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IBM IOD 2011: Business analytics to replace market research

IBM IOD 2011: Business analytics to replace market research

Using social media analytics via Twitter and Facebook, companies can see what consumers want and use the data for business gains

IBM general manager of business analytics, Rob Ashe.

IBM general manager of business analytics, Rob Ashe.

Business analytics will render the traditional format of market research almost obsolete in the future as companies use the technology to track market sentiment.

IBM general manager of business analytics, Rob Ashe, said social media analytics is changing in the way research is conducted as the rise of social media has participants discussing openly what they like and dislike, what their plans are, and so on.

“There is an explosion of data on social networks about what consumers are consuming, what they’re going to consume, what their likes are, what their preferences are, and so it’s a new source of data that we all have to harness,” Ashe said.

Ashe said that as many sectors face a challenging financial time, the more information and analytics they can get about their customers and what they are doing, the more targeted they could become.

“Analytics is important in the area of customer behaviour for upsell, churn and retention, for employee sentiment as companies try to understand the mood of their employees, citizen sentiment to understand how are they responding to programs, and political campaigns which are largely driven by Facebook and people communicating with each other,” he said.

“This is a key area and a different kind of data, it’s not something we’re trying to put into data warehouses or apply governance to it’s going to change every minute and has very low latency, it’s real-time and very highly relevant and therefore can make a huge impact.”

According to the Professor for marketing and director of executive education at the University of Connecticut, Girish Punj, the nature of data is changing and the gradual move away from market research is due to the traditional use of surveys generated by large samples.

Punj said as the nature of data begins to change and market research gives way to business analytics, the university is making moves to follow that and develop courses to teach business analytics skills.

“One of the reasons students are so interested in sentiment data is because they believe that this is their data, it is data they have generated so because of that their involvement is higher,” he said.

The faster moving the industry, the more valuable this kind of data is, said Nihad Aytaman, director of business applications for high fashion label, Elie Tahari.

Aytaman said for the business of high fashion, which requires about 450 new styles to be designed and produced each season (of which there are four per year), it is imperative to know what the market trends are and what the consumer is moving towards.

“A consumer insight type of product which goes out and looks at the tweets and looks at Facebook and pulls in what people talk about is very important because that is our consumer, we can react to what they’re talking about in real-time and produce a line that is more acceptable and obviously generates more revenue,” Aytaman said.

Aytaman also presented the other side of the spectrum, when someone writes something negative about the brand or the product, the technology enables the company to capture that as soon as possible and remedy the situation.

“Another aspect we didn’t have until now is the ability to see what people are saying about our competition and that was not previously available to us, so there is certain information to be gained out of that and we could potentially look at that information and find opportunities,” he said.

“This levels the playing field, all of a sudden the secrecy disappears because if it’s a public blog or tweet that people talk about it’s out in the open and it’s fair game so we can monitor that.”

One area that is tricky when it comes to social media analytics, Ashe said, is sarcasm and how the technology can understand and interpret that correctly.

According to Ashe, a lot of work is being done on ensuring the technology gets smarter as time goes on, similar to the way IBM’s supercomputer Watson learns, and will continually learn by exception.

“We can actually go back and tell the system when we see something is negative and so it will learn over time what is positive or negative, what is a pun, and what is sarcasm,” Ashe said.

Chloe Herrick travelled to LAs Vegas as a guest of IBM.

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