Demonstrating the success of the Sensory AI Drivers methodology in the Bakery category

BRIEF

A new client came to MMR having seen a decline in sales over the course of a few years. They had never conducted any formal consumer testing and now wanted to understand how their product performed versus the competition, and how to improve it.

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APPROACH

We tested 6 products with consumers in a central location test in the US and had our expert sensory panel profile the same set of products in our sensory facility. Using our Sensory AI Drivers (SAID) approach, we combined the consumer and sensory data to identify drivers of liking and guide optimization.

OUTCOME

The results confirmed what the client suspected; their product was rated amongst the least appealing. Our SAID analysis identified a number of primary and secondary drivers for the category. Looking at how the product performed on these drivers, we were able to identify priority attributes for optimization, from changing the size of the product through to taste and textural properties.

The client embarked on some of this optimization and follow-up prototype testing versus their current identified a recipe that resulted in a significant uplift in appeal!

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