Article Summary

Article Summary

Over the past decade, practitioners and academics have applied neurophysical methods to understand the marketing phenomenon. However, it is still unclear how these methods predict the success of advertising. In this article, the researchers attempt to predict distinct advertising measures through the assessment of 30-second TV ads. The experimental protocol measures the effectiveness of advertising in relation to biometrics, eye tracking, functional magnetic resonance imaging, and electroencephalography. The listed measures tap reliably onto the high level of constructs like desirability, memory, and attention applicable in advertising research. Additionally, the researchers used time series data on gross rating points and sales to relate TV ads to individual level response and the adverts’ aggregate market level elasticity (Venkatraman et al., 2015, pp. 436).  Furthermore, the researchers highlight how the measures of functional magnetic resonance imaging (beyond traditional baseline measures) explain variance in the elasticity of advertising. Of keen to note, however, is that the ventral striatum activity is one of the strongest predictors of real-world market level response to television advertising, prompting the need for the article authors to discuss the implications of study findings to practice and theory.

Each year, corporations spend a significant amount of resources to advertise new and existing products successfully. Failure to do so renders the firms vulnerable to competitions from larger multinationals, thus threatening their survival in the business environment. Most of the spending occur during the advert pretest phase and in-market analysis phase after the launch of the campaign.  Currently, strategic marketers apply sophisticated statistical approaches like marketing mix modeling to assess the impact of financial spending on advertising across the multimedia.  The researchers admit that considerable industrial and academic research has already been conducted using neurophysiological measures, but it is imperative to examine if these measures translate into real-life success in advertising or not. Considering this, the researchers intend to link neurophysiological and traditional measures to actual consumer responses in the market, especially with regards to advertising elasticity. Besides, they assess the value of neurophysiological methods in projecting the advert’s success beyond traditional methods.

The review board of Temple University approved the study and tests for 37 advertisements drawn from six business entities. The 30-second adverts covered approximately 15 distinct brands and products. Additionally, the researchers recruited the participants from the United States online. Information about TV ad watching was also collected using online pre-screening questionnaires to complement the study. Besides, participant’s predisposition to brands and products was measured by showing images of featured brands and products while collecting information regarding their usage and purchase intent. Biases were minimized through the inclusion of products from competitors in the study.

On the other hand, the main study involved data collection from more than 225 participants, though the research was split into four particular phases. For greater experimental control, the researchers conducted the study in the laboratory. The four phases included traditional and implicit measures, Biometrics and eye tracking, fMRI, and EEG (Venkatraman et al., 2015, pp. 443). Notably, the number of participants in each phase was variable as per the data required.

The study established a significant correlation that exists among multiple measures related to advertisements such as familiarity, relevance, linking, and informativeness. Moreover, the researchers discovered major correlations among product-related measures like recommendation intent, product familiarity, and usage intent. Furthermore, the experiments revealed a strong correlation between the product-related measures and ad-related strategies. Next, the analysts applied factor analysis to categorize traditional advertising measures. Given that different sets of study subjects completed each of the four phases, analysis of the consistency of traditional measures was possible. For instance, there was a strong consistency linking familiarity and recognition due to self-reporting.

Further, examination of the relationship between traditional and biometric measures for the study subjects revealed deceleration correlated with recognition, linking and change in personal intent. The findings proved that deceleration provides independent measures of increased consumer attention. In the case if the relationship between traditional measures and fMRI, the researchers elucidated the neural correlates of fundamental traditional measures including recognition, purchase intent, and linking. They used average purchase intent and average linking measures for specified adverts across study subjects from all four categories as covariates. The move allowed for the identification of brain regions that tracked the shifting measures.

While a healthy skepticism exists in practice and academia on the value and contribution of advertisement as a marketing method, it is undeniable that this study provides an important framework on how neuroscience academic research informs the practice of advertising. In fact, it demonstrates the relative contribution of specific measures with regards to the prediction of advertising elasticity using objective and independent measures on successful advertising produced via marketing-mix modeling techniques. The implications of this study are numerous. First, it allows for direct comparison of neurophysical and traditional methods of examining television adverts. Secondly, it examines the interrelationship between the measures obtained using neurophysical and traditional methods, given they are correspondent to fundamental constructs linkable to advertising success (Venkatraman et al., 2015, pp. 450). Lastly, the study demonstrates the existing relationship between real-world outcomes of marketing and lab tests.

References

Venkatraman, V., Dimoka, A., Pavlou, P. A., Vo, K., Hampton, W., Bollinger, B., ... & Winer, R. S. (2015). Predicting Advertising Success beyond Traditional Measures: New Insights from Neurophysiological Methods and Market Response Modeling. Journal of Marketing Research, 52(4), 436-452.