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  • Friday, August, 2019| Today's Market | Current Time: 12:36:13
  • The ability of machines to truly comprehend human emotion is the final frontier in artificial intelligence. It’s also a powerful conceptual tool marketers can use to develop solid, impactful campaigns powered by the relationship a consumer has with a brand. By the year 2020, customer experience is expected to overtake both price and product as the key differentiator for brands.

    Businesses have a vested interest in being able to parse more historically qualitative metrics like emotional responsiveness and brand trust into actionable data points within their marketing strategy. This post takes a closer look at how technologists are using computer algorithms to recognize emotive behavior, and what that means for the consumer-brand relationship.

    Artificial intelligence

    Artificial intelligence (AI) refers to a software application or system programmed to emulate cognitive tasks performed by humans. This encompasses tasks as simple as determining variable outcomes for one single dataset, to massive systems created to analyze vast amounts of information deemed too complex and time-consuming for the human mind.

    Machine learning (ML) is a sub-field of AI relating to the development of computer systems that are able to “learn” by continuously analyzing statistical insights through repetition of a specific task, without additional programming. This has proved extremely valuable not only in analyzing vast data sets but also in being able to make accurate predictions.

    Deep Learning (DL), has emerged in recent years as a broader approach to traditional ML methodology. It aims to cross the threshold into human emotion by designing model systems that closely mimic the structure of the brain as it relates to thought, through the layers of neurons in the neocortex. In this way, computer scientists hope to unlock the next level of cybernetics by teaching machines to recognize patterns in images, sound, and video.

    The emotion economy

    So how does it all work, and why is it suddenly so profitable? Well, for one, emotions lie at the heart of the human experience: a conclusion that brands are starting to understand has an immediate influence on their bottom line.

    How we feel impacts the way we communicate with others and can drive our decision making. Technology is beginning to evolve to reflect the need to integrate these insights into a brand’s reporting capabilities.

    What’s currently possible

    Humans possess tens of thousands of facial muscles and nonverbal cues that help convey the distinct range of emotions we experience on a daily basis. Even though one could argue that a computer couldn’t possibly possess emotional intelligence without being able to actually feel, the reality is that the multitude of probabilities in human expression adds up to a complex data set that machine learning algorithms were, by their very nature, designed to process.

     

    Enter “affective computing”, an emerging offshoot of the artificial intelligence modalities listed above. It aims to close the gap between human emotions and computational programming via algorithms trained to recognize cues and facial landmarks, even in the pixels of a digital image. This allows a program to effectively classify a spectrum of emotions and learn from repetitively analyzing those against new data. Affectiva, a company born out of the Media Lab at MIT, specializes in affective computing technology that’s been used in a broad range of applications. It can help young stroke victims relearn motor skills and adapt gameplay within a horror-based video game to account for emotional distress.

     

    We’re also seeing elements of emotional analysis in the devices that we use on an everyday basis. Apple’s FaceID feature on the newest iPhone X projects and analyzes over 30 thousand 3D data points to create a depth map of your specific face. The strength of its recognition software means that you can change your hair, wear heavy makeup, grow a beard, and even sit in complete darkness and the device will still be able to analyze and recognize your features. Additionally, their Animoji feature has been hailed as revolutionary, and not just because you can send clips of yourself as a singing cartoon pig. Experts argue that Animoji is a proof-of-concept for smartphones being able to sense and respond to facial cues triggered by emotional responses.

     

    Last year, Voxpopme paired with Affectiva to integrate the company’s Emotion AI into more effective video research software. Being able to pull enhanced emotional data from video snippets is crucial to marketers looking to attach KPIs to their content marketing campaigns, build engagement, and ultimately develop a user experience that’s based on real feedback.

    Predictions for the future

    As inroads are made into more sophisticated software development, the potential for video analytics to further impact a variety of sectors will increase. According to a recent study from Market Research Future, the global “emotion analytics market” is expected to be worth around $23 billion by 2023. Technologists point to a combined increase in spending on deep learning software and supplementary technology in the years to come.

    The issue of privacy also isn’t likely to fade away anytime soon. The plugged-in consumer has access to more content than ever before, but their personal data is also less private, as we’ve seen in recent headlines. However, brands are in a unique position to achieve positive impact by establishing mutually beneficial exchanges. In fact, nearly 80 percent of consumers surveyed recently stated that they would be willing to share relevant information about themselves in exchange for “contextualized interactions in which they’re immediately known and understood”. Emotional analysis leads to better marketing content, which leads to profitability.

     

    In today’s world, progress is driven by insights that blend emotional intelligence with logistical reasoning. In this way, machines are a marketer’s greatest ally in the race to achieve market share in the emotion economy.

    Author of this article Brian Thomas is a contributor to Enlightened Digital, long-distance cyclist, and lifelong advocate for women in business from Philadelphia. Tech and business are his lifeblood, but he’s also a fanatic of brewpubs and just about every sports team in Philadelphia.

     

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