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Currently the world is composed of data that every day is being produced by businesses as well as individuals. According to a tally, in 2020 each Internet user created 1,7 MB of information every second, Google processed more than 40 000 queries, about 3 million emails were sent by people around the world. And those rates continue to rise rapidly.

This amount of data processing requires advanced analytic solutions, specifically big data analytics.

What is this?

Big Data Analytics (BDA) – is the complex of advanced analytic methods that are focused on the work with big and different size data (from terabytes to zettabytes) to uncover valuable information from structured, semi-structured and unstructured data sets from different sources. By using this tool, it is possible to uncover hidden patterns, unexplored correlations, market trends and customer preferences. BDA comes with technologies and methods like predictive analytics, statistic analysis, text analysis, data visualization, machine learning, artificial neural networks, spatial analysis, Data Mining, pattern recognition, simulation etc.

World data amount stupefies but opens huge capacities for business. For instance, in working with customers and their behavior. By collecting and analyzing data for each client it becomes possible to provide an individualized offer upon request. As a result, a company becomes more competitive, customer experience becomes higher and revenue is growing.

Some examples how BDA can help to improve customer experience:

• Personalization: with BDA’s ability to uncover hidden data companies are able to know their customers better, also can help to simplify and transform «Customer – Company»
• Customer loyalty: big data analytics provides qualitative and quantitative vision of the business situation. So, company’s management has a possibility to identify essential trends that could be transformed into more qualitative product, service and operating activity. It allows to make customer loyalty stronger.
• Customer behavior tracking: this tool helps to identify what is behind customers’ behaviors. Thereby companies have a possibility to make more qualitative connection with customers and improve customer experience.
• Data collection: at this time every purchase, voice command or search may be recorded. In the digital marketing era companies have an opportunity to create profile for everyone with thousands of data points.
• Customer retention: data has a huge potential and plays an important role in the planning considering interests of particular users. It helps to retain returning customers and attract new one.
• Predictive analysis: this analysis type is useful for definition of current and future customers’ interests. Also, predictive analysis helps business to specify future events that gives a possibility to prep for them in advance, prevent risks and impact on results.
• Support: in consequence of big data analytics it becomes possible to determine what platform customers prefer to get support.