How Telecom Companies Use Big Data Analytics

Assignment Task

Background

A US-based Telecom Company, XYZ Telecommunications, has seen phenomenal growth in the past decade of operation. The prospects look good for the firm, and everything seems to be working in favour of the company. However, due to growing competition in the market with slightly better offerings, the churn rate has increased and might hurt the company’s brand value and finances in the long run. The firm’s CEO is worried about the latest updates. He is looking at the bigger picture and is aware of the cascading effect that increasing churn rate can create. He has asked the Analytics and Marketing departments to work together and come up with proper actionable insights and product/marketing campaign changes.

Problem Statement

You are the Head of the Analytics Department working together with Marketing Teams. You have access to the attached dataset, which you got from your team. Your task is to analyse the given dataset and identify the patterns in the data to check if there’s anything serious that CEO should be worried about. After a thorough analysis, suggest recommendations/actionable insights to the CEO regarding what steps can be taken to improve the company’s short and long-term prospects.

Task

1. Analyse the given dataset. Highlight all crucial metrics across different dimensions. Include anything that you feel will be important to resolve the issue.

2. Deliver key insights into customers' profiles, the satisfaction of customers, offerings & payments, problems, etc. Some questions that perhaps can help you (do not limit to these):

• What user personas/profiles are important to us and how can we target them efficiently?
• What are the problems our customers are facing and how can we address them?
• What are the best overall offerings by the company such as online backup, premium tech support, Streaming TV, etc. and is there any relationship between the offerings choices and churn rate?
• Is there any relationship between what kind of plan a person is using and the possibility of staying with the company?
• Can we predict who is going to stay and who is not? What level of accuracy can we achieve on this?

3. Summarize your findings, backed by data-driven insights, to the CEO highlighting all the key metrics that cover the issues reported and put forward your insights to these findings. Also, suggest recommendations (max. 3 top recommendations) that the firm can adopt to resolve these issues/concerns and come up with a strategy to go ahead in the long run.

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