The Three Legs of The Rational Heart’s Emotional Measurement Stool
The Rational Heart has developed a method of emotional response measurement that is unique in the market research arena. We have built a tool, protected by trade secret status, that is used to gauge emotional response to almost any stimulus object or event. We believe it is important that those who use this tool have a basic understanding of the philosophies and components upon which it is based. This post covers each of the three legs of our analytics stool, as well as a summary of the combined components that deliver the resulting emotional measurements.
Leg 1: Plutchik’s Psycho-evolutionary Theory
The first key element of our tool is the structural platform upon which the emotional model is built. This model is drawn from Robert Plutchik’s Psycho-evolutionary Theory of Emotions, developed in the 1970’s and published widely in 1980. For readers who are unfamiliar with Plutchik’s work, a good summary of the components – including the ten postulates which comprise the theory – can be found on Wikipedia here, or for more detail in this book.
Here, we will review how practitioners at The Rational Heart use the theory, how we update it to reflect current vocabularies and language evolution, and why we think it can and should serve as the structural cornerstone of the phenomenon of emotional response.
Plutchik’s theory is based on Darwinian principles of evolution. It posits that emotions evolved in humans (and in all animals) because they help us to survive as a species. Psycho-evolutionary Theory describes how something as complex as emotion can be broken down into core responses, reactions, and actions, which allows us to understand all emotional responses in humans today.
However, as with all theories that have the staying power of over 40 years, our use of Plutchik’s model has required that we make minor updates to make its use fully relevant today. As such, we have updated Plutchik’s theory to reflect changes in our environments and to adjust for minor emotional word choices that have turned out to be less than ideal as language has evolved. At this point, we have the tools to detect those dated aspects and have implemented changes to improve predictability. Despite the need for minor modernization, the principles of Plutchik’s work, published with Henry Kellerman in 1980, rightfully drew widespread acclaim and were translated into more than 60 languages internationally. They still provide valuable guidance in measuring emotional response.
Perhaps the most iconic imagery to emerge from Plutchik’s work was the multicolored wheel that he used to describe how emotions are not simply independent “feelings,” but are interrelated in fundamental ways. The version of the wheel shown below is revised, largely to accommodate language changes that have occurred since the original version was completed.
In this model, Plutchik proposes eight basic emotions that are at the core of all emotional response. Start with Joy (in the yellow spoke at the top of the wheel) and continue around that concentric circle which includes Joy, Trust, Fear, Surprise, Sadness, Disgust, Anger, and Anticipation. Those are the basic eight. Also included in each spoke are higher-intensity and lower-intensity versions of those basic eight. So, lower-intensity Joy is Peaceful, and higher-intensity Joy is Ecstasy. Thus, there are 24 emotions depicted in the eight spokes of the wheel, the 8 basic emotions in their various levels of intensity.
Importantly, each spoke is directly across from an opposite emotional spoke. We see that Joy is the opposite of Sadness, and Trust is the opposite of Disgust, for instance. And they feel opposite. Joy and Trust both feel positive, while Sadness and Disgust both feel negative. “But what about Fear and Anger?” you might ask. They both are uncomfortable emotional responses. The idea here is they drive opposite response actions. It reflects the well-known Fight or Flight relationship when we sense the presence of a threat.
One of the more remarkable propositions to come out of Psycho-evolutionary Theory was the assertion that Complex Emotions are not separate emotions in and of themselves. They are instead the result of combining Basic Emotions. So, for instance, if the stimulus you are considering is a person, or perhaps a car, and you feel both Joy and Trust for that person or that car, you will come to “Love” them. Love appears at the intersection of Joy and Trust on the wheel.
We can build emotions that result from combining all sorts of emotions. There are many, many emotions that are formed when you feel two (or more!) emotions at once. And you can even combine Complex emotions to form Higher-Order emotions. What is important in the combining of emotions is the way we think about these combinations. When you think about combining emotions, you want to envision “combining paint, not marbles.” If you have 100 red marbles, and 100 yellow marbles, and you dump them into a bucket, you will get a bucket full of red and yellow marbles. But if you take a can of red paint and a can of yellow paint, and stir the contents together in a bucket, you will get a bucket of orange paint. And that orange is fundamentally different from either the red or yellow paints with which you started. It is the same with emotions. If you combine Joy and Trust, you get Love, which is fundamentally different from the original emotions. That new emotion feels different, as well.
Finally, we would also point out that, similar to Basic emotions, each of the Complex emotions mentioned here also have high-intensity and low-intensity emotions associated with them. So, low-intensity Love is Like. And high-intensity Love is Worship. And again, this persists across all the Complex emotions. At The Rational Heart, we have identified over 140 different Basic and Complex emotions that are incorporated into the Plutchik wheel.
The principles of Psycho-evolutionary Theory, developed and espoused by Robert Plutchik and his colleagues, have done much to build an understanding of how emotional response to environmental stimuli evolved in humans (and other animals). But unfortunately, much of the initial support for his work dissipated, in large part because he did not have the tools that we now have to demonstrate that his ideas were supported by scientific evidence through measurement. With the advent of Behavioral Economics from Kahneman and Tversky (and others), and the advancements from more readily available Bayesian statistical processing from Jordan Louviere (and others), we now do have those tools which we will examine as Leg-2 and Leg-3 of the Stool from The Rational Heart to see how these components help to complete our comprehensive emotional measurement capability.
