Assessing the Influence of Product Page Design on Purchasing Influence of Products in Online Marketplaces

Assessing the Influence of Product Page Design on Purchasing Influence of Products in Online Marketplaces

Alphas Kakuko¹, Paul Oyile², Patrick Owoche³, Richard Ronoh⁴

^1,2,3 Department of Information Technology, Kibabii University, Kenya

⁴ Department of Computer Science, Kibabii University, Kenya

DOI: https://doi.org/10.51584/IJRIAS.2024.909056

Received: 04 September 2024; Revised: 19 September 2024; Accepted: 23 September 2024; Published: 22 October 2024

ABSTRACT

In the era of e-commerce, online marketplaces have become indispensable platforms for businesses to reach a global audience. This study investigates the impact of product page design on purchasing influence within online marketplaces, focusing on the relationship between key design elements and consumer behavior. The research addresses a gap in understanding how layout, visual appeal, and the strategic placement of elements affect purchase intent and behavior. Employing a quantitative research design, the study sampled 186 online market consumers within Nairobi County in Kenya, across six major e-commerce platforms, including Amazon, Jumia, and Alibaba. Data were collected through structured questionnaires and analyzed using descriptive and inferential statistics. Key findings indicate that visually appealing designs, clear product information, and well-positioned call-to-action buttons significantly enhance user engagement and purchasing decisions. The study concludes with recommendations for optimizing online product pages to increase sales and reduce cart abandonment rates. Ethical considerations were adhered to throughout the research, ensuring participant confidentiality and data integrity. This research highlights the need for e-commerce platforms to prioritize user-centric design strategies that align with consumer preferences, driving better engagement and conversion rates.

Key words: Product page design, Purchasing influence, Consumer behavior, E-commerce platforms, User engagement

INTRODUCTION

In the era of e-commerce, online marketplaces have become integral to consumer shopping habits. The success of these platforms hinges on their ability to effectively influence purchasing decisions. A crucial factor in this regard is the design of product pages, which serve as the digital storefront for products. The design of these pages can significantly impact how consumers perceive and interact with products, ultimately influencing their likelihood to make a purchase (Urne & Aggrawal, 2020).

Previous research has explored the influence of individual product page design elements on consumer behavior. For instance, studies have shown that visually appealing product images can enhance product attractiveness and increase purchase intent (Trudel, 2019). Similarly, clear and concise product descriptions have been found to improve consumer understanding and reduce perceived risk (Bairrada, Coelho, & Lizanets, 2019). However, there is a lack of comprehensive research that examines the interplay of multiple design elements and their combined impact on consumer purchasing decisions.

This study aims to bridge this gap by investigating the influence of product page design on consumer purchasing behavior in online marketplaces. Specifically, the study examines the impact of positioning key elements on a product’s page and conversion rate optimization on consumer perceptions of purchase intent, actual purchase behavior, and shopping cart abandonment rate. By understanding the complex relationship between product page design and consumer behavior, businesses can optimize their online storefronts to increase sales and improve customer satisfaction.

LITERATURE REVIEW

Understanding the intricate relationship between website design, layout, and user behavior is crucial for optimizing user engagement within online marketplaces. This section explores existing research on the design and layout of product pages, delving into the impact of visual hierarchy, the positioning of key elements, and the principles of Conversion Rate Optimization (CRO) on user behavior and decision-making.

Product Page Design and User Experience

Product page design and user experience are vital aspects that influence consumer engagement in online platforms. Research by Brown and Jones (2018) underscores the significance of visual hierarchy, where the arrangement of page elements guides user interaction and exploration. A well-structured hierarchy ensures that essential components such as product categories and promotions capture user attention and facilitate intuitive navigation. This concept is further supported by Kim and Moon (1998), who emphasize that visually appealing designs positively influence user perceptions and attitudes, contributing to an overall positive user experience.

The strategic placement of call-to-action buttons is also a key determinant of user behavior. Brown and Jones (2018) highlight how properly positioned elements such as “Add to Cart” or “Buy Now” buttons can optimize user engagement and guide actions. Similarly, Fogg et al. (2001) explore the persuasive power of interface design, indicating that the placement of these buttons enhances user satisfaction and decision-making. This is closely tied to the broader information framework of the page, as highlighted by Nielsen (2000), which argues that a clear, concise information structure reduces cognitive load, making it easier for users to locate relevant details efficiently.

