ANALYZING TURKEY'S PREMIER E-COMMERCE MARKETPLACES BY PREDICTIVE EYE TRACKING METHOD

Artificial intelligence (AI) is a rapidly evolving and intensely debated discipline over the last decade. AI has the potential to impact many industries, including neuromarketing. Today, many scholars and academic studies emphasize AI's enormous marketing opportunities. Likewise, neuromarketing is a rapidly expanding discipline in marketing. Neuromarketing often aims to use neuroscientific ideas and marketing strategies and integrate them into marketing domains. Neuromarketing uses electroencephalography, functional magnetic resonance, eye tracking, galvanic skin response, and facial coding to assess subjects' neurophysiological responses to various stimuli. In this study, an analysis was performed with an eye tracker. Eye tracking is the most widely used neuromarketing technology in market research. Today, predictive eye tracking, or AI-based eye tracking, has started to be used as a tool in the neuromarketing field of artificial intelligence. This framework uses many images from device- and subject-based eye-tracking studies to train complex deep-learning algorithms. These algorithms can better predict people's neuroscientific preferences as more data is fed to them. The accuracy of academic visual saliency prediction models is about 90%, with a small margin of error. However, this is expected to improve over time. This study analyzed five web pages in the coffee machine category of Turkey's leading e-commerce marketplaces, www.amazon.com and www.trendyol.com, with cognitive demand and clarity metrics, using Neurovision software. As a result of the analysis, it was determined that the overall cognitive demand metric score of these marketplaces' web pages was acceptable; the overall clarity metric score had the best score on the scale, and the websites in question had very user-friendly designs.