While I don’t use all the marketing tools at my disposal, I am certainly curious about them. After all, such tools provide marketers with powerful insights on their prospects and customers.
I became especially curious about one marketing tool when re-examining a phrase I use often.
- I use the phrase “biometric content marketing expert” in a non-traditional way. When I use it, I am attempting to say that I am a content marketing expert on the use of biometrics for identification. In other words, I can create multiple types of content that discusses fingerprint identification, facial recognition, and similar technologies.
- But if you speak to a normal person, they will assume that a “biometric content marketing expert” is someone who uses biometrics (the broader term, not the narrower term) to support content marketing. This is something very different—something that is generally known as “facial coding,” a technique that purports to provide information to marketers.
What is facial coding?
Earlier this year, Reshu Rathi of Entropik wrote a blog post about facial coding. Rathi provided this definition.
We all know that our face conveys emotions through facial expressions; facial coding is the process of measuring those human emotions. With the help of computer vision, powered by AI and machine learning, emotions can be detected via webcam or mobile cam. The tech tracks every muscle movement on the face or all-action units (AU) based on the FACS (facial action coding system).
From https://www.entropik.io/blogs/facial-coding-what-why-and-how-to-use-facial-coding-in-marketing
The differences between facial coding and facial recognition
Unlike the topics in which I usually dwell, facial coding:
- Does not identify individuals. Many people can share the same emotions, so detection of a particular emotion does not serve as individualization.
- Does not provide permanent information. In the course of watching a movie or even a short advertisement, viewers often exhibit a wide range of emotions. Just because you exhibit a particular emotion at the beginning of an ad doesn’t mean you’ll exhibit the same emotion at the conclusion.
As Rathi describes the practice, it preserves privacy by allowing people to opt-in, and to record the emotions anonymously.
So, the user’s permission is required to access their camera and all this data is captured with consent. And no video is shared. Only the emotion data of the users are captured through their facial expressions and shared in real-time. The emotions on a person’s face are captured as binary units (0 and 1). Hence no PII (Personally Identifiable Information) related to race, ethnicity, gender, or age is captured at any point in time.
From https://www.entropik.io/blogs/facial-coding-what-why-and-how-to-use-facial-coding-in-marketing
Of course, some of this is a matter of implementation, or in the way that Entropik uses the facial coding technique.
- But what if another firm chooses to gather more data, thus reducing the anonymity of the data collected? “I don’t only want to know how people react to the content. I want to know how black women in their 30s react to the content.”
- And what if another firm (or a government agency, such as the Transportation Security Administration) chooses to gather the data without explicit consent, or with consent buried deep in the terms of service? In that case, people may not even realize that their facial expressions are being watched.
Examining facial expressions is not the only way to decipher what is happening in a person’s mind as they view content. But it’s powerful.
Well, maybe.
Does everyone exhibit the same facial coding?
The underlying assumption behind emotion recognition is that you can identify emotions at a universal level. If content makes me happy, or if it makes a person halfway around the world happy, we will exhibit the same measurable facial characteristics.
Lisa Feldman Barrett disagrees.
Research has not revealed a consistent, physical fingerprint for even a single emotion. When scientists attach electrodes to a person’s face and measure muscle movement during an emotion, they find tremendous variety, not uniformity. They find the same variety with the body and brain. You can experience anger with or without a spike in blood pressure. You can experience fear with or without a change in the amygdala, the brain region tagged as the home of fear.
When scientists set aside the classical view and just look at the data, a radically different explanation for emotion comes to light. We find that emotions are not universal but vary from culture to culture. They are not triggered; you create them. They emerge as a combination of the physical properties of your body, a flexible brain that wires itself to whatever environment it develops in, and your culture and upbringing.
From https://www.theguardian.com/lifeandstyle/2017/mar/26/why-our-emotions-are-cultural-not-hardwired-at-birth
If Barrett is correct, then how reliable is facial coding, even within a particular region? After all, even Southern California does not have a single universal culture, but is made up of many cultures in which people react in many different ways. And if we preserve privacy by NOT collecting this cultural information, then we may not fully understand the codings that the cameras record.
Back to the familiar “biometric” world
And with that, I will retreat from the broader definition of biometrics to the narrower and more familiar one, as described here.
The term “Biometrics” has also been used to refer to the field of technology devoted to the identification of individuals using biological traits, such as those based on retinal or iris scanning, fingerprints, or face recognition. Neither the journal “Biometrics” nor the International Biometric Society is engaged in research, marketing, or reporting related to this technology.
From https://www.biometricsociety.org/about/what-is-biometry
My self-description as a biometric content marketing expert applies to this narrower definition only.
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