One of these things is not like the other

Editor's note: Susan Fader is qualitative researcher at FaderFocus, a New York research firm. 

In order to field any type of research study, one has to interact with people – whether it is an in-person conversation or a self-administered questionnaire. Companies have spent inordinate amounts of money creating demographic and segmentation profiles of their customers, potential customers and “non-users.” They rely on these demographic specifications and segmentation profiles to determine who is or is not included in research. These categorizations are also used as guidelines for organizing databases and determining what potential research participant sample might be purchased. The people included in research are a major prism through which research data/findings are analyzed and business decisions are made.

It is human nature to try to group like things together and it is a major way that helps accelerate processing information, seeing patterns, making connections and discovering opportunities. We start as toddlers matching similar shapes and colors, so it’s not surprising that in this data-rich world, companies generally create a handful of what they think are distinct demographic profile groupings that capture the key demographics of the people they want to do research with. By filtering any research findings through these specific demographic groupings, there is the belief that it will both speed and improve our ability to analyze the data.

Currently, many of the grouping profiles follow the rules that were set in place years, even decades ago. Many rely primarily on traditional demographic parameters (gender, age, relationship status, HHI, education and category engagement) that usually revolve around purchase of a product or service. Some profiles overlay attitudinal questions, which in many cases fall into whether they will be an engaged research participant (e.g., “I like to share my opinion with others.”).

Maybe assumptions are off

So if research findings are based on feedback from these selected peoples’ perspective and opinions, shouldn’t we be reexamining the baseline assumptions that went into developing these groupings? Maybe the baseline assumptions used to develop them are off. If so, then the research is being designed and recruited with perhaps the wrong understanding of who the people are and how they make decisions.

We have to do a better job of incorporating how people self-define and view the world, versus the categories researchers may be fitting people into. Traditional demographic groupings are based on an outsider – the company, the researcher – making a judgement call on the characteristics that determine how people fall into groups and how similar they are being perceived. In addition, since companies field research to help their businesses operate better, it is not surprising that companies tend to create demographic groupings that align with how their business units are structured, which may not replicate how people perceive the world their products/services exist in.

I feel we need to reframe how we view people and am calling this approach cognitive demographics. It has multiple uses including in the recruiting process; as a guide to help us listen better to what people are saying in research; and as a tool for better development and positioning of products and services. Cognitive demographics incorporates traditional demographics, plus the need to do a better job of reflecting diversity, equality and inclusion in the overall participant population. Cognitive demographics then adds another component that provides a way to better understand a person’s value hierarchy – how they self-affiliate and make decisions. It also incorporates an emotional component of how people rationalize behavior and make decisions. 

Determining whether a person utilizes analytical or holistic thinking is one of the keys to better understanding how people make a decision. Analytical thinkers tend to be linear thinkers who like discrete, rule-governed categories. Holistic thinkers focus more on the big picture, specifically first looking at possible relationships. Analytical and holistic thinkers may sometimes arrive at the same conclusion but their rationalization for arriving at a common answer can be dramatically different. In a triad task, a person is shown three items and asked which two go together. If a pig, apple and dog were shown, the analytical thinker may group a pig and dog together because they are both animals. A holistic thinker would focus on the relationship and thus group the pig and dog together because the dog protects the pig from predators. If you just looked at their answer and didn’t delve into the fact one was an analytical viewer of the world and the other a holistic viewer of the world, you would have missed that how they view the world and process information is different, which ultimately can impact product/service interest, usage and purchase decisions.

Radically different 

With a traditional demographics approach, people may appear to be falling into the same demographic group but how they perceive themselves and the world and make decisions may be radically different. Yossi Klein Halevi, an American-born Israeli author who is very active in Arab-Jewish reconciliation efforts, and John Zogby, the political pollster, both emphasize that a key to better understanding people is to recognize that a person’s value system gives insights into how they make decisions. Halevi has spoken often about the fact that as humans we tend to share the same basket of values – family, community, work, religion, individual rights, the role of government etc. – but prioritize them differently and so we end up on different sides of an argument. Zogby, who conducted thousands of interviews for his 2016 book, “We are Many, We are One: Neo-Tribes and Tribal Analytics in 21st Century America,” feels that “self-identified tribal affinities – shared values, life philosophies and outlooks…transcend demographics and other category-specific attitudes and behaviors, which would be the basis of a traditional market segmentation study.”

In a research setting, recognizing how moms self-perceive their mom role can be crucial to understanding how they are making a purchase decision for a product for their children. Two moms may mirror each other when only using traditional metrics such as demographics, frequency of buying particular products and attitudes towards brands and thus be seen as being in the same segment, with the expectation that they would perceive the world similarly. Incorporating a cognitive demographic measure of how they view their role as a mother would show that these moms actually see the world very differently and therefore may be making purchase decisions using a different framework. One mom’s motto may be, “I will do anything for my kids,” putting her in the helicopter-parent category, while the other’s is, “Go with the flow,” which shows she is much more laid back when it comes to parenting. If you are fielding a new product, concept, messaging or pricing study, not recognizing that these moms think about their mom role radically differently can hinder how you make conclusions based on the research.

