Uncovering the emotion of eating to develop winning products
Guest blog by Dietmar Weiss email@example.com
Eating can give us a myriad of sensations and emotions, good and bad, but it can be difficult for us to put these feelings into words. The slightly earthy, bitter, lingering flavour of elderberry jam can transport me back to my childhood in Germany and give me a warm homely feeling, but I find it hard to adequately describe it in words.
So we know what we like, but the reasons for why we like or dislike a food might be buried deep in our unconscious. Unlocking these emotions and feelings for foods is the basis of my research.
In Japan the feeling about something is called Kansai and Kansai engineering is the method by which feelings and impressions are extracted to optimize products during development, Seeking To communicate with the brain processes that are instinctive and emotional (System 1), rather than what is deliberate and logical (System 2, in Kahneman & Frederick, 2002 nomenclature).
My research focuses on extracting the emotional response to a food product by building a picture representation of these emotions through a visual process. Picture pairs are used to capture the emotional response of the individual to the food. For example a picture pair of a desert and a waterfall, and many others are shown to span an emotional space. The consumer picks the picture which intuitively describes what they are feeling when consuming the product, thereby building a semantic space. For example, we found a salsa sauce sample that contains in its spices mix, a higher amount of smoked chilli and cinnamon that might trigger a more defined feeling of warmth and excitement when the consumer eats it. Consumers were tending more towards pictures of a hot sunny place and pictures of a laughing and lively group of people rather than a snow covered landscape and a solitary person.
Data collected from this testing method will be statistically modelled to reduce the need for time consuming testing, and hopefully arrive faster at an optimal product.
This is an exciting new and emerging tool for food product development and food marketing and is likely to be a new way by which food companies can design specific products that the consumer is more likely to buy.