Using Eye Tracking to Explore Consumers' Visual Behavior According to Their Shopping Motivation in Mobile Environments

Abstract

Despite a strong shift to mobile shopping trends, many in-depth questions about mobile shoppers' visual behaviors in mobile shopping environments remain unaddressed. This study aims to answer two challenging research questions (RQs): (a) how much does shopping motivation like goal orientation and recreation influence mobile shoppers' visual behavior toward displays of shopping information on a mobile shopping screen and (b) how much of mobile shoppers' visual behavior influences their purchase intention for the products displayed on a mobile shopping screen? An eye-tracking approach is adopted to answer the RQs empirically. The experimental results showed that goal-oriented shoppers paid closer attention to products' information areas to meet their shopping goals. Their purchase intention was positively influenced by their visual attention to the two areas of interest such as product information and consumer opinions. In contrast, recreational shoppers tended to visually fixate on the promotion area, which positively influences their purchase intention. The results contribute to understanding mobile shoppers' visual behaviors and shopping intentions from the perspective of mindset theory.

Introduction

Owing to the unprecedented development of highly intelligent mobile technologies, mobile commerce worldwide has been increasing rapidly. In the mobile shopping environments, consumers are allowed to browse retail products, purchase and pay for them, and arrange for their delivery.¹ The numerous advantages of mobile devices, such as their mobility and personalization, enable the development of new shopping services that can fulfill more consumer requirements.² As a result, retail mobile shopping, which includes shopping through mobile phones and tablets, increased by 70 percent and reached $42.13 billion in 2013.³ Goldman Sachs Group, Inc., estimated that retail mobile sales will reach ∼$626.00 billion in 2018. However, despite the industry's high expectations for mobile shopping, a relatively small proportion of people actually use their mobile devices to make their final purchases. According to the Centre for Retail Research,⁴ in 2015 only 12.8 percent of users paid for purchases through mobile devices. This indicates that consumers are reluctant to finalize their shopping on mobile devices, despite spending considerable time shopping on them. This phenomenon illustrates the necessity to understand mobile shoppers' behaviors much more.⁵

Mobile shopping is arguably very different from brick-and-mortar and desktop online shopping because of the characteristics of mobile devices.⁶ First, mobile devices support users in accessing information in real time from anywhere they have an Internet connection, and so they can freely use information services with diverse motivations in various situations.⁷ For instance, Yang and Kim⁸ identified that idea, efficiency, adventure, and gratification shopping motivations are associated with mobile shoppers. Consumers with different motivations could demonstrate quite different shopping behaviors. Second, mobile devices provide information on a smaller screen than desktops. In other words, mobile shoppers can only exercise their visual attention at the product information presented on a small mobile screen.⁹ The visual behavior reveals consumers' areas of concern and their cognitive procedure when making a buying decision.¹⁰ Thus, the retailers' challenge is how to grab the mobile shoppers' visual attention to the shopping information displayed on a limited mobile screen.

The literature has limited studies on understanding mobile consumers' visual behaviors from the view of the eye-tracking method. Kim et al.¹¹ examined the users' different web search behaviors between desktop and mobile devices. Using an eye-tracking approach, the previous studies found that users had more difficulty extracting information from the search results of a mobile device. Qu et al.¹² analyzed users' visual behavior on the smartphone instant message apps by using an eye tracker. Sohn et al.¹³ also used an eye-tracking approach to identify the impacts of the perceived visual complexity of mobile online shops on users' satisfaction. In the desktop environments, eye-tracking approach was adopted to explore online consumer's different visual behaviors according to shopper's gender types, cognitive styles, and motivations.^14–16 It is noted that there are still scant studies to identify mobile shopper's visual behaviors in mobile environments.

Online shoppers tend to show different shopping behaviors when they possess different shopping motivations such as goal-oriented motivation and recreational.¹⁷ Shoppers with goal-oriented motivation tend to shop for their target products more earnestly than those with recreational motivation. Mindset theory states that consumers with a task-focused shopping orientation are more likely to activate the cognitive procedures of an implemental mindset, whereas consumers with an experiential shopping orientation are more likely to rely on the cognitive procedures of a deliberative mindset.¹⁸ Therefore, we expect that the analysis of the consumers' visual behavior in a mobile shopping context may shed light on our understanding of how mobile shoppers show different cognitive procedures in line with their shopping motivation. In this sense, this study proposes two research questions (RQs).

