The Future of Data Analytics Lies in AI Assisted Customer Analytics

by Jay Marwaha

We’ve come a long way since the days of horse-drawn carriages, haven’t we? Not only do we have fast, powerful cars at our disposal, we can also see glimpses of a time in the not-so-distant future when everyone will be riding in self-driving automobiles.

You can say the same for data analytics. Computers and digital data have done much to revolutionize the processing of information, but artificial intelligence is expected to change the rules of the game in the decades to come.

The cutting-edge data analytics tools of today don’t just process static data. Instead, they analyze data in-motion, based on a dynamic model that evolves with each new addition of data, in order to coordinate an immediate and appropriate response. This type of program – what we call AI Assisted Customer Analytics is already being used by businesses in a wide range of industries. Think about websites like Amazon, and how they tailor results and recommendations to a customer’s online behavior.

This kind of behavioral analytics is also an important weapon in the arsenal of several government entities seeking to improve intelligence production capabilities and strengthen their cybersecurity. It provides the analytics capability to identify suspicious users based on their immediate behavior on the network, and consequently shut them out instantly.

Just like self-driving cars, AI Assisted Customer Analytics offers traditional data analytics functions with the addition of cutting-edge technologies. The program can make recommendations based on the data accumulated over time, in areas such as internal management, customer-facing applications, and effective information sharing. That means you get the bets of both worlds: traditional data processing and an AI program working for you around the clock.

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Tags:  Analytics

Jay Marwaha

Founder and CEO of Syntasa (an AI assisted customer intelligence platform). He has over 20 years of professional experience in the field of analytics, data science, performance measurement & management, and strategic planning.