Customer Profile Analysis

This project's goal is to increase a company's revenue by identifying the Ideal Customer Profile (ICP) also known as the most valuable customer for the company.

To this purpose, each client presented in the database was given a score from 1 to 100, with 100 being the most valuable client and 1 the least valuable.

Packages used:

• pandas
• plotly.express
• plotly.io

Importing the Database

First we need to import the database, visualize and process the data using the pandas package. In this scenario the .csv file contains special characters and is separated by semicolon instead of comma so the keyword arguments "enconding" and "sep" are not default. Also, the dataframe contains a column with empty values, so we need to drop it.

Customer_Profile_Analysis/Customer_Profile_Analysis.py

Lines 3 to 7 in c4ff758

	#Passo 1: Importar a base de dados
	tabela = pd.read_csv("clientes.csv", encoding="latin1", sep=";")
	#Passo 2: Visualizar a base de dados
	tabela = tabela.drop("Unnamed: 8", axis=1)

Data Processing

Using the DataFrame.info() method we can observe two major problems:

1. The column "Salário Anual (R$)" is a Dtype object and not a Dtype int64;
2. There're 35 entries where "Profissão" information is null, so these are not very useful data.

Customer_Profile_Analysis/Customer_Profile_Analysis.py

Lines 12 to 15 in c4ff758

	#Passo 3: Tratamento de dados
	tabela["Salário Anual (R$)"] = pd.to_numeric(tabela["Salário Anual (R$)"], errors="coerce")
	tabela = tabela.dropna()
	print(tabela.info())

Data Analysis

By using the DataFrame.describe() method we can see that the average score achieved is around 52, so this will be our main benchmark.

Using .histogram() method from plotly.express package we can perform a graphic analysis, comparing the Score with the other parameters such as Age (Idade) or Yearly Income (Salário Anual).

Conclusion

Analysing the Age X Score, Profession X Score, Work Experience X Score and Family Size X Score graphics we can conclude that the ICP is above 15 years old, works in the Entertainment Industry or is an Artist, has between 10 to 15 years of work experience, and has a family size no larger than 7.

Note: this is a project developed for academic purposes, therefore the data contained in "Clientes.csv" is fictitious and used only to learn Pandas and Plotly packages applications.