Businesses are still cautious about investing in social media analytics, despite the hype around social media and the role it plays and will increasingly play in enterprise.
Laurie Miles, head of analytics at business analytics software company SAS, told Computerworld UK: "It has started, but people are toe in the water at the moment.
"But there are early adopters, and they're getting interesting results back. They're using it for [measuring] sentiment, but also to add to what they know already. I can see only more of that growing."
Customers are investing, however, in solutions that can help them make forecasts about where their business is going, based on the data they have collated.
"Major organisations have collected all the data, put it together and are producing the reports, but are not necessarily analysing the data to get genuine insight into where their business is going and what will happen next.
"They want to leverage the investment [in collecting the data] they have made. Clearly, knowing what your customers are going to do next, what is going to sell, are all great ways to use that data to affect their profitability," said Miles.
He explained: "For example, retailers want to forecast for stock replenishment and price optimisation, so that they charge the best price, rather than just taking off 10 or 20 percent."
The use of predictive analytics is not a trend limited to the private sector - the public sector has also been investing in it, Miles said. SAS currently supplies services to a range of government departments, including the NHS, the Department for Work and Pensions (DWP) and the Ministry of Defence (MoD).
"For example, we enable the NHS to better decide where to make their investment in drugs, and help them manage the patient data. We help the DWP to run simulations to determine the impact of decisions they make, such as a pension age change, and we also help the MoD in optimising the transit of goods and materials," he said.
In addition, SAS has also noticed that companies are trying to turn their analytic capability into a business process. So instead of manually building an analytics model, which would then take several months for IT to tweak and implement it into a business process, the IT implementation part of the process is automated.
However, companies looking to exploit their data for business insights are facing a number of challenges. One of these is getting hold of the right data, at the right time. This is made particularly difficult as sometimes, the data has been optimised for storage, rather than analysis.
There is also a lack of skills in the area. "There's a challenge in finding data analysts. There is a great demand for them," said Miles.