Low-Level Video Features as Predictors of Consumer Engagement in Multimedia Advertisement

The article addresses modelling of consumer engagement in video advertising based on automatically derived low-level video features. The focus is on a young consumer group (18–24 years old) that uses ad-supported online streaming more than any other group. The reference ground truth for consumer eng...

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Bibliographic Details
Published in:Applied sciences 2023-02, Vol.13 (4), p.2426
Main Authors: Aslan Oğuz, Evin, Košir, Andrej, Strle, Gregor, Burnik, Urban
Format: Article
Language:English
Subjects:
Advertising campaigns
Advertising executives
advertising exposure
automatic estimation
Consumer behavior
consumer engagement
Consumers
low-level video features
Marketing research
Metadata
Multimedia
multimedia signal processing
Observational studies
Online advertising
Statistical analysis
Streaming
Streaming media
Usability
User feedback
Variance
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Summary:The article addresses modelling of consumer engagement in video advertising based on automatically derived low-level video features. The focus is on a young consumer group (18–24 years old) that uses ad-supported online streaming more than any other group. The reference ground truth for consumer engagement was collected in an online crowdsourcing study (N = 150 participants) using the User Engagement Scale-Short Form (UES-SF). Several aspects of consumer engagement were modeled: focused attention, aesthetic appeal, perceived usability, and reward. The contribution of low-level video features was assessed using both the linear and nonlinear models. The best predictions were obtained for the UES-SF dimension Aesthetic Appeal (R2=0.35) using a nonlinear model. Overall, the results show that several video features are statistically significant in predicting consumer engagement with an ad. We have identified linear relations with Lighting Key and quadratic relations with Color Variance and Motion features (p
ISSN:2076-3417
2076-3417
DOI:10.3390/app13042426