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Big Data - Are You Using It For Better Customer Service?
Sriram Padmanabhan
SVP-NIIT Technologies
Thursday, October 13, 2016
By 2020, more than six billion smartphones will be in operation worldwide, becoming more pervasive than traditional landlines. Moreover, the same source estimates that 80 percent of mobile data traffic will be from smartphones by 2020.

This drastic rise in smartphone penetration marks a monumental change in the way that the world communicates. With a continued increase in mobile throughout the world, businesses must consider how it will impact workflow, customer engagement and the bottom line. For those in the banking and financial services industry, it is even more imperative that executives consider the ramifications of this mobile movement.

Preparing for the impact of mobile on banking

According to a 2013 Pew Research study, 51 percent of U.S. adults bank online to some degree-and the younger a person is,

the more likely they are to bank online or on their smartphone. With this influx of mobile banking, the idea of the community bank with a home-grown bank president who participates in local events is diminishing. Instead, today's customers trust and rely on the real-time information of a mobile banking app as much as, if not more than,other forms of communication. This shift makes sense, as a push notification about a current balance is more timely and accurate than a letter that arrives a few days later when many other events could have occurred.

While the trend towards mobile banking is not new, the impact it has on businesses continues to evolve. As more customers move to mobile and online banking, companies can gather more information than ever before on their customers. With more detailed information, banks can and should provide differentiated and personalized service to customers even if they come into the brick-and-mortar facility less frequently.

Using big data and predicting customer needs

The first step to personalized service is an effective data management plan. Companies should analyze the entire data management process to identify places where it is ineffective, cumbersome or antiquated. From there, processes should be updated, streamlined and automated to the greatest possible extent. However, in their haste to realize greater efficiency, businesses must take care not to automate an ineffective system-this will only create more difficulties and inaccuracies in the long run.

Once these changes to the data management process are complete, companies should be able to gather in-depth insights about their customers based on specific actions, trends and demographics in one concise database. If clean data is available and combined with an effective analysis tool, companies can provide their customers with personalized services and better monitor how customers respond to specific campaigns, including:

Determining which customers are most likely to leave-There are markers of unhappy customers who are contemplating changing banks. If banks can review the actions previous customers took before leaving, they can use that information to monitor current customers and prevent continued churn.

Defining which marketing campaigns work with specific customers-By tracking attributes of customers and prospects along with reactions to previous marketing campaigns, companies can predict which customers will respond to a specific campaign. With this information, companies can target campaigns and offers, more effectively driving engagement than the traditional "spray and pray" method.

Providing more accurate prices for service rates- For many banks, data sets are reviewed and updated irregularly, curbing the ability to analyze how a price change impacts revenue in great detail. With predictive analytics and a consistently updated data set, companies can anticipate how their bottom line will be affected if prices increase or decrease. For example, the business will be able to predict how a 10 percent change in overdraft fees will impact customer action and the bottom line, empowering a more informed business decision.

Customizing options for each customer-Banks offer many services ranging from saving accounts to checking and loans. While most customers independently select from among these offerings, effective use of data could create a more personalized sales experience. For example, if data is effectively tracked, the bank will know which customers will be more likely to need a home loan with private mortgage insurance or which ones will want a new retirement fund, which can help a bank proactively offer these options to the customer, increasing the likelihood of the customers buying the service.

With the rapid growth of online and mobile banking, companies in the financial industry cannot afford to wait to modernize their systems-their bottom line depends upon it. However, once that transformation is complete, businesses cannot stop. Rather, they must use the data that customers provide to ensure they provide the best customer experience possible without crowding them or invading their privacy. Striking this balance- first analyzing the data analyzed and then putting marketing and engagement efforts into place-will be imperative for the success of the company.

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