Service provider’s understanding of their customer churn : executive’s assumptions compared to results from customer data analysis
1University of Oulu, Oulu Business School, Department of Management and International Business, International Business
|Online Access:||PDF Full Text (PDF, )|
|Persistent link:|| http://urn.fi/URN:NBN:fi:oulu-201811283126
|Publish Date:|| 2018-11-28
|Thesis type:||Master's thesis
Customer churn is one of the key metrics defining company’s growth. While companies are increasing their investments into customer retention, churn remains remarkably high in most industries in B2B sector. This raises a question if service providers have thorough enough understanding of what causes their customers to churn, and how to effectively manage customer churn. This thesis explored executives assumptions on their customer churn, and we were able to provide suggestions on how to improve company’s resource allocation to increase customer retention. Quantitative analysis based on customer data, and qualitative analysis based on executive interviews were conducted to evaluate the executive’s understanding of their customer churn and their ability to improve customer retention. Those two analyses were then compared to each other to make conclusions on the matter. Research was conducted as a case study involving one service provider, with more than 4000 of their customer companies being included in the analysis. Customer churn has been studied widely, and predictive analytics has been found to be effective in detecting future churners. In addition, other studies are suggesting that executive’s might have wrong assumptions of what causes their customers to churn, and their capability of assessing the issue has been questioned. It is crucial for service providers to retain their customers, and even a 10% increase in customer retention can cause 30% increase in company valuation. Hence, misconceptions of what causes customer churn should not be tolerated, and companies should understand their customer churn thoroughly. By possessing the results from executive interviews and from customer data analysis, we were able to draw a conclusion whether the assumptions possessed by the executives were aligned with what the data was telling. While the executive’s assumptions were somewhat accurate and aligned with the data analysis results, there was still room for improvement in understanding what causes customers to churn and how to detect the future churners. Based on the results, it is reasonable to expect that service providers could improve their customer retention by deepening their understanding of their customer churn.
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