IBM’s Watson Analytics: How it makes sales and marketing’s job easier

James has more than a decade of experience as a tech journalist, writer and editor, and served as Editor in Chief of TechForge Media between 2017 and 2021. James was named as one of the top 20 UK technology influencers by Tyto, and has also been cited by Onalytica, Feedspot and Zsah as an influential cloud computing writer.

Yesterday IBM unveiled Watson Analytics, a freemium data science tool for businesses of all sizes utilising the power of Watson’s supercomputer technology.

As we reported, for a company which isn’t averse to bigging itself up, Watson Analytics appears to be a release of which Big Blue is particularly proud, with IBM exec Oliver Oursin calling it a ‘breakthrough’.

The main talking point is that Watson uses natural language to spit out its analysis, meaning everyone in the business can get results. Whether you’re in sales, marketing, or the CEO, and whether your knowledge of code, mathematics and algorithms is spotty at best, Watson Analytics aims to make your job easier.

Ask Watson a question such as ‘Which sales are likely to close?’, or a statement such as ‘Show me revenue by time period’, and it will come back with similar results in plain language, not a bunch of code.

Gene Villeneuve, European predictive & business intelligence sales and brand leader at IBM, explained to CloudTech the various types of algorithms used in Watson, from analytical techniques such as correlations, trending, forecasting, and scoring of the data, to SPSS algorithms, a data mining software application built by IBM.

“By embedding capabilities around advanced algorithms, we are giving guided analytics directly in the box for end users,” says Villeneuve. “That’s the intent: not only is it really easy to get started, but once you’re in there and having this very immersive dialogue with the data, Watson Analytics will guide you to see other things you wouldn’t have been able to see with other capabilities on the market today.”

Oliver Oursin, global predictive and business intelligence solutions, explained how the type of question asked in the front end will influence what Watson digs through in the back end.

“When you ask the question, the real language question to us, what we’re doing is trying to go after key concepts in that question,” he says. “If I say ‘can you compare the quarters and the revenue?’, you get a bar chart, or something similar. If I say ‘can you give me the trend of the revenue over the quarters?’, then I would have to bring a line chart.

“That’s a very simple example, how the analytics of the question drives the results,” he adds.

“As we go into the mathematical end of it, obviously we have a lot of algorithms in there that are used in parallel, and they’re used where they make most sense,” Oursin continues. “As we do analytics, we don’t just think of revenue. I want to understand it by geography, I want to understand it by sales, product, channel.

“We also do multi-variant analytics in the back end, which means we specifically search for combinations that drive revenue to bring you real insight.”

Watson can’t tell you whether the data is right or wrong, Oursin adds – it’s not psychic, after all – but it can tell you whether your data is good enough to help you make key business decisions.

Another key aim of Watson Analytics is to take the hassle out of data science – cutting out the middle man. When asked how it will benefit sales and marketing professionals, Oursin replies: “I would think this makes it easier in many ways.

“The first thing is, it’s very easy to touch. Using Watson Analytics, you have no pre-knowledge that’s required, you just need to understand your business, and you have to have your data. That’s the only thing you need to bring to the table.

“The fact that it’s cloud makes it very accessible,” he adds. “You don’t have to think about us sending you software, us giving you an install guide…you just connect to it and off you [go].”

Above all, IBM sees a trend developing in terms of key stakeholders and decision makers in modern business. Gone are the days when the CEO or CIO would be solely responsible for making a decision. In some companies, the marketing manager will have lots of power; in others, not. Bringing new technology into the business used to sit with IT and IT only. It all makes for a more democratic line of business approach.

“10, 15 years ago, it was really IT driving a lot of these systems, and the power sat with IT in most of those decisions,” Oursin says. “But that has changed. Today the budget, the power, the decision making sits in the business, which means they want to make a decision, and they want to act on it right away.

“And that will make it much easier for us,” he adds.

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