Adding to this understanding, Liu and Park (2015) demonstrate the role of visual aesthetics in fostering positive user attitudes and engagement. These interconnected elements of visual hierarchy, button placement, and clear information flow collectively shape how users experience product pages. The combined insights from these studies provide a holistic understanding of how design elements influence engagement, forming the foundation of effective product page design.

Positioning of Key Elements

The strategic positioning of key elements on product pages plays a crucial role in shaping user decisions and behavior. Huang, Zhang, and Ma (2021) examined how placing high-quality images and product descriptions above the fold enhances user engagement by providing immediate access to essential information. This initial interaction helps establish a positive user impression, which is critical in influencing purchasing behavior.

The importance of visual design elements, such as product images and page layout, is further emphasized by Sundar (2000), who explored how these factors contribute to shaping user perceptions. The ease with which users can access pricing information and customer reviews also plays a significant role in fostering trust and facilitating decision-making. Research by Kim and Moon (1998) supports this by showing that strategically placed pricing details and reviews help establish credibility and trust, positively impacting purchasing decisions.

Liu and Park (2015) also contribute to this discourse by exploring how the placement of user-generated content, particularly customer reviews, affects consumer decision-making. Their findings highlight the interconnectedness of element positioning, user engagement, and trust. By integrating the findings of these studies, businesses can optimize their website layouts to enhance user experiences and improve purchasing outcomes.

Conversion Rate Optimization (CRO)

Conversion Rate Optimization (CRO) is a strategy that focuses on improving website performance to increase the likelihood of users completing desired actions, such as making purchases. At its core, CRO is guided by principles of testing and personalization. Smith and Davis (2019) emphasize the value of A/B testing, which compares different versions of a webpage to determine which design or layout yields better user engagement and conversions. This data-driven approach allows businesses to make informed decisions, refining their online presence to align with user preferences.

Personalized user experiences are another critical component of CRO. By analyzing user data, businesses can offer tailored recommendations and content, enhancing overall user satisfaction and increasing the likelihood of conversions. Smith and Davis (2019) suggest that this personalization, combined with intuitive navigation frameworks, ensures a smoother user journey and reduces friction, positively influencing conversion rates.

Williams and Jackson (2020) expand on these ideas by exploring the role of persuasive design elements in CRO. Their research underscores the effectiveness of compelling visuals and persuasive copy in guiding user behavior toward desired actions. In addition, Chen et al. (2017) explores how social proof, through elements such as customer testimonials and ratings, builds trust and credibility, further enhancing conversions.

In summary, the principles of CRO, as outlined by Smith and Davis (2019), provide a comprehensive approach to enhancing user interaction and conversion rates. Integrating insights from Williams and Jackson (2020) and Chen et al. (2017), businesses can implement a holistic CRO strategy that leverages testing, personalization, and social proof to optimize their websites and drive user engagement.

METHODOLOGY

This section outlines the methodology the researcher utilized to achieve the study’s objective. It details the research process, encompassing the research design, target population, sampling frame, methods of data collection, validation and reliability of the research instrument, and ethical considerations.

Research Design

The study employed a quantitative research design to examine the influence of product page design on consumer purchasing decisions in online marketplaces. This approach was selected because it allows for the collection of numerical data, facilitating the measurement of key variables such as purchase intent, actual purchasing behavior, and shopping cart abandonment. By utilizing statistical analysis, the study was able to identify relationships and patterns within the data, providing an objective and reliable foundation for the investigation. The structured nature of quantitative research also made it suitable for testing hypotheses related to the impact of product page design elements on consumer behavior.

Additionally, the quantitative design enabled the study to handle a large sample size across various online marketplaces in Nairobi County, Kenya, ensuring the results were generalizable. The selected platforms represented a diverse array of product categories, industries, and consumer demographics, allowing for a comprehensive view of user behaviors in the broader online marketplace landscape. This design not only facilitated the comparison of different platforms but also supported the identification of key factors that contribute to effective product page design and its impact on consumer purchasing decisions.

Target Population

The target population for the study encompassed a diverse group of people actively engaging within online market places in Nairobi, Kenya, as well as online market place applications used in Kenya. These included consumers of varying demographics, such as age, gender, income level, and educational background, ensuring a comprehensive understanding of user behavior across different segments. The target population comprised of consumers that actively participated in transactions, reviews, and other engagement activities within selected online market places as well as the selected applications they interact with, within Nairobi county, Kenya.

