We’ve all complained about it – the explosion of social media activity has become its own self-feeding juggernaut. But, beyond the noise of it all, behind the tweets and the selfies, the likes and the 140-character revelations, we’re starting to see that there are patterns emerging. There are trends in all of this data that can be meaningful to help understand market behavior, reveal what customers want and ultimately drive better business decisions.
Our latest Business Tech Trends study showed that big data and analytics adoption is on the rise with 39 percent of companies surveyed being in advanced stages of deployment and adoption. Pacesetters are using it to enhance collaboration, speed innovation and improve customer experience. These leading companies are also far more steeped in analyzing social data in particular – in fact, they’re six times more likely than their peers to be using social media analytics. Perhaps this isn’t a huge revelation given that big data has become such a big draw.
But what’s surprising is that while many companies understand the abstract value of digging into data to analyze behaviors, trends, patterns and correlations, many companies are still struggling with how to make sense of it all – especially social data. We may have thrown ourselves into the data game, but we’re not sure how to play to win. Our recent study, Charting the Social Universe, found that while many companies have implemented social capabilities to better understand customers, only 24 percent of them actually use social analytics when making marketing decisions. They’re still relying on gut to drive decisions that could be more accurately executed based on strategic insights.
So how do we simplify the entry into social analytics? The recent IBMandTwitter announcement highlighted ways that companies can tap into this public real-time data to extract valuable insights. Beyond social listening, there are many real-world use cases that seamlessly integrate social and existing business data, whether it’s in financial services, telecom or commerce.
For instance, in the apparel industry, manufacturers were able to better understand why some products sell well while others don’t by analyzing Twitter data that influential fashion bloggers generated. In another example, by combining Twitter data with information about other factors like rain, wind or snow that trigger service interruptions, a telecom was able to identify a correlation between weather events, angry Tweets and customer churn.
The mantra of analytics at the core is appealing. It’s a resounding theme, and one we heard echoed at this year’s SXSW event during a panel about “IBM and Twitter on the Future of Digital Engagement.” It’s still about putting customers first. It’s still about deepening relationships with employees, customers, partners and all communities. The shift is from playing the guessing game to making data insights that businesses can act on.
Want more fuel for the data revolution? Read about Generation D (for data) and check out our data and analytics blog posts.
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