A Framework using Neurometrics, Machine Learning & Genetic Algorithms to Choose Optimal Advertisement Method | Original Article

ABSTRACT:

Neuromarketing is an emerging field and gaining rapid credibility and adoption among advertising and marketing professionals. Each year, over 400 billion dollars is invested in advertising campaigns. Yet, conventional methods for testing and predicting the effectiveness of those investments have generally failed because they depend on consumers’ willingness and competency to describe how they feel when they are exposed to an advertisement. Neuromarketing offers cutting edge methods for directly probing minds without requiring demanding cognitive or conscious participation. This paper discusses the promise of neuromarketing and suggests it has the potential to significantly improve the effectiveness of both commercial and cause-related advertising messages around the world. Neuromarketing under the control of genetic algorithms and machine learning techniques result in a framework that can be used to evaluate the effectiveness of different advertisement strategies to figure out the best suitable channel of advertisement for business practices. This paper is divided into four sections. Section-I discusses brief introduction of neuromarketing, review of existing literature, gap analysis. Section-II discusses about problem formulation and objectives to be achieved. Section-III presents the methodology adapted and algorithm used in the research. Section-IV deals with results analysis and conclusion of the study. related to genetic algorithm, neurometrics, and machine learning. After reviewing the existing literature the researcher feels that Genetic algorithm, Neurometrics, and Machine learning can be clubbed together to provide a framework which can help in determining the impacts of different advertisement strategies to find out the best suitable mode of advertisement for business practices.