Sampling Procedure

The sampling procedure for this study followed a structured approach aimed at selecting a representative sample of active users of online marketplaces. A combination of purposive sampling, stratified sampling, and simple random sampling was used to ensure that the study accurately captured the target population. Purposive sampling was employed to focus on online marketplace users actively engaged in transactions, reviews, and interactions within the selected platforms. This ensured that only individuals who significantly contribute to consumer decisions were included. Users who were inactive or not engaged in the marketplace activities were excluded from the sample. The stratified sampling approach was utilized to divide the online market users into distinct groups based on demographic and platform usage, ensuring diversity in the representation of different types of consumers across the selected online marketplaces. Simple random sampling was then applied within each stratum to randomly select participants, reducing bias and enhancing the representativeness of the sample.

To determine the sample size, Cochran’s formula was applied, which is appropriate for large or unknown target populations. This method involved using a 95% confidence level (Z-score of 1.96), an estimated proportion of the target population (p) set at the worst-case value of 50% (0.5), and a margin of error (E) set at 7% (0.07). The calculation resulted in a sample size of 196 active online marketplace users.

n=Z²⋅p⋅q/E²

n= ((1.96)²*(0.5) *(1-0.5))/ (0.07)²

= (3.8416*0.25)/0.0049

=0.9604/0.0049

=196

For the selection of online marketplaces, six popular platforms—Jumia, Kilimall, Jiji Kenya, Masoko, Alibaba, and Amazon—were purposively selected based on their widespread usage in Kenya. This approach ensured that the sample accurately reflected the diversity of online marketplaces and user engagement across the platforms. Table 3.1 provides a summary of the sample population, detailing the categories of respondents, target population, sample size, and degree of accuracy observed in the study.

Table 3.1: Sample Population

Data Collection Instruments

In this study, a structured questionnaire was the main tool for gathering data on the influence of product page design on consumer purchasing behavior in online marketplaces. The questionnaire included both closed-ended and open-ended questions, allowing for the collection of quantitative and qualitative data. Sections of the questionnaire were strategically organized to cover visual appeal, product descriptions, and layout, and their effects on purchasing intent, actual behavior, and shopping cart abandonment. The closed-ended questions, primarily using Likert scales, provided numerical data for statistical analysis, while open-ended questions captured participants’ deeper insights and personal experiences.

The questionnaire was distributed through online platforms, targeting active online marketplace users. Online distribution enabled efficient access to participants engaged in e-commerce. This approach ensured comprehensive data collection, offering a balanced view of how different product page elements impact consumer decisions. The responses were then systematically organized and analyzed to draw meaningful conclusions about the relationship between product page design and purchasing behavior.

Validity of Research Instruments

To ensure validity, the study employed content validity, using a panel of experts familiar with online marketplaces to assess the relevance and representativeness of the research tools’ elements (Burton & Mazerolle, 2011).

Content validity was assessed by determining the degree to which data collected through the instruments represented specific indicators or content within the realm of online market places. Experts in online marketplace dynamics evaluated whether the tools accurately captured the relevant concepts. Three experts rated the content validity of the tools on a scale of one to ten (1–10), and the results were tabulated for analysis. This assessment aimed to establish the credibility, accuracy, relevance, and breadth of knowledge regarding the online market place domain (Burton & Mazerolle, 2011). Table 3.2 shows the validity results of the research instruments.

Table 3.2: Validity Results of Research Instruments

Reliability of Research Instruments

To ensure the reliability of the instruments used in this study within the context of online marketplaces, a pilot study was conducted with six participants—three representative users (customers) and three individuals involved in online marketplace management, selected randomly from a sampled group of online businesses. The pilot study aimed to eliminate any ambiguity in questioning and assess the reliability of the instruments. Results were tabulated, and scores computed for correlation. Following the criteria of Taber (2018), the tool was to be considered reliable if the Cronbach’s Coefficient value was above 0.70, although lower thresholds may be considered based on relevant literature. This approach involved correlating scores obtained in one item with scores from other items within the same instrument, ensuring consistency in measuring the concept of interest (Mugenda & Mugenda, 2012). Table 3.3 shows the results of reliability test conducted.

