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I created a new clustering algorithm which can be used with all types of response data which is gathered during consumer tests of product concepts, product prototypes, final products and marketing communication campaigns. My new clustering algorithm is suitable to identify products with most appealing sensory and non sensory dimensions before they are introduced in markets and to identify most effective elements of marketing communication campaigns.
The existing product response data analysis algorithms which try to identify and calculate the most pleasant sensory and non sensory dimensions of products and most effective elements of marketing communications campaigns have 2 big problems:
1. They are not able to take adequately into account individual differences of consumers in stimulus perception and responses to generate representative and commercial meaningful results
2. They are not objective
I could develop a new response data analysis algorithm for identifying and calculating the most pleasant sensory and non sensory dimensions of products and most effective elements of marketing communications campaigns which solves the 2 problems of the existing ones !
My response data analysis process calculates with an accuracy of 99% and the highest possible representativeness the most pleasant sensory and non sensory dimensions of products and most effective elements of marketing communications campaigns! That is at least 40% accurater and 50% reliabler at the same time than other similar existing response data analysis algorithm.
With my response data analysis algorithm firms can make estimated at least 10% more revenue than without my response data analysis algorithm. Would you like to buy my response data analysis algorithm?
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