IBM has unveiled predictive intelligence software designed specifically to analyse data from wikis, RSS feeds, blogs and social networking sources like Twitter.
The company claimed that SPSS Modeler can merge this information into a data repository for more accuracy and insight, allowing customers to gain a wider understanding of customer relationship strategies.
The software can mine data and text for behavioural attitudes, and use predictive intelligence to assess future customer buying trends, the firm said.
IBM explained that the system can capture trends using industry-specific terminology from verticals like life sciences, banking, insurance and consumer electronics. The software includes 180 taxonomies with more than 400,000 terms and 100,000 synonyms.
The predictive analytics uses natural language processing to allow organisations to harvest data for better customer insights, according to IBM, and is precise enough to reach specific customers, constituents, employees or students at a specific time and through a specific channel.
The consequence is better customer relationship management with more predictable and profitable results, the firm said.
"We are excited about delivering this new predictive analytics capability to our clients," said Deepak Advani, vice president of predictive analytics at IBM.
"Smart businesses need to analyse social media sources to garner a true understanding of consumer sentiment and translate customer knowledge into action."
SPSS Modeler is available now.
Could be used for everything from search-and-rescue robots to wearable tech
Don't require the rare material being mined from the mountains of South America
IBM hopes that its new tool will avoid bias in artificial intelligence
Found by calculating the strength of the material deep inside the crust of neutron stars