RQ1: How do mobile shoppers' shopping motivations, such as goal-oriented motivation and recreational motivation, affect their visual behaviors to the shopping information displayed on a mobile screen?

RQ2: How do the mobile shoppers' visual behaviors influence their purchase intention?

Method

To test our hypothesis, we conducted experiments using the eye-tracking method. As one of the typical physiological techniques, eye tracking is used to measure the visual attention patterns of the experiments' participants.¹⁹

Participants

Young people in their 20s typically exhibit active usage of mobile device and mobile shopping.²⁰ Therefore, we recruited 50 college students (30 females, 20 males) to the eye-tracking experiments. Eight participants were excluded from the experiments because of incorrect calibration. Of the remaining participants, 44 percent were under 21 years old. Of these, 37 percent reported that they frequently used online shopping. Participants received $10 for their participation.

Shopping information and experiment devices

The target product is a notebook computer. Mobile shopping information about the product is displayed on a smartphone, which is to be observed by the participants as shown in Figure 1. As is shown in Table 1, nine categories were used for clarity. A best-selling notebook computer model was displayed as a utilitarian product.²¹ Nine categories of mobile shopping information were grouped into four areas of interest (AOIs), as summarized in Table 1. Data from the eye-tracking experiment were garnered from the AOIs and analyzed to answer the two RQs. A smartphone with a 5.2″ mobile screen at 2,012 × 1,920 resolution was used for the eye-tracking experiments. The smartphone was administered by a mobile eye tracker, Tobii X2-30, as shown in Figure 2. The eye-tracking equipment uses a 30 Hz sampling rate installed in a mounting solution for mobile devices.²²

FIG. 1.

Mobile shopping screen.

FIG. 2.

Mobile eye-tracking experiment.

Table 1.

Areas of Interest of Mobile Shopping Information

Areas of interest (AOIs)	Mobile shopping information
Product information	Product image
	Product description
	Product price
Consumer opinion	Product review
Consumer opinion	Product FAQs
Promotion	Special offers (e.g., free gifts such as computer mouse)
Supplementary information	Seller information
Supplementary information	Shipping information
	Return/exchange information

Shopping motivation

Shopping motivations can be categorized into two types: goal oriented or recreational.¹⁷ Goal-oriented shopping motivation is basically utilitarian oriented and transaction oriented, during which people tend to purchase what they want for the sake of convenience and efficiency. From the perspective of goal-oriented shopping motivation, shopping activity is regarded as a task or work. Therefore, not surprisingly, consumers with goal-oriented motivation evaluate the success of their shopping efforts according to the measurements of efficiency and achievement. In contrast, those consumers with recreational shopping motivation emphasize their feelings and psychological perceptions.²³ They consider shopping as a hedonic activity that serves an entertainment purpose. In the course of our experiments, the two types of shopping motivation were manipulated as two shopping scenarios that participants are supposed to follow.

Procedure

In the eye-tracking experiment, participants were given an overall explanation of the experiment and asked to answer a demographic questionnaire. Then they were randomly divided into two groups of 21 participants. Each group was given a shopping scenario to induce one of the two shopping motivations: goal oriented or recreational. The participants were asked to answer a questionnaire, an adapted version of the Revised Personal Involvement Inventory,²⁴ by checking their product involvement level about notebook computers. The questionnaire was answered by using a seven-point Likert scale. Results showed that goal-oriented participants had higher levels of product involvement than recreational participants, with a statistical significance (goal oriented: M = 4.43; recreational: M = 2.87, t = 6.42, p < 0.01).

After calibrating to fit the eye-tracking equipment to each participant, he or she was supposed to observe, for 100 seconds, the shopping information about the notebook computer model that was displayed on the mobile shopping screen. The participants' visual behaviors and finger touches on the mobile shopping screen were recorded by the mobile eye tracker. Visual behaviors measured include the eye-fixation and eye-movement paths over the four AOIs. Total fixation duration (TFD) was calculated by the Tobii studio software. Finally, participants were asked to answer a questionnaire about their purchase intention toward the displayed notebook computer. The whole experiment took ∼20 minutes.

