The increasing abundance of data generated from every moment of our lives has eliminated two once important reasons for using qual. One of these was that qual is cheap, which did a lot of harm by framing qual as trivial research with tiny sample sizes. The other was that qual was a great way to 'hear the voice of the consumer'. However, with social listening and interactive panels, qual is by no means the most efficient way of doing this, and qual should never have been about communicating the voice of the customer in a literal, unmediated way.
A key contribution of qual in the face of Big Data will be in helping to define the most meaningful questions, which our newly abundant data can then be directed towards answering. Qual can do this because it is uniquely suited to the psychological interpretation of context. So, what is qual's unique value when it comes to interpreting context?
According to Daniel Kahneman, there are three types of information that? can be extracted from what people say: Rationalisation, Association and Metaphor. Approaching qual from this perspective helps to pinpoint the distinct forms of information ?that we elicit and the need to handle them in different ways. It can also help to distinguish what it is about qual that is truly unique within the research field.
Rationalisation is the type of information that consumers deliver in response to an implicit or explicit question. It is what most people would recognise as a conventional answer, and is essential to communication. However, it has acquired something of a bad name where research is concerned. No matter how convincing and convinced consumers may ?be, they are not reliable witnesses to their? own motivations or behaviour. As such, rationalisation is a data source that both qual and quant need to use without naivety. It is a form of context-specific linguistic behaviour, a clue but not the literal truth. Qual is better placed than quant to interpret rationalisations, but this is not the form of information that defines qual's unique contribution to research.
Association is another form of information that is easy for qual to access and is in ?many ways more valuable than consumer rationalisation. When we understand people's associations, we understand the context that a product or brand is set within. Observing patterns of associations can provide strong evidence of the assumptions that underlie a topic and how it is framed. And this enables qual to make a significant contribution through association-focused techniques. Increasingly though, ?this is not a unique capability. Quantitative research is becoming adept at presenting ?this kind of data and identifying significant patterns of response.
This takes us to Metaphor. In this sense, metaphor is the thought structure that is essential to cognition and the communication of meaning. Let's call it 'Big Metaphor' to help underline this distinction.
Big Metaphor is an observation about how the mind identifies meaning by observing a parallel between one thing and another, in order to frame the world around us. Our speech, cognition and behaviour are impregnated with this kind of invisible metaphor, in fact we use a metaphor every four sentences on average.
The job of observation in research is essentially to identify these implicit metaphors, because they explain why people do things in the way that they do. Analysis of metaphors allows us to unwrap psychological mechanics and align products, ads and brands with these invisible rules. In talking about 'metaphor' what we are really talking about is psychological meaning.
Looked at this way, it becomes obvious that products are full of metaphorical meaning: milk is love, Coke is happiness, lipstick is hope and tea is reflection. At the more granular level, every ad has a story, which will be archetypal at one level and will therefore be a bearer of metaphorical meaning.
If we understand metaphor in this broad sense, as Big Metaphor, we can see that it encompasses all that is most valuable in qualitative practice: from personification, to collage, to storytelling. They are all ways of generating the consumer meanings that we already know are core to inspiring and insightful qual.
Machines cannot recognise metaphor, since they work by calculation rather than by analogy. This is a major gap given the central importance of metaphor in human cognition. New data sets and algorithms will yield ever broader, more immediate and more powerful information, but its psychological significance will remain elusive unless we leverage the most effective research tool that we have for unlocking metaphorical meaning. As Big Data increasingly defines the future of quant research, so Big Metaphor will increasingly define the role of qual.
TNS advises clients on specific growth strategies around new market entry, innovation, brand switching and stakeholder management, based on long-established expertise and market-leading solutions. With a presence in over 80 countries, TNS has more conversations with the world's consumers than anyone else and understands individual human behaviours and attitudes across every cultural, economic and political region of the world. TNS is part of Kantar, one of the world's largest insight, information and consultancy groups. Please visit www.tnsglobal.com for more information.
Kantar is the data investment management division of WPP and one of the world's largest insight, information and consultancy groups. By connecting the diverse talents of its 13 specialist companies, the group aims to become the pre-eminent provider of compelling and inspirational insights for the global business community. Its 28,500 employees work across 100 countries and across the whole spectrum of research and consultancy disciplines, enabling the group to offer clients business insights at every point of the consumer cycle. The group's services are employed by over half of the Fortune Top 500 companies. For further information, please visit us at www.kantar.com.