If you wanted to change my mind about something or my behavior, what kind of research would help you do that most effectively? Behavioral science findings show that many traditional approaches don’t really work.
What’s a better way?
We unearthed deep but narrow veins of behavioral science studies related to how individuals make sense of their world, and which hidden forces guide their behavior. We integrated these separate threads to weave a new kind of tapestry that ultimately revealed a much more usable portrait of individuals.
We all know the flaws in stated preference research or many forms of self-report research. Whether filtered through a self-aggrandizing ego, or fear of being out-of-step with the group, individual reports can be far from accurate.
How about demographics? Aren’t there predictive truths in what binds individuals, from geographical roots, to age or education levels? Perhaps there are shared aspects among these broad swaths, but it is also possible a teenage girl from Cameroon could share important predictive sensemaking aspects with a 70-year-old man in Cambridge. Or that two women of the same age, educational attainment and income, having grown up in the same small town, have completely different hidden filters that shape their worldviews.
Then what about actual behavior: How an individual shopped, traveled, what they watched, how they voted or what they clicked on? Isn’t that a better set of clues? Yes, that is actual rather than projected, but it may also be true only in the past or within certain contexts. It misses the “Real Why” of an individual’s motivation and behavior.
Attitude counts
While behavioral economics has revealed the downside of otherwise important human sensemaking shortcuts that we all need, by highlighting cognitive biases and decision-making heuristics, it does so at a human species level and also in very independent way. Yes, we all tend to discount the future (“temporal discounting”) compared to the here and now (“present bias”), but some may do so more than others.
All humans may tend to value avoiding a loss more than reaping a gain (“prospect theory”), but some are wired to be more sensitive to one than others. You may have been schooled and grew up in a community that looks the same (lookalike demos). But some identify with a worldview where individuals must be accountable for their own outcomes and will rise above others, while others believe the community must take care to close all gaps of all forms of inequality. So while two seemingly identical individuals may struggle with weight management, one may have a very different skew within one personality factor that makes it far more difficult to stick with a diet.
We started to ask how these different factors influence each other; how they fit together and which of a sea of cognitive biases and heuristics would be most useful to measure from a market research perspective. To explore this we undertook a multi-year evaluation of more than 14,000 behavioral science studies into areas such as:
Personality trait science
Cultural cognition
Regulatory focus
Locus of control
Need for affect/cognition
Zimbardo time perspective
Self-efficacy
Rational vs Experiential
What we did not know was whether interweaving all these behavioral science threads would create a high-definition portrait or a Gordian knot.
But even if we could integrate many separate behavioral science aspects of individual makeup, to do so, we needed to improve on methodologies of testing for these traits in the first place.
Testing tests
Nearly all traditional behavioral science findings depend on self-report surveys, generally based on a Likert scale of “strongly disagree” to “strongly agree.” We know a respondent clicking through reams of questions may develop a bored Likert laziness, but they are also only likely to select choices that make them feel comfortable about themselves.
For example, if someone asks you how conscientious you are, unless you are both very self-aware and honest, it is unlikely you will confess you are more like the Dude in the Big Lebowski than Hermione Granger in Harry Potter.
In our paper (presented at the 2019 ESOMAR Congress) we outline a range of some of the solutions we uncovered for example, if you are given an quick, implicit photo test of what your socks drawer looks like right now, how you park your car, whether you recycle, how often you floss your teeth — you will likely click on those choices that reflect something closer to the real you. In behavioral science terms, the more you answer in quick, intuitive, implicit, “System 1” mindset instead of a slow, deliberate “System 2” mindset, the more likely you will tell us the truth.
We tried to think about all these behavioral and personality characteristics more as overlapping lenses, not separate, unrelated factors. Rather than looking at the night sky and seeing separate stars, you have the concept of constellations, and ever after, each bright dot becomes a pixel in a portrait revealing the “hidden who.”
We experimented on cross-measuring all these different aspects alongside one another. These experiments showed that the different personality aspects are often closely interwoven like constellations of stars threaded together with gossamer strings. For example, a person who considers the future and has a strong sense of internal self-control is also likely to be more conscientious, so the answers from each test could be used to cross-validate each other, providing greater data stability overall.
This also led to efficiencies. By measuring multiple facets together, we could whittle down each test to its core unique elements, removing overlapping questions and using the answers from one test to inform the answers to another to shorten the overall length of the survey considerably.
That said, we still had quite a long survey that could be a tough ask for people to concentrate on answering throughout. So we designed the survey around a modular format, breaking up the component parts into three-minute-long, “thinking chunks”. We began each with a “thought starter” question to introduce the topic of the next section and grab the respondent’s attention.
At the end of each section, we gave the respondents feedback about what we had learned about them along the way, and asked them to validate the accuracy of our assessment. If they thought it was wrong, they were given the option to correct it. This approach measurably improved respondents’ motivations to focus on their answers.
How to deploy our new approach?
In the health arena, by better decoding individuals, we can craft more effective message framing, content, creative and interventions, whether it be to manage obesity, combat “vaccine hesitancy,” aid smoking cessation, or overcome substance addiction.
When communicating environmental impact, we can reframe the storyline so that it will better resonate rather than clash with a person’s worldview.
When crafting reward and recognition programs for employees, we can find out what people really value (as opposed to what conventional wisdom or the employees themselves state explicitly).
Just imagine if we could move marketing research away from its tradition of warlike posturing (“target,” “acquire,”) to an empathetic approach that resonates with the “hidden who” of individuals or improve the effectiveness of communications, content and interventions through a new kind of personalization. To do that, we must use a new genome of sensemaking.
This paper won the 2019 ESOMAR Congress Top Paper award and the full paper is available at https://ana.esomar.org , ESOMAR’s intelligent reference tool for ESOMAR’s resources library.
