Employee turnover is bad for business. While that may be obvious, IBM has data that shows why. And it's offering companies the opportunity to seek similar insights through a deal with Twitter.
In October, IBM partnered with Twitter to make Twitter's social data available to IBM's data analysis. After more than 100 exploratory engagements with clients, IBM and Twitter on Tuesday plan to make three cloud-data services available to help businesses turn Twitter conversations into business intelligence that they can use in the decision-making process.
These include: IBM Insights for Twitter Service on Bluemix, a way to create apps that utilize social data; Watson Analytics with Twitter Built In, a service that combines and automates data curation, predictive analysis, and visual storytelling; and BigInsights Enterprise Hadoop as a Service, a way to bring Twitter data to enterprise Hadoop deployments.
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Intelligence agencies have been mining social media for years, as have private sector companies. IBM contends its approach – which involves combining Twitter data with other streams of public and business data, such as weather forecasts, sales figures, and inventory statistics – allows businesses to spend less time preparing data and more time creating information that can be acted upon.
By mixing Twitter data with Watson Analytics, IBM says it helped a global food service chain understand how employee turnover was turning off its most loyal customers. IBM's analytics models showed that customers built up relationships with the food chain's sales associates and expressed that affinity in tweets. Customers also remarked on the absence of those employees and expressed frustration using the same social media channel. Sales declined as a consequence and those venting their dissatisfaction were among the company's most loyal and valuable customers.
IBM is suggesting that if you look, you can see the impact of tweets on your bottom line.
Other insights that emerged from IBM's analysis of client-related Twitter data include ways to anticipate and mitigate telecom customer churn and to assess demand for apparel products.
IBM introduced a beta version of Watson Analytics in September 2014 as a tool to make data analysis more accessible. The firm has been adding language processing, image recognition, and reasoning capabilities through acquisitions like AlchemyAPI earlier this month.
Dave Schubmehl, research director at IDC, said in a phone interview that, while other companies have been analyzing social media sentiment for years, IBM's involvement should expand awareness of Twitter data among enterprise IT groups. "A lot of enterprise organizations that IBM is involved with haven't looked at the wide range of use cases for Twitter data," he said. "What I think is really happening here is IBM is helping to validate social media data in general, and Twitter data specifically, as something that should be a part of the enterprise."
Schubmehl said the value of IBM's approach is in combining Twitter data with other types of complex data – like weather data, for example – so that the result isn't just sentiment analysis.
Schubmehl sees the IBM-Twitter partnership as a good sign for Twitter and other sources of social media data. "Data itself is coming of age as a product, and companies like Twitter and Facebook that sell that kind of data will do very well."
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