Measurements

To compute the participants' visual attention metrics, TFD was calculated as the sum of duration for all fixations within an AOI. Therefore, a high TFD indicates strong visual attention to the AOI.²⁵ The measurement unit was the mean number of seconds. It is normal for participants to exercise finger touches such as zooming in and swiping on the mobile shopping screen. For example, zooming behavior occurs when users want to take a closer look at a specific part of the screen. Meanwhile, swiping behavior ensues when they want to move to the target information. Participants' finger touch behaviors were recorded by the eye tracker and analyzed to obtain participants' zooming and swiping.²⁶ Participants' purchase intention toward the displayed notebook computer was measured by three items adapted from relevant literature.²⁷

Results

Results for RQ1

To answer RQ1, the impact of shopping motivation on visual behavior had to be tested. For this purpose, a t test was conducted for each of the four AOIs on the TFD differences between goal-oriented participants and recreational shopping participants. As shown in Table 2, t test results were statistically significant only in the product information AOI (t = 2.09, p < 0.05). For the product information AOI, goal-oriented participants paid higher visual attention than the recreational participants (goal oriented: M = 46.75; recreational: M = 34.32). To compare the two shopping motivation groups in line with the nine mobile shopping information areas (refer to Table 1), TFD results of the two shopping motivation groups are paired with each other for each information area, as depicted in Figure 3. One peculiar fact was that, compared with recreational participants, goal-oriented participants paid higher visual attention to most of the shopping information areas, except the product review area (goal oriented: M = 16.73; recreational: M = 18.93). Finally, in terms of finger touch activities such as zooming and swiping, goal-oriented participants showed considerably more active usage of zooming and swiping behaviors than recreational participants. Figure 4 depicts this result quite clearly.

FIG. 3.

Total fixation duration results in nine shopping information areas.

FIG. 4.

Zooming and swiping behavior in a mobile shopping context.

Table 2.

Total Fixation Duration Results in Areas of Interest Between Goal-Oriented and Recreational Participants

	Mean
Visual attention (TFD)	Goal oriented	Recreational	t
Product information	46.75	34.32	2.09^*
Consumer opinion	18.98	19.35	−0.06
Promotion	1.76	1.74	0.01
Supplementary information	4.40	3.30	0.95

p < 0.05, ^**p < 0.01.

TFD, total fixation duration.

Results for RQ2

To answer RQ2, multiple regression analysis was applied to the two shopping motivation groups, wherein the TFDs in four AOIs were used as independent variables, and purchase intention was set as a dependent variable. As shown Table 3, goal-oriented mobile shoppers' purchase intention was positively influenced by their visual attentions to the two AOIs of product information and consumer opinions (β = 0.494 for product information, β = 0.550 for consumer opinions). In contrast, recreational mobile shoppers' purchase intention was significantly affected by their visual attention to the two AOIs of promotion and supplementary information (β = 0.733 for promotion, β = −0.597 for supplementary information). In other words, the recreational shoppers' TFD to promotion AOI had a positive effect on their purchase intention, whereas their TFD to supplementary information AOI was negatively linked with their purchase intention.

Table 3.

Effects of Visual Attention on Purchase Intention for Displayed Product

	Goal-oriented participants (R ² = 0.430, F = 3.023 ^* )		Recreational participants (R ² = 0.430, F = 3.021 ^* )
AOIs	β	p Value	β	p Value
Product information	0.494	0.039^*	−0.329	0.129
Consumer opinion	0.550	0.025^*	−0.415	0.060
Promotion	0.264	0.267	0.733	0.012^*
Supplementary information	−0.294	0.231	−0.597	0.034^*

p < 0.05, ^**p < 0.01.

AOIs, areas of interest.

