In 2005, 5% of adults in the U.S. were on social media; today it’s around 70%. Facebook has over 1.65 billion users engaging for more than 50 minutes per day. Social media is ubiquitous, and smart brands are sprinting to keep pace. But what about getting ahead of the curve?
What has evolved beyond Social Monitoring to Social Listening is now poised to enter a 3.0 phase in which crowd-sourcing and artificial intelligence will play pivotal roles.
A New Era: Social Listening
Social Listening starts with a required input: “What, where or whom should we listen to?” Creating that list, similar to how SEM and SEO marketers derive their keyword list, takes expert practitioners and smart tools. However, social is just more wild, more organic and more unpredictable than search.
It is simply not possible to anticipate everything you should be listening for.
Let’s take the example of what Mondelez, creator of Oreos, did during Super Bowl 2013. Oreo prepared for the event by organizing a team of creative writers, thinkers and executives to react to anything notable during the big game. When a power outage hit, Oreo tweeted, “You can still dunk in the dark.” The earned media that came out of that single tweet was phenomenal (and well summarized here).
As brilliant as Oreo’s execution was, it was not actually the result of Social Listening. This was a more proactive, real-time form of social marketing that will be able to scale with the Social Listening 3.0 that is yet to come.
Social Listening 3.0
The next generation of Social Listening is fast approaching and will operate more nimbly. This new type of Listening will be able to to identify opportunities that would never have been included in a brand’s “listen to this” input. Brands want to find topics that are not yet trending, but that they could own if they moved fast enough.
So how will this new generation of Social Listening work? Very likely, there will be two main drivers.
The Crowd Economy
First, the crowd economy that already exists will be invited to take on a new role. Oreo had its team at the ready for the Super Bowl; however, no brand can have always-on staff, listening to every conceivable tweet, share and post. But imagine if consumers are asked to Listen on a brand’s behalf.
Here’s a purely fictional example: Lululemon is likely listening for social conversations around keywords "exercise or gym fashion.” But there are other opportunities happening all the time. Let’s say there is an unfortunate wardrobe malfunction — such as a dancer ripping the seat of his pants during a dance routine on Dancing With The Stars.
Lululemon would probably love to be alerted to that in real-time through whatever platform is geared for rapid user alerts and tweet out a screenshot and caption such as: "This wouldn't happen in our pants."
This new Listening workforce will be recruited the same way consumers are recruited for advocacy programs, content creation programs and more. They will be trained and empowered and eventually will compete with each other at Social Listening.
The second driver is artificial intelligence (AI) as machines learn to understand which social content might represent brand opportunities. AI is already being applied to decipher not only images (such as when Facebook automatically tags the correct person based on facial recognition) but also the sentiment behind images.
AI will also be applied to Listening in a way that requires less of a prescriptive input of what to listen to. Opportunities such as the hypothetical Lululemon example will increasingly be able to be identified by AI-powered natural language understanding and image interpretation. Yet, don’t despair, fellow humans, while machines will get more skilled at identifying these moments, creative humans will remain better at responding. I’ve heard songs written by AI recently and none of them are on my playlist.
Overall, brands should stop monitoring and chasing trends but push themselves or their technology partners to better create the trending conversations that lead to greater engagement.