UberVu tries to go beyond social media monitoring by providing actual suggestions of things for social media managers to do. Today its Signals service, which we covered previously, is out of beta. The service also comes with a completely redesigned interface.
Every analytics company claims to offer “actionable intelligence,” so what does that mean in UberVu’s case? For small companies that don’t get many mentions, it might not be a big deal to stay on top of social media interactions. For large companies, it could be a real problem to sift through thousands of messages to find out which ones actually need a response. The Signals service processes streams of stuff like @ mentions on Twitter and references to specific keywords, and processes it all into something more digestible.
UberVu Founder and Chief Product Officer Vladimir Oane used GM as a sample company, though GM isn’t actually a customer.
The demo monitors for social media mentions relating to GM brands and competitors, as well as messages meant specifically for the GM Twitter account. It then uses machine-learning algorithms to sift through and find messages that a GM employee should actually respond to. For example, tweets with complaints from influential Twitter users, or questions about GM cars. It can also find things like articles that could be flagged for the PR department to review, or independent content that could be shared from official GM social media accounts.
The real question is how good its algorithms really are at prioritizing important tweets and content. That’s hard to gauge from a demo. But I can clearly see the value of this service for big brands if it works as advertised.
Update: Here’s an official screenshots from UberVu (I grabbed the one above during the demo):