The rules of engagement have modernized. There is no question that – for a while now – we’ve been living in the era of the ‘distracted viewer’. If anything, the re-invention of TV over the last decade should have spawned a more appreciative and engaged consumer. Firstly, content on the small screen has re-emerged as innovative, surprising, ‘wonder what comes next’, claiming, it feels, some of the old cinema aura. Secondly, more money than ever before is now spent on commissioning and acquiring content for the general TV; Netflix, Amazon and HBO announced they are spending, as a total, more than $12 billion dollars on content this year
Instead, the abundance of shows to choose from combined with the plethora of devices demanding our attention have turned us consumers into the toughest of judges on a talent show at any given time. And I will explain why; whether we are streaming or still enjoying the traditional TV, viewing is rarely a single action. Online browsing, social networking, instant messaging or just good old phone ringing come in the way of a viewing experience. Unless we make a conscious decision to remain uncontactable during a viewing session, pop up alerts will be fighting for our attention throughout repeatedly asking us to make a choice as to whether the content we watch is worth interrupting; our engagement will be undoubtedly tested.
Engagement through emotion
So, what is it in a programme that keeps us engaged? For many decades, creatives globally (with the help of their insight teams) have been attempting to solve the engagement question, which more often than not is synonymous with international appeal and longevity of a show in the viewers’ hearts. Figuring out that emotions are some of the main drivers of engagement is almost straightforward. Deciding which are the lead emotions and how to track them is trickier.
In market research, emotions are captured in numerous and cross methodology ways: from using words/emojis/open questions in quantitative surveys to having ‘emotional’ qualitative group discussions and in depth one-to-one interviews to using dial testing, heart rate tracking and machine learning algorithms like facial expression capturing and voice recognition, all used to define the emotional connection between the viewers and a new programme. But, in all honestly, creatives have been taking the lead on this one, not necessarily with the fine-tooth comb of emotions, rather with gut feeling and their years of experience taking centre stage in this decision making. Sometimes the audience choices will contradict these decisions. The most striking example of a success that was failed to spot is ‘Mad Men’; it was rejected by both HBO and Showtime before AMC decided to take a punt with it. Same with C.S.I. which was consciously overlooked by ABC, NBC and Fox and it was only the CBS executives who decided to take a chance with it. 17 years after it first launched, it continues to be the bread and butter of many schedules around the world.
Measuring audience emotions
So, what’s so important about emotions that can predict a show’s appeal? The answer sits somewhere between neuroscience and psychology. Think about a movie scene that increased your heart beat, made you start biting your nails again, stand up or even scream. At that particular moment, you were biometrically experiencing what was happening in the movie world, fully empathising with the feelings of the character. If then or immediately after you were asked a pure and undiluted research question like: ‘what did you think?’, any emotions would be decoded in your answer. GfK Voice allows us to do exactly that, ie. capture audiences’ emotions and their sense of engagement by translating people’s voice response to quantifiable data.
Analyzing the ‘distracted viewer’
Once emotions subside, people start rationalizing what they’ve experienced. Referring to that movie scene again here, if it’s memorable and worth pondering, thoughts will start coming in. Emotions will give place to reasoning and our ‘distracted viewer’ will engage in chats, tweets, will write reviews, share comments on social media and even reply to surveys offering well-thought, moulded answers. The key to unlocking the essence from all this unstructured text is artificial intelligence (AI). The text mining process that analyses transcripts, unlocks themes, detects how formal, informal or emotive writing is, is what we call Advanced Text Analytics. This automated process of examining text delves deep into the context behind engagement recreating the consumer’s mind.
The combination of emotional decoding and artificial intelligence can shine the brightest light on the consumer’s mind and produce powerful diagnostic as well as predictive results. Engagement might be constantly tested with distractions all around us and machine learning technologies define exactly how much that is. However, in this world of distractions, the abundance of platforms consumers use to express themselves unveils the deepest insights that are often the hardest to get. And this is where AI benefits the most.