By Nathan Gnanasambandam
Customer service is a top priority as well as a tough business challenge for every business. Data analytics is a key tool that can be used to not only provide better customer service, but also deepen customer relationships. For example:
The Customer Experience: Predictive analytics can play a major role in the customer experience by decreasing – and in many cases, eliminating — customer issues before they even occur.
Imagine a customer getting a call from a company with a fix for a product recall before he even experienced an issue. By synthesizing data from a number of sources, predictive analytics can be proactive and help brand managers see what is around the corner. The result: Address a problem before a customer is even aware of the problem.
Healthcare: Xerox has been applying predictive analytics in the healthcare industry to predict possible reasons for future doctor or hospital visits. This information can lead to early diagnosis and treatment, and potentially save lives.
Early pilots show that we can use predictive analytics to foresee issues or questions patients will most likely have, and proactively provide the information in a personalized fashion before the patient even has the issue.
Predictive analytics in #healthcare can lead to early diagnosis and treatment, and potentially save lives. http://ctt.ec/LWtHC+ #HealthIT
Help Desks: We see promising results using predictive analytics in customer care centers. Customer care agents can provide better service because an evidence-backed recommender system helps the agent make proactive suggestions during a customer service call.
Predictive analytics can help any company transform mountains of data into valuable insights that deepen customer relationships. I don’t need analytics to predict that when a customer is happy, your business will succeed.
Nathan Gnanasambandam, Ph.D, is a senior research scientist in the Big Data Analytics lab at PARC, A Xerox Company. His expertise includes experience in quantitative modeling including behavioral and contextual profiling, risk modeling, text and graph mining, and big data analytics. His current interests are in social and healthcare analytics.
From the editor: This article was excerpted from the NGData blog article, “26 Data Analysis Experts Reveal the #1 Business Problem that Can Be Solved with Predictive Analytics.”