As the story goes, the first “market research” was conducted in the United States around 1820, when a newspaper tried to analyse the flow of political winds through a simple street survey. Beginning to take shape with advertising tests in the early 1900s, the industry developed significantly after the Second World War. Driven by the need for “differentiation” in products and services, the drive to understand the consumer (insight) led to systems that allowed detailed examination of existing data, and — with the help of developing statistical methods — quantitative research began. From the 1970s onwards, qualitative research techniques were used to examine consumer understanding in depth. From the 1980s, statistics, marketing and the other disciplines that make up qualitative research came together into a holistic perspective. In the 1990s, when cause-and-effect relationships were questioned more closely, we witnessed many research models developed by global market research agencies.
Because of both the growing need for knowledge and insight at different levels and the contribution of technology to market research (particularly to analysis methods), research agencies began working on new and different research methods and analyses. I like to think of the history of research in four periods:
• Infancy: the period up to the last quarter of the 1900s.
• Childhood: the period up to the 1990s, when research was generally conducted with traditional statistical analysis models.
• Adolescence: the period up to the 2010s, when branded research models were used and research was infused with qualitative work.
• Youth: the period since the 2010s, in which alternative research techniques and analysis methods have taken centre stage.
Naturally, each period claimed to be more innovative and to deliver more added value than the previous one. While every period took steps that moved research forward, there were also situations in which the old was ignored and the focus fell only on new methods. In those cases, people working in research built their marketing strategies on the inadequacies of the previous period. This stemmed both from the search for a market of one's own and from a natural generation gap. In recent years we have witnessed a similar generation gap in Türkiye. Every research agency visiting clients to introduce their company and methods explains how “innovative”, how “different”, how “cutting-edge” their approach and models are and how well they justify the money spent, listing the advantages of next-generation research approaches over classical methods.
So, are next-generation methods really that good? To what extent do they differ from methods described as traditional? And perhaps most importantly for decision-makers: should investment go into next-generation models rather than traditional methods? Time will answer these questions in each case. But there are some factors worth considering in these generational battles.
The most important foundation for advocates of next-generation research methods is human nature. The first serious challenge to the idea that people are purely rational came from Daniel Kahneman. In the work for which he received the Nobel Prize in Economics in 2002, Kahneman demonstrated that human economic behaviour and decision-making are not purely rational, and that emotions and intuitions also play an active role. On the argument that people act on emotion rather than the classical “homo economicus” model (the economic model holding that people decide rationally), applications aimed at understanding human behaviour are being developed. This is why the strongest criticism is directed at traditional research methods that rely on “stated responses”.
According to Harvard Business School professor Gerald Zaltman, “Most market research is biased towards reason rather than emotion. Marketers collect survey results and other consumer information and try to interpret it as if consumers' decisions emerged from conscious, rational processes.” Zaltman argues that consumers like having many options but prefer to avoid the mentally burdensome effort of dealing with them — and that this effort is minimised by emotion. Therefore, to understand the consumer (the human being), one must understand emotions, and methods capable of producing non-stated outputs — such as projective techniques or neurological research — produce more effective results than traditional methods. Again according to Zaltman: “Neurological research reveals that people do not think in a linear, staged order. Metaphorically speaking, they cannot taste a cake by trying its raw ingredients one after another. They only enjoy a fully baked cake.”
Even though someone who dislikes eggs does not need to wait for the cake to be baked in order to want it made without eggs — and even though the advertising copy used in neurological measurement for ad tests can be an unfinished storyboard — I agree that as a general philosophy this is the ideal.
Yener Girişken, who works on neurological measurement, notes in his book *Gerçeği Algıla* that “neuro-measurements applied during purchasing behaviour are important because they make it possible to observe people's purchasing processes through the prefrontal region of the brain”. “In other words, by examining the activation level in the prefrontal region we will be able to draw important conclusions about product pricing based on our decision tendencies. And without even asking people a question. This may in turn call into question the pricing research model known in the industry as conjoint, in which results are analysed according to people's rational choices.”
There are also those who think next-generation studies do not create as much added value as claimed. Hulusi Derici, founder of the M.A.R.K.A. advertising agency, is sharply critical of next-generation research methods, particularly neurological measurement: “I find it a rather comical enthusiasm. If you look at market leaders, at brands that entered the market recently and succeeded, at brands that collapsed while at the top — everything is already there in plain sight. What is the point of insisting on not seeing the obvious and looking for something more hidden, deeper down? If this friend is going to solve the secrets of the brain, let them find a cure for death too. It is more or less the same thing.”
Personally, while I do not warm to the idea of neurological research replacing advanced statistical modelling, I think denying its contribution to the marketing and market research world is contrary to scientific reality. I have two reservations about neurological research:
• It is not quite right to think that emotions such as liking or stress, identified through neurological methods, alone drive purchasing behaviour. Because humans are social beings, and decisions may well be shaped so as to gain social acceptance. Someone might, for example, use a brand they do not particularly like purely for social acceptance. When a beverage that performs similarly to its competitor in blind taste tests falls behind once tested branded, it shows how difficult potential estimation becomes with more than one component involved.
• The complexity does not end with the reason–emotion dilemma. Human-specific details such as “intuitions”, “feelings”, “values” and “will” — which neuroscientists have only recently begun to discuss how to handle — are still waiting to be discovered and made sense of.
• Research measuring several variables at once can, in every case, provide information more effectively than neurological measurement built around a single variable (an advertisement, a price, a brand, and so on). In a study aimed only at finding the right price, for instance, neurological applications can determine preference between different price alternatives. But once variables such as different packaging or different sizes enter the picture, identifying the component that creates liking through neurological signals becomes both difficult and highly costly.
In light of all this, the methods used in market research must be chosen carefully, and thought must be given to which methods best serve the desired objectives. Conflict and interaction between generations will always exist. What matters is reaching the targeted answers and insight, and ensuring research creates added value. Blending findings obtained through traditional methods with next-generation research approaches will both increase confidence in market research and support marketing decision-makers in their decision-making.
Antonio Damasio of the University of Iowa, who gained a wide following in Türkiye with *Descartes' Error*, concluded from his research on the complex relationships between brain, mind and body: “We are not thinking machines that feel; we are feeling machines that think.” To understand this machine, we need multi-disciplinary research — research that brings different perspectives together.