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Introduction

Customer churn is an age-old problem for most industries, especially for ones with high competition, low prices or margins, and volume-based business models. Telecommunications, retail, and certain segments of the financial services industry, and increasingly software-as-a-service businesses, are prime examples of such markets where players invest significant resources in tracking, measuring, and understanding customer churn, so that they can manage it better.

Highlights

  • This case study sheds light on how one large provider successfully navigated this process through the use of search-driven analytics, and offers important "lessons learned" that can be applied in other industries.

Features and Benefits

  • Assess and understand the business challenge of identifying the root cause of customer churn and addressing it through analytics.
  • Explore the business benefits and lessons learnt in the deployment of analytics to tackle customer churn.

Key questions answered

  • What are the key drivers to adopting analytics to address customer churn in the telecommunications industry?
  • What are the best practices that other enterprises can adopt when facing similar business challenges?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations for telecommunications industry analytics practitioners and leaders

  • Have a plan to assess the ROI of your analytics solution
  • Look for solutions that help avoid silos, not create them

Using analytics to find probable causes for churn

  • Setting the business context
  • Understanding the existing architecture

ROI assessment

  • Figure 2 shows how the ROI accelerates as ThoughtSpot is used over a five-year period.
  • ThoughtSpot deployment started paying for itself in less than a year
  • ThoughtSpot will start generating profits from the end of year one onwards
  • Expanding the number of users had a multiplier effect on ROI
  • Intangible benefits include trust in data and management efficiency

Lessons learned

  • Build consensus from the beginning
  • Do not be afraid to go best of breed if required

Appendix

  • Methodology
  • Further reading
  • Author

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