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Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers.

Big Data Analytics provide value:

  1. Cost reduction. Big data technologies bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.
  2. Faster, better decision making. Combining agility and ability to analyze new sources of data, businesses can analyze information immediately – and make decisions based on what they’ve learned.
  3. New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want.

Predictive analytics technology uses data, statistical algorithms and machine-learning techniques to identify the likelihood of future outcomes based on historical data. It’s all about providing a best assessment on what will happen in the future, so organizations can feel more confident that they’re making the best possible business decision. Some of the most common applications of predictive analytics include fraud detection, risk, operations and marketing.

Social media has opened new avenues and opportunities for organizations to connect with their customers, but sheer volume of communications about brands, products and services; discussed, shared, criticized or liked on different social platforms can be overwhelming.  Sentimental analytics helps to rapidly read all this data, providing an executive summary of what people like and don’t like about a company brand or products. The reasons behind the sentiment can then be easily extracted, providing valuable business insights.

Understanding a customer as a whole is important to stay ahead of competitors. There are several important aspects to consider when developing a 360-degree customer view. The past and immediate customer behavior is important to predict future customer trends and what their most likely next action will be. The customer’s transactions and travel habits are also important to build a lifestyle profile and discover new insights.