LucyImo/MTN-SERVICE-ANALYSIS

This is a data analysis of MTN services and sales, also tracking the churn status of customers who patronize MTN as a service provider. MTN is one of the network providers in Nigeria. The data is record of customers from the period of January to March of a particular year. # MTN-SERVICE-ANALYSIS ## TABLE OF CONTENTS - Data_Overview - Content - Data_Sources - Observations_During_Data_Cleaning_and_Preparation - Findings - Recommendations - References ### DATA OVERVIEW This is a data analysis of MTN services and sales tracking customer churn status, and an investigation was carried out to note the general problem, which is the reason for churn, and ways to mitigate this problem. MTN is one of the network providers in Nigeria. The data was a record of customers from the period of January to March of a particular year, with a total of 974 customers. This Analysis was done with the Python language. The Following Insights were analyzed; These are: -Count trend * How many customers does MTN have from January to March * What is the customers' distribution based on the month * What is the highest-selling device? * What is the customers' distribution based on Gender * What is the count of Customers based on Location? * What is the percentage of customers' Status -Period Trend - * 1. What month did MTN have a decline in most - * 2. Number of Customer registrations based on location - * 3. What location has the highest revenue -Rating Trend - * 1. How is the customer's Rating based on the state? - * 2. Does the rating have a significant effect on the reason for churn based on location? - * 3. What is the total reason for churn based on location? ### CONTENTS - The dataset comprises the following: 974 rows and 17 columns. In the 17 columns, we have the following headers; * a. Customer ID: * b. Full Name: This column contains the full name of customers who were registered with MTN. * c. Date of Purchase: This is the date registration was made for the customer using the MTN device. * d. Age: This is the Age of a particular customer. * e. State: This is the state of registration. * f. MTN Device: This is an MTN product that was sold to a customer at a particular period. * g. Gender: This is the column that distinguishes the male and female cus …