How Big Data can Stop Customer Churn?


Big Data helps businesses on the cutting point of client experience find out why some customers leave and how to make customer service better to retain seemingly disengaged customers. All the client information is gathered so the representative can see, using a visualization tool, that this is truly a good customer who’s just having a bad day.


Big Data Embrace Big Promise for Refining Customer Experience


Customer service representative doesn’t have a red light, the green light dashboard to view quite yet, but for companies on the bleeding edge of big data analytics, the scenario described above is happening today-says Eric de Roos. He also writes that -“Big Data gives you a more in-depth understanding of what people are doing and how they are engaging with the organization. Ten to 15 years ago companies were just storing transactional data”.


That data, merged with the transactional information, gives companies a good picture of an individual customer’s value, Eric de Roos says.


By adding sentiment analysis from the IBM Infosphere Streams, Twitter API and the Micro-Strategy Wisdomengine, which tracked the 15 million “likes” of some 65,000 Facebook users and their links, can provide a  clearer picture of what that customer thinks of you and, and your competition.



Customers blogging, Tweeting and liking things on Facebook simultaneously collect an “influence score” and engage with your brand, says Wilson Raj, global customer intelligence director for SAS. These “digital traces,” in turn, can be connected to get a full view of that customer.



Since customer experience and knowledge is an important aspect for IT companies. Twitter feeds with YouTube headers is combined with Sentiment analysis from Web-generated data sets and the blogosphere. This data is enfolded in a natural language processing (NLP) engine in order to deem a customer’s feelings. As these skills mature, corporate IT departments find the time, talent and assets, to catch up with this trend.



Rita Sallam, Gartner’s BI analyst, and research vice president wrote -“Advanced analytics must be more persistent to deliver significant value and competitive advantage to an organization,”.



Moving to techniques like AI into the hands of line-of-business users may not be as hard as you would imagine, says IBM’s Director of Emerging Technologies David Barnes.


T-Mobile Using Big Data to Understand and Predict Network


Using Big data on the back-end to make sure your offerings are what you say they are. T-Mobile. The main focus of network engineering is optimum network performance in the name of customer knowledge, she says. “We use clickstream data to compute the speed of downloaded songs. This gives us a great deputation for understanding throughput speeds at the tower level, as well as handset speeds.”



With this data at the set, T-Mobile has been able to expect—and avoid—network outages that could have been initiated by faulty Android applications, Twiford says.


Big Data Will Make Big Strides


Big data doesn’t come easily. Companies employed to mix the many silos of internal data with intellect from the Web and gush analysis from NLP trains, then, are riding the curl of this wave. Such firms are in the minority



“Big data provides social data and other publicly available data that can be analyzed and used to recognize the customers’ sentiment and needs before they become issues or problems that lead to churn,” Kolsky says. “This is a significant advancement for organizations that, until now, had to rely on customers’ openness and candor to understand the issues.”


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