Identification of emotional patterns according to neural and physiological signals in product concept tests

• Grant number: 18/07466-9
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: December 01, 2018
• End date: August 31, 2019
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Renan Schiavolin Recio
• Grantee: Renan Schiavolin Recio
• Company: NEURUX - Soluções em Neurociência e Tecnologia Ltda
• CNAE: Tratamento de dados, provedores de serviços de aplicação e serviços de hospedagem na internet ; Pesquisas de mercado e de opinião pública
• City: São Paulo
• Associated researchers: Diego dos Santos Vega Senise
• Associated research grant(s): 19/22602-9 - Identification of emotional patterns according to neural and physiological signals in product and advertisement concept tests, AP.PIPE
• Associated scholarship(s): 18/26243-0 - Identification of emotional patterns according to neural and physiological signals in product concept tests, BP.PIPE

Abstract

Studying behaviour and opinion from potential clients is essential for developing better products and services, create marketing strategies and more effective communication. One method in market research for product concept testing is to apply declarative questionnaires. Despite the fact this technique brings important results regarding the evaluation of the acceptance and success scenario of one product, it is debatable that the method is capable of capturing relevant non-declarative information, which interferes with decision-making of the target public. Decision-making is one of the most important cognitive components to be evaluated in market research and it is affected by many aspects, such as attention, memory and emotion. With respect to emotion, this component has been gaining greater prominence in market research, but since it's non-declarative aspect, it's hard to be assessed by traditional market research. People might not be able to put in words what they feel or wish to hide some feelings of shame and fear in front of a researcher. Therefore, we intend to use techniques in neuroscience to assess hidden emotional states during product concept tests. We will use electrophysiological measures, facial recognition and non-verbal scales of emotion and computational classifiers in order to verify the gain of information from each type of data about emotional states. As a result, we can develop a new methodology that can be used together with traditional market research techniques to improve the current metrics, adding value and helping companies develop more effective strategies and products. (AU)