Table 3.3: Reliability Test Results

Data Analysis and Presentation

The data collected in this study underwent a comprehensive analysis employing a diverse approach to derive meaningful insights into product page design and purchasing influence within online marketplaces. The initial phase of analysis involved descriptive statistics, where key product page design metrics, such as positioning of key elements on a product page and conversion rate optimization, were quantified. This quantitative snapshot provided a clear and concise overview of the central tendencies and variations within the dataset, facilitating a deeper understanding of product page design and purchasing influence. Correlation analysis was applied to discern relationships between product page design metrics, and purchasing influence. By exploring the degree and direction of correlations, the study aimed to unveil potential connections. This phase of analysis illuminated the interplay between different variables, contributing to a more in-depth comprehension of the factors shaping user engagement and decision-making processes. Factor Analysis was applied to extract various components per study variable that could then inform the constructs and the sub-constructs of the developed sub-framework.

Ethical Consideration

To commence the research process, the researcher began by securing an approval letter from the School of Graduate Studies (SGS) at Kibabii University. Subsequently, the researcher obtained a research permit from the National Commission for Science, Technology, and Innovation (NACOSTI) and thereafter an approval from Nairobi County Commissioner before proceeding with the data collection phase. The data collection procedure commenced with the issuance of a signed introductory letter, introducing the researcher and providing a concise explanation of the study’s purpose or objectives to all identified respondents and local authorities involved. Prior to conducting any focus group discussions, the researcher actively sought the informed consent of participants, providing a clear explanation of the discussion’s purpose and assuring them of the confidentiality of the information they contributed. Additionally, the researcher duly acknowledged all sources and authors of information utilized in developing the study, ensuring proper citation and referencing. A plagiarism test was conducted to uphold academic integrity and originality.

FINDINGS OF THE STUDY

This chapter presents a comprehensive analysis of empirical data collected through research methodologies outlined in Chapter Three, Section 3.4. The investigation encompasses an evaluation of instrument response rate, product page design within online marketplaces, and its influence on purchasing decisions within these digital environments.

Response Rate

Response rates were determined by examining the proportion of completed questionnaires returned from the total sample. Of the 196 questionnaires distributed to online marketplace users in Nairobi to explore user-generated content, user behavior, product page design, and purchasing influence, 186 were fully completed and returned for analysis, as presented in Table 4.1.

Table 4.1: Online Market Place Users Response Rate

This yielded a response rate of 94.90%. According to established benchmarks, a response rate of 50% or higher is generally considered adequate for data analysis and subsequent generalization (Mugenda, 2012). Babbie (2004) further elaborates on this, categorizing response rates of 50% as acceptable for analysis and publication, 60% as good, and 70% as excellent. Given these standards, the achieved response rate of 94.90% was considered sufficiently robust to support the research objectives and draw meaningful conclusions about the study population. The remaining 5.10% of non-respondents likely attributed their non-participation to factors such as time constraints or a lack of willingness to engage in the survey.

Product Page Design in Online Marketplaces

This study looked at the influence of product page design on user purchasing influence. This section presents the descriptive statistics related to the influence of product page design (PPD) on consumer purchasing decisions. The data were collected through a questionnaire administered to a sample of 186 respondents, who rated various statements on product page design on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree). The statements addressed key aspects of product page design, including the positioning of key elements and conversion rate optimization (CRO). Table 4.2 summarizes the responses for each statement.

Table 4.2: Descriptive Statistics on Perception of Respondents on Product Page Design in Online Market Places

Table 4.2 presents the descriptive statistics related to respondents’ perceptions of various elements of product page design in online marketplaces. The Table breaks down the responses to specific statements such as the positioning of key elements on a product’s page and conversion rate optimization (CRO).

Positioning of Key Elements

When considering the ease of finding product images on the page, 4.3% of respondents strongly disagreed, and 7.0% somewhat disagreed. A significant 29.0% were neutral, while 29.0% somewhat agreed, and 30.6% strongly agreed. This indicates that a substantial majority (59.6%) found it easy to locate product images, with a mean rating suggesting a positive overall perception.

Regarding the clarity and accessibility of the product description, 5.9% strongly disagreed, and 8.1% somewhat disagreed. Meanwhile, 21.5% were neutral, 36.6% somewhat agreed, and 28.0% strongly agreed. This distribution reflects a positive view among respondents (64.6%) about the clarity and ease of locating the product description.

The prominence of the product’s price was rated highly, with 5.9% strongly disagreeing and 5.4% somewhat disagreeing. A smaller proportion, 16.7%, were neutral, whereas 26.9% somewhat agreed, and a significant 45.2% strongly agreed. This indicates a strong consensus (72.1%) that the product’s price is prominently displayed, with the highest mean rating among the elements considered.

