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dashboards and tabular data reports to supplement their recommendations and to help business
managers better understand what is happening in the business. Ultimately, business analysts use
business data to further the organization’s strategic goals and to support them in providing
guidance on any procedural improvements that need to be made.
In contrast, if you want to obtain answers to very specific questions on your data, and you can
obtain those answers only via advanced analysis and modeling of business data, bring in a
business-centric data scientist. Many times, a data scientist may support the work of a business
analyst. In such cases, the data scientist might be asked to analyze very specific data-related
problems and then report the results back to the business analyst to support him in making
recommendations. Business analysts can use the findings of business-centric data scientists to help
them determine how to best fulfill a requirement or build a business solution.
Exploring Data Science in Business: A Data-
Driven Business Success Story
Southeast Telecommunications Company was losing many of its customers to customer churn —
the customers were simply moving to other telecom service providers. Because it’s significantly
more expensive to acquire new customers than it is to retain existing customers, Southeast’s
management wanted to find a way to decrease the churn rates. So, Southeast Telecommunications
engaged Analytic Solutions, Inc. (ASI), a business-analysis company. ASI interviewed Southeast’s
employees, regional managers, supervisors, frontline employees, and help desk employees. After
consulting with personnel, they collected business data that was relevant to customer retention.
ASI began examining several years’ worth of Southeast’s customer data to develop a better
understanding of customer behavior and why some people left after years of loyalty while others
continued to stay on. The customer datasets contained records for the number of times a customer
had contacted Southeast’s help desk, the number of customer complaints, and the number of
minutes and megabytes of data each customer used per month. ASI also had demographic and
personal data (credit score, age, and region, for example) that was contextually relevant to the
evaluation.
By looking at this customer data, ASI discovered the following insights. Within the 1-year time
interval before switching service providers
Eighty-four percent of customers who left Southeast had placed two or more calls into its help
desk in the nine months before switching providers.
Sixty percent of customers who switched showed drastic usage drops in the six months before
switching.
Forty-four percent of customers who switched had made at least one complaint to Southeast in
the six months before switching. (The data showed significant overlap between these
customers and those who had called into the help desk.)