The use of computer vision to analyze brand-related user generated image content
Nanne,Annemarie Antheunis,Marjolijn van der Lee,Chris Postma,Eric Wubben,Sander van Noort,Guda
Nanne,Annemarie
Antheunis,Marjolijn
van der Lee,Chris
Postma,Eric
Wubben,Sander
van Noort,Guda
Abstract
With the increasing popularity of visual-oriented social media platforms, the prevalence of visual brand-related User Generated Content (UGC) have increased. Monitoring such content is important as this visual brand-related UGC can have a large influence on a brand's image and hence provides useful opportunities to observe brand performance (e.g., monitoring trends and consumer segments). The current research discusses the application of computer vision for marketing practitioners and researchers and examines the usability of three different pre-trained ready-to-use computer vision models (i.e., YOLOV2, Google Cloud Vision, and Clarifai) to analyze visual brand-related UGC automatically. A 3-step approach was adopted in which 1) a database of 21,738 Instagram pictures related to 24 different brands was constructed, 2) the images were processed by the three different computer vision models, and 3) a label evaluation procedure was conducted with a sample of the labels (object names) outputted by the models. The results of the label evaluation procedure are quantitatively assessed and complemented with four concrete examples of how the output of computer vision can be used to analyze visual brand-related UGC. Results show that computer vision can yield various marketing insights. Moreover, we found that the three tested computer vision models differ in applicability. Google Cloud Vision is more accurate in object detection, whereas Clarifai provides more useful labels to interpret the portrayal of a brand. YOLOV2 did not prove to be useful to analyze visual brand-related UGC. Results and implications of the findings for marketers and marketing scholars will be discussed. (C) 2019 Direct Marketing Educational Foundation, Inc. dba Marketing EDGE. All rights reserved.
Description
Funding Information: We are grateful to Emiel Krahmer for thinking along with the design of the label evaluation. We would also like to thank our fellow researchers at the Interactive Marketing Research Conference 2018, for the useful feedback they provided during the High Density Session. Publisher Copyright: © 2019 Marketing EDGE.org. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
Date
2020-05-01
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Keywords
Visual brand-related UGC, Computer vision, Pre-trained computer vision, Image mining, Automated content analysis, SOCIAL MEDIA, CONSUMERS, EWOM
Citation
Nanne, A, Antheunis, M, van der Lee, C, Postma, E, Wubben, S & van Noort, G 2020, 'The use of computer vision to analyze brand-related user generated image content', Journal of Interactive Marketing, vol. 50, pp. 156-167. https://doi.org/10.1016/j.intmar.2019.09.003