Another component of cognitive demographics is capturing how people perceive the world that your product/service exists in. A company’s definition of the category it is in may be very different from how the consumer sees the world the product resides in. If you don’t integrate how people perceive the role of your product/service in their lives, you may miss the big picture. As Theodore Levitt, an economist who helped popularize the term “globalization,” famously said, “Customers who buy a drill aren’t buying a drill. They’re buying a hole in the wall.”

Missed the big picture

Years ago, if P&G had integrated a cognitive demographic approach in the diaper category, it may not have missed the big picture, which ended up costing it a large market share that took years to recover. 

Based on reams of research findings that consistently pointed to diaper leakage/need for absorbency being the No. 1 concern and purchase decision determinant, P&G invested tens of millions of dollars developing diaper and manufacturing capabilities to make Pampers the most absorbent/leak-proof diaper on the market. Then Kimberly-Clark made a big marketing push for a new version of Huggies, one that, while more absorbent than previous versions of Huggies, was still less absorbent than Pampers. To P&G’s shock, with the introduction of this new version of Huggies, the Huggies share of market increased and Pampers declined. What happened? Had diaper absorbency/less leakage become less important? Were mothers lying about wanting to purchase diapers that were best at absorbency. Nope! Diaper leakage continued to be the overwhelming No. 1 frustration in the diaper category – even some moms buying Huggies were complaining about Huggies being less absorbent.

So what was going on? Well, P&G had a siloed, non-cognitive demographic view of the diaper category. It thought functionality was the lens through which moms saw the diaper world. But for a number of moms their take on diapers was broader and included a separate emotional component that impacted how they perceived their roles as moms. Through P&G’s functional lens, P&G had viewed the emotional “being a good mom” component as a subsegment of functionality and that the act of buying and putting the more absorbent diaper on their baby was helping them fulfill the “good mom” emotional component.

Focusing almost exclusively on manufacturing the best leak-proof diaper on the market, and believing that the most absorbent diaper was the component that delivered on “good mom,” P&G’s diaper used a type of plastic liner that, while very effective in preventing leaks, also made crinkling noises when the child was picked up. Kimberly Clark recognized that the self-perception “good mom” component was, for a sizable segment of moms, not a subset of the absorbency functionality but an emotional driver that relied on other things beyond absorbency, i.e., moms wanted a diaper that didn’t leak but also separately, the diaper they chose to put on their baby was also a reflection of how good a mom they were. A diaper that made noise suggested to this segment of moms that they were putting “unhealthy” plastic on their child. Huggies diapers were almost as absorbent as Pampers but their quieter plastic liner was doing a better job of delivering on a “healthier”/less plasticky diaper that moms could put on their baby. P&G lost share-of-market when these moms were willing to sacrifice some absorbency to get better delivery on the “good mother” emotional self-perception need. The new Huggies and the most absorbent Pampers both had about the same amount of plastic in the diaper, so if P&G had incorporated cognitive demographics to better understand that for a large segment of moms, the diaper world included a standalone functional and a separate emotional component, its research would probably have picked up that a noisy plastic liner would lead to loss of market share, even if that diaper offered the best absorbency.

Incorporating narrative economics – which uses stories as input to provide insight into how people you are interested in perceive and rationalize the world around them – can help the researcher get a better understanding of how to structure demographic profiles and understand people’s feedback by providing context and background of how people self-perceive. (For more on narrative economics, see my December 2019 Quirk’s article “Storytelling as an input, not just an output.”) Narrative economics utilizes stories that people tell to get insight into how they rationalize their choices and see the world. One way to use narrative economics to get insight into people’s values and how they see the world is to read memoirs, biographies and works of non-fiction. 

An example is J.D. Vance’s “Hillbilly Elegy,” which gives insight to choices and decision-making in the world of poor/lower middle-class Rust Belt whites. Those decisions may appear illogical to an outsider (behavioral economics) but logical to them (narrative economics). For example, being close to family is one of their top values and prevents many who are jobless from moving from a place where there are no jobs to a place that has jobs, even if they are destitute. Another great example is Isabel Wilkerson’s beautifully written “The Warmth of Other Suns,” which uses the detailed life stories of three different Black Americans and their families to provide insight into the Jim Crow world and the impact on the 6 million Black people who migrated from the Southern United States to the Northern United States cities during the 1920s-1970s. 

In addition to books, podcasts are also a great source for getting the world view of almost any specific demographic you may be interested in, but especially valuable if you are doing research on a topic with a very small universe. For example, if you are doing research for a rare medical condition, there is probably a podcast specific to that medical condition. The podcast may also be an avenue in to help recruit these difficult-to-find people to a research study.

Reality check

Utilizing cognitive demographics can be a reality check on whether the way researchers and marketers group people is truly matching how people self-perceive and make decisions. It can also help uncover instances where the alignment of company business units may not reflect a target audience’s view of the world in which your products and services exist.