IBM is integrating data collected by Twitter’s real-time conversation platform with a new cloud-based data analytics service aimed for enterprise organizations.
The idea is to help business professionals “do more than social listening” to be able to use Twitter data to make better informed decision essential to their organization’s goals, according to IBM.
IBM intends to “isolate the signal from the noise” found in social media conversations by enhancing Twitter data with information from millions of data points from other streams such as sales information, product inventory statistics and ever weather forecasts. IBM will also use its analytics technology to make sense of the information.
IBM technology, like the super computer Watson, will access Twitter data and use the information as input for multi-variable, pattern dependent questions such: “What do customers like best about my products?”
“Twitter provides a powerful new lens through which to look at the world – as both a platform for hundreds of millions of consumers and business professionals and as a synthesizer of trends,” said Ginni Rometty, president of IBM. “This partnership, drawing on IBM’s leading cloud-based analytics platform, will help clients enrich business decision business decision with an entirely new class of data.”
— SimonPorter (@simonlporter) March 19, 2015
According to Big Blue there are now more than 100 early client engagements connected with the project.
Earlier this year, IBM also acquired Gnip, a leading provider of social data and long –standing partner of Twitter. Gnip provided IBM with an enterprise-grade platform that delivers more than 15 billion social activities per day.
Here’s how the new service is being used. For example, customers tweet about relationships they build with a business’s sales associates, but they also tweet about they also tweet about the sense of loss or dissatisfaction they feel when that sales associate leave the business.
IBM looked at Twitter data along with loyalty information and financial performance of different stores and restaurants. IBM found that not only did dissatisfaction with employee turnover impact sales negatively, the dissatisfaction was keenly felt by the most loyal (and most valuable) customers.
In one study, the impact was highest with a customer cluster that represented just 3.3 per cent of the total customer population (over six million in the loyalty program). But these customers accounted for the highest gross margins for the retailer every day, IBM said.