Discussion and Conclusion

Through the eye-tracking experiments, the two RQs were addressed empirically. In a nutshell, our results revealed that visual behaviors measured in TFD show significant differences between goal-oriented motivation shoppers and recreational motivation shoppers. Besides, their purchase intention is influenced by visual attention to different AOIs. Let us elaborate on the implications of these results. First, in comparison with recreational shoppers, goal-oriented shoppers' TFD is stronger in most of nine mobile shopping information areas, except the product review. For details, refer to Figure 3. Besides, goal-oriented shoppers' zooming and swiping activities (measured in counts) were significantly greater than that for recreational shoppers (refer to Fig. 4). Second, the two shopping motivation groups' purchase intention showed different responses to the TFDs of the four AOIs. The goal-oriented group's purchase intention was positively influenced by their TFDs to the two AOIs of product information and consumer opinion. In comparison, for the recreational motivation group, their TFDs to the two AOIs of promotion and supplementary information had a significant impact on their purchase intention.

Our empirical results from the eye-tracking experiments can be interpreted from the perspective of mindset theory. According to this theory, there are two types of mindsets: implemental and experiential. Task-oriented shoppers are more likely to shop in an implemental mindset, in which their information processing is tuned toward realizing their shopping. They tend to find shopping information more actively in a short time to minimize shopping risk and maximize successful purchases.¹⁸ In contrast, recreational shoppers are more likely to shop with a deliberative mindset, in which their information processing is tuned toward thinking about wishes and desires, and they are evaluating whether offers are interesting to them. They have experiential requirements to seek enjoyment during shopping.¹⁸

The mindset theory can be logically applied to our study. Goal-oriented mobile shoppers seem to possess an implemental mindset by examining the shopping information presented on a mobile screen more actively by zooming and swiping to achieve their shopping goal successfully. Such behaviors are seemingly caused by the generic fact that consumers in an online shopping context cannot touch or feel the product and, therefore, they want to assess and perceive the product quality by presented product information and consumers' review.²⁸ Goal-oriented mobile shoppers' purchase intention was significantly influenced by their visual attention on the two AOIs such as product information and consumer opinion. In this way, they recognize essential product features and check consumer opinions to make successful purchase decisions.

In contrast, recreational mobile shoppers seemingly rely on a deliberative mindset with their lower visual attention to the shopping information areas than goal-oriented mobile shoppers. Exceptionally, they pay active visual attention to the product review area (see Fig. 3). Goldsmith and Horowitz²⁹ suggested that consumers recognize that reading experiential product reviews by other customers is enjoyable and a source of fun. Therefore, in our mobile shopping experiment, recreational mobile shoppers paid more active visual attention to the product review than goal-oriented shoppers, considering that it is an experiential stimulus fulfilling their desire for enjoyment. Recreational shoppers with experiential mindset preferred retailer claims that highlighted stimulation during shopping.³⁰ Marketing coupons usually lead to eliciting more spending when consumers are in a deliberative mindset than when they are in an implemental mindset.³¹ Recreational shoppers' visual attention on the promotion AOI positively influenced their purchase intention. However, their visual attention to the supplementary information AOI led to a negative purchase intention. As is often the case, the supplementary information AOI includes various types of utilitarian information about sellers, shipping, return/exchange information, etc. Especially, in the mobile shopping contexts, such information is conveyed in a rather small mobile screen, causing a sense of hard-to-interpretation to shoppers and the increased cognitive load.³² Therefore, the situation like this may negatively influence recreational shoppers who prefer hedonic sources when they are in a deliberative mindset.

One of the limitations of this study is that the participants in the experiment are in their 20s, and most of them are active mobile shopping users. In that sense, caution is needed to generalize the empirical results of this study. In addition, for the sake of research purposes, we organized experiments so that participants may feel two types of shopping motivations. However, in real situations, the intensity level of the mobile shopping motivation is likely to vary depending on the situations that mobile shoppers face. A future study is needed that includes the participants of more versatile age groups. Besides, hedonic products need to be included as target products to expand the practical implication of the empirical results. Another future research direction can start from the extension of the mindset theory, which was successfully applied to this study. Since mindset theory is about recognizing the role of two types of mindsets—deliberative mindset and implemental mindset—in the process of various types of decision-making, future research can extend the mindset theory to fit into more sophisticated decision-making problems.

This study did successfully address unexplored RQs in the literature. Also, it has been proven that the eye-tracking method is very useful in seeking to answer innovative RQs about mobile shopping issues. We hope that our results will serve as a catalyst to prompt similar studies that increase our understanding of consumers' mobile shopping behaviors.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

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