There is something marketing managers seem to forget about the internet: it was made for people, not for companies and brands. As such, it offers managers a source of insight they never had — social listening.
Eavesdropping on consumers’ social-media chatter allows marketers to economically and regularly peer inside people’s lives as they are being lived, without introducing biases through direct interaction. Armed with traces of revealed opinions and behaviors, managers can at long last discover the manifestations and ripple effects of their actions on consumer behavior. Clear indications from marketing science underline how chatter affects sales, brand health, and even stock performance. Social listening competency will be critical to competitive advantage in the digital age.
But despite its potential, companies underleverage the social media stream for market intelligence. Analysts look for data confirming a predetermined viewpoint, or view the social media conversation as something to be managed rather than listened to. They frame listening as a descriptive exercise rather than the high-potential strategic project it should become.
Some pay attention to social media data only when corporate crisis demands it. Although insights from social listening can and should drive corporate strategy and innovation, these are more likely trapped inside the marketing and service departments that “own” them. Social listening promises the Holy Grail in business: superior understanding of customers. Why, then, do managers fail to fully exploit it?
Econometricians, computer scientists, and information systems (IS) professionals often manage social listening efforts and their skills in database management and big data analytics are essential. But these hard scientists lack the social science skill set that allows managers to move from data to insight in the social listening world. At issue is the fundamental difference between information and meaning. True to their titles, IS professionals specialize in managing information. Their function is reductionist: bringing complex data down to the simple level of numbers — zeros and ones.