and Avg. Annual Income

Figure 3: Profession, Gender and Avg. Annual IncomeFig.3 Shows bar graph which represent gender, profession wise annual income. We can easily see executive role or profession female salary in highest then other profession.

Profession and work Experience

Figure 4: Profession and Work ExperienceFig. 4 shows average annual income and average work experience. In this plot bar graph show professions wise average annual income and trend line showing profession wise average work experience. We can easily see homemaker have highest work experience as compared to other professions but average annual income is low for homemaker.

Spending Score Overview Dashboard

Figure 5: Spending Score Overview DashboardThe above dashboard shows overview of spending scores like family size and profession wise spending score and Annual income-based spending score. From this dashboard a business man or persons easily understand which factor is more effect the spending score like family size or annual income.

Family size and Spending score

Figure 6: Family size and Spending score Employees has 1 to 9 members in their family. More employees family member is 6 and 7 but, their spending score is 50. Highest spending score is approximately is 52 and their average family size is 4. The lowest spending score is approximately is 17 whose family size is 9 and their average annual income is low as compared to other.

Profession and Spending Score

Figure 7: Profession and spending scoreFig. 7 shows Profession based spending score and average annual income. So, for the other profession average annual income is high but the spending score low. Artist average annual income is low as compared to other profession but the spending score is high as compared to other profession.

Employees Spending Dashboard

Figure 8: Employee Spending ScoreThis Dashboard show employees spending score and annual income also over all representation of data based on different attributes. From this dashboard we see many factors like family size and annual income. Experience based annual income.

Profession wise employees in which profession employee are more. Professionals spending score in which professionals employees spending score is high.

Family size and annual income

Figure 9: Family size and Annual IncomeIn fig.9 bar graph shows profession and average family size based on profession and trend line showing average annual income for each profession. As we can see average annual income for most of the profession are approximately same. So, average family size for each profession is 3 or 4.

Gender Age and Annual income

Figure 10: Gender Age and Annual IncomeIn this plot on x axis age is given; age lie between 0 to 100 and on y axis average annual income is given. Blue and pink circle is for gender. Blue circle represents male employee and pink circle represents female employee. So, from this plot a person or business man can easily understand gender and age wise annual income and which age group employees are working more and what is their annual income.

Experienced Annual income

Figure 11: Experienced Annual IncomeFig. 11 is showing experienced annual income. In this plot x axis number of years experience and y-axis represent annual income. From this plot we easily see fresher or zero year of work experience employees are more and 10 to 50 years of work experience employees income is high.

Persons in each Profession

Figure 12: Persons in Each ProfessionFig. 12 is pie chart which shows number of male and female in each profession. From this we can easily see Artist have more employees as compared to other professionals spending score.

Professionals Spending Score

Figure 13: Professionals spending scoreFig. 13 shows box plot which represents professionals spending score and statistical five number summary for spending score. Spending score high for Artist and healthcare.

Walk-through

By looking at the graphs in the above implementation, I have got the results based on Gender and profession composition in the customer data and then comparing them to average annual income and spending score. And then I have taken work experience and average annual income comparing them with type of profession present in the customer data.

Firstly, I have created the pie chart for gender and profession distribution in the data. then I created a horizontal bar chart for each profession separate for male and female and trend of income is plotted for these professions. Line chart is plotted to see the work-experience and average income distribution for the professions .

Reflective Discussion

I plotted the average annual income by gender, work experience and profession. The spending score is low for other profession. Customer with profession lawyer and Entertainment has low work experience with annual earnings above 110K. Additionally, these two professions have spending score is between 45 to 55. Profession distribution in male and female is similar as seen in the pie chart.

References

https://help.tableau.com/current/pro/desktop/en-us/buildexamples_line.htmhttps://help.tableau.com/current/pro/desktop/en-us/buildexamples_pie.htm