The Measurement of Consumer Interest and Prediction of Product Selection in E-commerce Using Eye Tracking Method

Sari, Juni Nurma; Nugroho, Lukito Edi; Santosa, Paulus Insap; Ferdiana, Ridi

doi:10.22266/ijies2018.0228.04

Cited by 9 publications

(7 citation statements)

References 16 publications

(19 reference statements)

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“…EGTs have been widely used in interactive and diagnostic applications such as in marketing field, e-commerce, psychology, in augmented and virtual reality [103, 104, 105, 106] . Eye gaze tracking has been used to study the influence of human visual behavior on consumer behavior and other attentional processes [9, 53, 104, 107].…”

Section: Resultsmentioning

confidence: 99%

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Singh

Modi

2019

Heliyon

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Eye gaze tracking has been used to study the influence of visual stimuli on consumer behavior and attentional processes. Eye gaze tracking techniques have made substantial contributions in advertisement design, human computer interaction, virtual reality and disease diagnosis. Eye gaze estimation is considered critical for prediction of human attention, and hence indispensable for better understanding human activities. In this paper, Latent Semantic Analysis is used to develop an information model for identifying emerging research trends within eye gaze estimation techniques. An exhaustive collection of 423 titles and abstracts of research papers published during 2005–2018 were used. Five major research areas and ten research trends were classified based upon this study.

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Section: Resultsmentioning

confidence: 99%

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Singh

Modi

2019

Heliyon

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“…Eye-tracking is already widely used to analyze human's behavior on websites, e.g., using fixation count and fixation duration to predict customer interest and choices [41,42]. The time-to-first-fixation of an AoI was found to not support customer intention prediction [41].…”

Section: Related Work On Eye-trackingmentioning

confidence: 99%

Integrating Eye- and Mouse-Tracking with Assistant Based Speech Recognition for Interaction at Controller Working Positions

2021

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Assistant based speech recognition (ABSR) prototypes for air traffic controllers have demonstrated to reduce controller workload and aircraft flight times as a result. However, two aspects of ABSR could enhance benefits, i.e., (1) the predicted controller commands that speech recognition engines use can be more accurate, and (2) the confirmation process of ABSR recognition output, such as callsigns, command types, and values by the controller, can be less intrusive. Both tasks can be supported by unobtrusive eye- and mouse-tracking when using operators’ gaze and interaction data. First, probabilities for predicted commands should consider controllers’ visual focus on the situation data display. Controllers will more likely give commands to aircraft that they focus on or where there was a mouse interaction on the display. Furthermore, they will more likely give certain command types depending on the characteristics of multiple aircraft being scanned. Second, it can be determined via eye-tracking instead of additional mouse clicks if the displayed ABSR output has been checked by the controller and remains uncorrected for a certain amount of time. Then, the output is assumed to be correct and is usable by other air traffic control systems, e.g., short-term conflict alert. If the ABSR output remains unchecked, an attention guidance functionality triggers different escalation levels to display visual cues. In a one-shot experimental case study with two controllers for the two implemented techniques, (1) command prediction probabilities improved by a factor of four, (2) prediction error rates based on an accuracy metric for three most-probable aircraft decreased by a factor of 25 when combining eye- and mouse-tracking data, and (3) visual confirmation of ABSR output promises to be an alternative for manual confirmation.

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“…The prediction data in this study used the Chandon model. The previous research used Chandon model as measurement of the prediction of product selection [22].…”

Section: B Prediction Of Consumers Purchase Product Desirementioning

confidence: 99%

“…This process needs product information and consumer profile. After consumer attention is defined by total FD, the next process is calculating the prediction of purchase (C) of that product using Chandon model [10], [22]. The result of prediction of purchase can be used as transaction data, while FD can be used as consumer interest data.…”

Section: Product Recommendations Based On Data Eyementioning

confidence: 99%

Product Recommendation Based on Eye Tracking Data Using Fixation Duration

Sari

Nugroho

Santosa

et al. 2021

IJITEE

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E-commerce can be used to increase companies or sellers’ profits. For consumers, e-commerce can help them shop faster. The weakness of e-commerce is that there is too much product information presented in the catalog which in turn makes consumers confused. The solution is by providing product recommendations. As the development of sensor technology, eye tracker can capture user attention when shopping. The user attention was used as data of consumer interest in the product in the form of fixation duration following the Bojko taxonomy. The fixation duration data was processed into product purchase prediction data to know consumers’ desire to buy the products by using Chandon method. Both data could be used as variables to make product recommendations based on eye tracking data. The implementation of the product recommendations based on eye tracking data was an eye tracking experiment at selvahouse.com which sells hijab and women modest wear. The result was a list of products that have similarities to other products. The product recommendation method used was item-to-item collaborative filtering. The novelty of this research is the use of eye tracking data, namely the fixation duration and product purchase prediction data as variables for product recommendations. Product recommendation that produced by eye tracking data can be solution of product recommendation’s problems, namely sparsity and cold start.

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The Measurement of Consumer Interest and Prediction of Product Selection in E-commerce Using Eye Tracking Method

Cited by 9 publications

References 16 publications

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Integrating Eye- and Mouse-Tracking with Assistant Based Speech Recognition for Interaction at Controller Working Positions

Product Recommendation Based on Eye Tracking Data Using Fixation Duration

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