Leg 2: Behavioral Economics Methods
The goal of this segment (Leg-2) of our post is to highlight how and why we use the principles of Behavioral Economics to help capture emotional response to any stimulus object or event under investigation. Here, we will describe how we use normal survey techniques – but applied in a specialized manner -- to gauge the degree to which people are feeling over 140 specific emotions in response to a stimulus object, or event.
As we begin this discussion, it is important to recognize that the emotional responses we measure at The Rational Heart are memory-based. Most simply, this is captured when one considers, “When I think about X, I feel A, B, and C.” This is distinct from other research techniques that may measure emotional responses that are in-the-moment. These immediate responses are captured as one is exposed to the stimulus, such as when one watches a movie or observes an advertisement, or takes in a sporting event. While we believe both approaches are valid and important, we concentrate on emotional memory, as this is key to consumer decision-making and what is referenced when consumers are faced with purchase decisions.
In 2011, Daniel Kahneman published his seminal work in Thinking, Fast and Slow, which described many of the principles of Behavioral Economics, and presented game-changing information on how our brains work. Importantly, this included a review of System1 and System2, the two modes of human thought.
System1 is fast, reactive, emotion-based and instinctive
System2 is slower, deliberate, logic-based and reflective
We will not go into the details of System1 and System2 thinking here, but readers who have not thoroughly consumed Kahneman’s book are advised to take the time to absorb his Nobel Prize winning insights. Instead, we will focus only on the attributes of System1 thinking, which is where emotional response resides. Kahneman and his colleague, Amos Tversky, figured out that to tap into System1 thought processes (where they were studying economics-based thought biases), one can do so by forcing people to process their thoughts rapidly. Only the System1 brain can effectively make decisions very rapidly; System2 thought processes are too slow and deliberate. They found that respondents who were participating in their experiments had to use System1 thinking in order to make any decisions at all when forced to do so very quickly.
At The Rational Heart, we use this simple, yet incredible finding to fuel our System1 measurement technique. We present possible emotions to respondents in pairs, and ask them to choose the one (of the two) they most closely associate with the stimulus object or event under investigation. This task is only manageable by System1 thinking as they are forced to make this decision very quickly.
Leg 3: Bayesian Statistical Methods
The goal of this segment (Leg-3) is to describe how we employ Bayesian statistical methods to score emotional response so that we can analyze the resulting data.
In the preceding content of this post, we explained the need to tap into the System1 brain to get authentic emotional responses. This, in turn, requires that we make the task for respondents as simple as possible. We show survey respondents two emotions at a time and ask them to specify which of the two emotions they “most closely associate” with the stimulus object or event being evaluated.
Now, we need a method for scaling that felt emotional response.
We use a software system for conducting MaxDiff experiments and analysis with specialized accommodations for timed parings. We use these methods (Bayesian techniques) to assess the degree to which survey respondents are feeling each of the 24 basic emotions from Robert Plutchik’s wheel of emotions (see above) that are defined by Psycho-evolutionary Theory.
The output from the MaxDiff software is centered around a data matrix of Utilities. For each survey respondent, we compute a Utility for each of the 24 basic emotions, reflecting the strength with which respondents feel those emotions. And this resulting set of utilities is the cornerstone of our emotional response measurement.
At this point, we know which basic emotions survey respondents feel when they consider the stimulus object or event being evaluated. And using these results, we can now model the complex emotions that they are feeling, as well. Complex emotions are those that result from combining two or more emotions at a time. In the Plutchik wheel shown above, we see examples of complex emotions that appear between the spokes of the wheel. So, Love is the result of combining Joy + Trust. And Optimism is the result of combining Joy + Anticipation (if you are Anticipating Joy in your future, you are Optimistic, right?).
The number of possible combinations that can produce unique emotions is substantial, as it is also possible to combine several emotions to produce a unique outcome emotion. For example, one of the most compelling instances is the emotion of Hope. At The Rational Heart, we have recognized that Hope is a ratio. As shown in the figure below, Hope is the ratio of Optimism and Confidence relative to Pessimism and Doubt.
If your Optimism and Confidence are high/large (the left side of the figure), and your Pessimism and Doubt are low/small (again, the left side of the figure), you are Hopeful. In categories like healthcare, Hope is a very important emotion. Patients often begin treatments prescribed by their physicians feeling an abundance of Hope. But if over time those treatments do not show improvement in their symptoms, these patients experience diminishing Hope. If we can measure that felt Hope, we can know when interventions might be needed. This can help patients stay fully committed to their experimental programs in a drug test, for instance.
At this point, one can see the importance of Leg-3 of the TRH stool. Bayesian statistics allow us to score felt emotions using the Utilities that result from the MaxDiff software programs. This means we can measure basic emotional response to different stimuli, and we can model complex emotional response to those stimuli, as well. Armed with this information, we can finally include emotional response in our battery of tools used to evaluate brands, products, messages, and more.
At The Rational Heart, we understand that emotions are at the core of successful business strategies. Consumers make decisions influenced by both logic and emotion. By quantifying emotional responses through our proprietary behavioral economics approach, we provide your business with a strategic advantage. Trust in The Rational Heart to turn emotional insights into impactful business strategies. Contact us today to discover how we can help your business thrive!