Everyone responds differently to video. Some smile or frown. Some roll their eyes. Others open their mouths in awe and amazement. For decades, agencies and marketers have tried to capture these reactions before finalizing TV shows and advertising. Unfortunately, these tactics turned out to be deeply flawed.
Dial testing, for example, has probably been the most popular method used to pre-test content. Respondents watch a video while turning a dial (or pressing buttons on a keyboard) to signal how they feel about the content from one moment to the next. The age-old problem, unfortunately, is that there can be a wide gap between how people say they feel and what they are actually feeling.
Fortunately, we now believe it’s possible to credibly measure, predict and even influence a consumer’s emotional reaction to content.
I can see it in your eyes (and your smile and your head tilt…)
Prestigious institutions like MIT and Oxford have begun developing automated systems that apply facial coding to testing marketing stimuli. This approach is based on the idea that everyone shares a number of basic emotions that are conveyed through the same facial expressions: lifting the corners of your mouth when you’re happy, furrowing your brow when confused, opening your eyes wider when amazed, and so on.
Some of this academic work is now utilized by companies that help brands and agencies test marketing communications, and hi-def cameras built into almost all modern laptops, desktops and smartphones provide an easy way to accurately capture a user’s emotional reactions in real time.
Utilizing CAT across MediaCom
This type of Content Assessment Tool (CAT) is now utilized across multiple specialist functions within MediaCom. The MediaCom Beyond Advertising team uses it for concept testing and editing video content. We also use it to determine how best to adjust global content for specific local markets. CAT can also help inform budget decisions, given that the results can indicate what level of engagement a client can expect from a specific piece of content.
Beyond these tactical use cases, MediaCom’s Business Science econometricians are integrating data from CAT tests into their modelling work. They have already identified some clear correlations between key CAT metrics and brand KPIs, such as awareness and sales uplifts.
We will also be able to measure the impact of altering content to reduce viewership drop-off, and could explore how emotional engagement combines with sequential messaging for even greater impact.
The future for CAT is promising, and the potential integration of wearable devices is particularly intriguing. With more people using smartwatches and fitness trackers, it’s plausible that a marketer might be able to read an individual’s biometric data to instantly determine a consumer’s emotional state (with consumer permission, of course).
At that point, we would have not only captured the ideal emotional state in which a target consumer “should” view content but, in theory, could then deliver that content to individuals currently in the desired emotional state.
Imagine a piece of branded content “magically” arriving at the exact moment an individual’s vital signs indicate s/he needs to be informed, engaged or entertained. What would that be worth? Perhaps in the not-so-distant feature, we’ll find out.