Telecom-Excel-project

Table of content

• Project Overview
• Data Sources
• Data Cleaning/Preparation
• Data analysis
• Recommendations

Project Overview

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This project analyzes the customer base for a telecommuunication company and provides insights into the factors that contribute and are likely to contribute customer attrition. It also analyzes the revenue generated by the company in diifferent cities. By analyzing various aspects of the customer base data, I seek to identify trends, make data-driven recommendations and gain a deeper understanding of the company's performance.

Data Sources

Telecom_customer_churn Data: The primary dataset for this analysis is the "telecom_customer_churn_1 (2).xlsx file containing detailed information about each customer interaction with the company

Tools

• Excel Download here

Data Cleaning/Preparation

In the initial data preparation phase, i performed the following tasks:

1. Data loading and inspection.
2. Data cleaning and formatting.

Data analysis

I analyzed the customer base dataset to answer key questions, such as

• What is the revenue performance of the company in various cities?
• What factors lead or are likely to lead to customer attrition?
• What is the revenue generated from the different customer segments

Results and findings

• Factors which lead to or are likely to lead to customer attrition:

1. Competitor Offers: Across all customer categories, this is the most significant reason for customer churn. It suggests that customers switched or are most likely to switch to a competitor due to more attractive offers.

2. Customer Service: The attitude of the support person is a common churn driver for both churned and retained customers, indicating that poor customer service or support experiences contributed or can contribute to churn. Improvements in customer service may positively impact customer retention.

3. Data and Download Speeds: Customers also cited the availability of more data as a reason for switching to a competitor. Higher download speeds offered by competitors were also a factor in customer churn,

• Total revenue by City:

1. Los Angeles contributes the highest percentage of total revenue among the listed cities, followed by San Diego.
2. Fresno, Sacramento, San Francisco, and San Jose each contribute to a smaller portion of the total revenue.

• Total revenue by Customer Segment: Old Customers:

1. This segment represents existing or retained customers.
2. Contributes the highest percentage of total revenue among the three segments. 3.Indicates the revenue generated from customers who have stayed loyal to the company.

New Customers:

1. This segment represents revenue generated from new customers.
2. Contributes the lowest percentage of total revenue. 3.Indicates the success of customer acquisition efforts and the potential for future revenue growth.

Churned:

1. This segment represents revenue generated from customers who have churned.
2. Contributes to a moderate percentage of total revenue among the three segments.
3. Requires attention to reduce churn rates and retain customers for long-term revenue sustainability.

Recommendations:

Based on the anaysis, I recommend the following actions:

• The company may need to revisit its pricing strategy, improve the quality of its services, and focus on providing excellent customer support to reduce churn in order to retain both existing customers and attract new ones

• It's crucial for the company to stay competitive in the market by offering compelling packages and addressing customer concerns to retain high-value customers.

• The company should consider promotions or improvements in data and download speed offerings, especially for new customer acquisition.

Contribution

If you would like to contribute to this project, please fork the repository and submit a pull request. Contributions are always welcome!

Credits

This project was created by Tari Joel

Contact If you have any questions or comments about this project, please contact me at tarijoel20@gmail.com.