As of November, Watson Analytics will become available to anyone, allowing organisations to access the computer’s powerful predictive and visual analytics tools to improve their understanding of their customer data, behaviour and CRM.
Offered up as a freemium service for desktop and mobile devices, Watson will help businesses answer questions such as what the key drivers are for product sales and what deals are most likely to close. It can even go to work on in-house data to help answer employment questions such as which benefits drive employee retention the most.
IBM claims Watson Analytics is designed to automate data preparation and predictive analysis, making it a potentially attraction opportunity for marketers as opposed to being exclusively for data scientists.
“Watson Analytics is designed to help all business people – from sales reps on the road to company CEOs – see patterns, pursue ideas and improve all types of decisions,” says Bob Picciano, senior vice president, Information and Analytics Group, IBM.
"We have eliminated the barrier between the answers they seek, the analytics they want and the data in the form they need. The combination of Watson-fueled analytics to magnify human cognition, the vast potential of big data, and cloud-scale delivery to PCs, smart phones and other devices is transformational.”
IBM has declared Watson’s latest release into the outside world as its “biggest announcement in a decade”, promising an analytics tool as powerful as that being used by “a small fraction of business people” on the globe.
The data analytics market is in need of a shot in the arm according to recent data from Gartner, with confusion remaining in many businesses about how best to garner insight from big data.
One key difference appears to be Watson’s ability to interpret a businesses’ requirement to avoid the time-consuming process of finding and validating data, automating much of the process and delivering reports in a story-style format that will allow employees outside of the data science field to interpret. With data analytics, it’s more and more about trying to understand the questions as well as the answers.
Chris is Editor of MyCustomer. He is a practiced editor, having worked as a copywriter for creative agency, Stranger Collective from 2009 to 2011 and subsequently as a journalist covering technology, marketing and customer service from 2011-2014 as editor of Business Cloud News. He joined MyCustomer in 2014.