Artificial Intelligence in Marketing Analytics: The Application of Artificial Neural Networks for Brand Image Measurement

Abstract

Addressing the high complexity of brand image measurement, the present research paper investigates the use of artificial neural networks in this particular application context. Since profound insights into the image of a brand are essential for management, the deployment of this learning algorithm is considered as it allows modeling of complex non-linear and multilayered relationships. The conceptual approach presented in the paper is illustrated with the empirical example of the sportswear manufacturer adidas. By using quantitative survey data, a multilayer artificial neural network is created to link the evaluations of specific brand attributes with the overall evaluation of the brand. Based on an analysis of the connection weights between neurons of the artificial neural network, the importance of different brand attributes for the brand evaluation is quantified. This results in concrete implications for brand management practice and potential for further investigations on the use of artificial intelligence in marketing analytics.

Application of DMSFNN-COA technique for brand image design

“…This technique is executed in MATLAB platform. The acquired outcomes of the BID-DMSFNN-COA method are analysed with the existing methods like BID-GNN [ 10 ], BID-ANN [ 11 ], and BID-CNN [ 12 ] methods respectively.…”

“…Nufer and Muth [ 11 ], have introduced a brand image measurement application of artificial neural networks. The research methodology that is being provided analyses the implementation of artificial neural networks in this specific application environment while taking into account the intricate nature of brand image measurement.…”

Moving Toward Economic and Digital Sustainability in Marketing Analytics

“…Another study investigates the landscape of BDA through the lens of the marketing mix and identifies applications from a different perspective, which include customer segmentation, profiling, product ontology and reputation, promotional marketing analysis, recommendation systems, pricing strategy analysis, competitor analysis, location-based advertising, and community dynamics analysis (Fan et al, 2015). Other applications are seen in new product development (Xu et al, 2016), customer value and firm performance (Aljumah et al, 2021), promotion strategy (Cao & Tian, 2020), social media sentiment analysis (Kauffmann et al, 2020), social media and brand image measurement (Nufer & Muth, 2022), digital transformation and value creation (Wang & Wang, 2020), and marketing decisions (Corrigan et al, 2014).…”