Abstract

Interest in improving advertisement impact on potential consumers has increased recently. One well-known strategy is to use emotion-based advertisement. In this approach, an emotional link with consumers is created, aiming to enhance the memorization process. In recent years, Neuromarketing techniques have allowed us to obtain more objective information on this process. However, the role of the autonomic nervous system (ANS) in the memorization process using emotional advertisement still needs further research. In this work, we propose the use of two physiological signals, namely, an electrocardiogram (heart rate variability, HRV) and electrodermal activity (EDA), to obtain indices assessing the ANS. We measured these signals in 43 subjects during the observation of six different spots, each conveying a different emotion (rational, disgust, anger, surprise, and sadness). After observing the spots, subjects were asked to answer a questionnaire to measure the spontaneous and induced recall. We propose the use of a statistical data-driven model based on Partial Least Squares-Path Modeling (PSL-PM), which allows us to incorporate contextual knowledge by defining a relational graph of unobservable variables (latent variables, LV), which are, in turn, estimated by measured variables (indices of the ANS). We defined four LVs, namely, sympathetic, vagal, ANS, and recall. Sympathetic and vagal are connected to the ANS, the latter being a measure of recall, estimated from a questionnaire. The model is then fitted to the data. Results showed that vagal activity (described by HRV indices) is the most critical factor to describe ANS activity; they are inversely related except for the spot, which is mainly rational. The model captured a moderate-to-high variability of ANS behavior, ranging from 38% up to 64% of the explained variance of the ANS. However, it can explain at most 11% of the recall score of the subjects. The proposed approach allows for the easy inclusion of more physiological measurements and provides an easy-to-interpret model of the ANS response to emotional advertisement.

Highlights

  • Interest in improving advertisement impact on potential consumers has increased recently

  • Before the analysis of the partial least squares path modeling approach (PLS-PM) models, we present the analysis of the recall scores for the different emotions represented in the spots

  • We present the results of the measurement model, which allows us to identify the adequacy of the manifest variables (MV) as valid indicators of the LV

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Summary

Introduction

Interest in improving advertisement impact on potential consumers has increased recently In this context, Neuromarketing techniques have allowed us to obtain more objective information on how the consumer unconsciously processes the information (Norton et al, 2007; Babiloni, 2015). The main research techniques are the following: (1) neuroimaging technologies to assess brain activity, such as functional magnetic resonances (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MNG), for market research (Ioannides et al, 2000; Vecchiato et al, 2010, 2014); and (2) autonomic nervous system (ANS) analysis tools, such as electrodermal analysis (EDA) and heart rate variability (HRV), to study emotion, cognition, and attention (Critchley, 2002; Cartocci et al, 2017). The latest, EDA and HRV, are physiological signals that can be registered with cheap and easyto-use equipment

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