Applying a Complexity-based Approach for Market Research

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Gary Wong
Consultant, Canada

Applying a Complexity-based Approach for Market Research

An alternative to a 'hypothesis-driven' approach is one that is 'research-driven'. It sidesteps the concerns and pitfalls associated with traditional surveys and questionnaires in which a major issue that is extremely difficult to avoid the cognitive biases of survey designers and interviewers.
The aim of market research should be to discover the unarticulated, unspoken needs of customers. To achieve that, instead of answering questions, customers' experiences can be gathered in the form of narratives – fragmented positive or negative stories around an emotional decision that was made. Storytellers are given the opportunity to self-intepret the meaning behind their narrative. That is, there is no one saying "I know exactly what you mean" or "I think this is what the person was feeling." Only the storyteller knows and has the authentic voice.
Self-interpretation is done through a set of visual signifiers (e.g. triads, dyads) with multiple aspects allowing the responder to indicate the most dominant aspect(s) related to their experience.
The narrative data also called "thick data" and is converted by Sensemaker® software to reveal patterns in the customer experiences that possibly explain what influences decisions. Of high value in market research are 'weak signals' - potential insights which could conceivably point to the emerging of a new market.

This approach has been used by major corporations. One example is KPMG who analyzed the investment attractiveness of Russia's regions from the point of view of foreign investors, who have global choices about where to invest: Taking the Investor Perspective: Looking at the regional investment climate through the eyes of foreign businesses.

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