For the availability of important information such as size, color, or material options, 5.9% strongly disagreed, and 6.5% somewhat disagreed. A notable 24.7% remained neutral, while 32.3% somewhat agreed, and 30.6% strongly agreed. The data reveal that a majority (62.9%) found such information readily available, reflecting a positive perception.

The visibility and ease of clicking the call-to-action button (e.g., “Add to Cart”) were well-rated, with 8.0% strongly disagreeing and 7.0% somewhat disagreeing. A significant 20.4% were neutral, while 29.0% somewhat agreed, and 39.2% strongly agreed. The data suggest a strong agreement (68.2%) on the visibility and functionality of the call-to-action button.

Conversion Rate Optimization (CRO)

Regarding the visual appeal of the product page and its ability to encourage exploration, 8.6% of respondents strongly disagreed, and 6.5% somewhat disagreed. A notable 25.3% were neutral, while 30.6% somewhat agreed, and 29.0% strongly agreed. This indicates that a majority (59.6%) found the product page visually appealing, encouraging further exploration.

The page’s ability to highlight product benefits and address potential customer concerns received mixed responses. About 6.5% strongly disagreed, and 10.8% somewhat disagreed. A significant 31.7% remained neutral, while 28.5% somewhat agreed, and 22.6% strongly agreed. This shows that a considerable portion (51.1%) perceive the page positively in highlighting benefits and addressing concerns.

The presence of customer reviews or testimonials that build trust in the product was also rated variably. About 6.5% strongly disagreed, and 10.2% somewhat disagreed. A notable 22.6% were neutral, while 37.1% somewhat agreed, and 23.7% strongly agreed. This suggests a majority (60.8%) value the trust-building aspect of customer reviews and testimonials.

Clear incentives or promotions to encourage purchase received lower ratings, with 10.8% strongly disagreeing, and 10.2% somewhat disagreeing. A notable 26.9% were neutral, while 31.7% somewhat agreed, and 20.4% strongly agreed. This reflects a moderate agreement (52.1%) on the effectiveness of incentives and promotions.

Lastly, the smooth navigation on the product page, making it easy to add the product to the cart and checkout, was rated positively. About 9.1% strongly disagreed, and 3.8% somewhat disagreed. A notable 17.7% were neutral, while 32.3% somewhat agreed, and 37.1% strongly agreed. This indicates a strong agreement (69.4%) on the ease of navigation and checkout process.

These statistics highlight the significant role of product page design elements, such as the positioning of key elements and conversion rate optimization, in shaping consumer perceptions and purchasing decisions in online marketplaces. Respondents generally viewed these elements positively, emphasizing their importance in enhancing the online shopping experience.

Purchasing Influence in Online Market Place

This section presents the descriptive statistics on respondents’ perceptions of various purchasing influences in online marketplaces. The data collected covered aspects such as purchase intent, actual purchase behavior, and shopping cart abandonment rate. Respondents rated statements aligned to these aspects on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree). Table 4.3 summarizes the responses.

Table 4.3: Descriptive Statistics on Perception of Respondents on Purchasing Influence in Online Marketplaces

Purchase Intent of Users Within an Online Market Place

When asked if the product page made them seriously consider purchasing the product, 7.5% of respondents strongly disagreed, and 11.8% somewhat disagreed. A significant 37.1% were neutral, while 25.8% somewhat agreed, and 17.7% strongly agreed. This indicates a moderate level of agreement (43.5%) that the product page effectively influences purchase consideration.

Regarding feeling more inclined to buy the product after browsing the page, 10.2% of respondents strongly disagreed, and 14.0% somewhat disagreed. About 33.9% were neutral, while 29.6% somewhat agreed, and 12.4% strongly agreed. This reflects a moderate inclination (42.0%) towards purchasing the product after viewing the page.

The statement that the information on the product page increased interest in purchasing the product received positive feedback. About 7.5% of respondents strongly disagreed, and 7.0% somewhat disagreed. A significant 36.0% were neutral, while 28.5% somewhat agreed, and 21.0% strongly agreed. This shows that 49.5% of respondents felt an increased interest in purchasing the product due to the information provided on the page.

Actual Purchase Behavior Within Online Market Places

When evaluating whether the product page effectively motivates users to complete a purchase, 7.5% of respondents strongly disagreed, and 10.8% somewhat disagreed. A notable 31.7% were neutral, while another 31.7% somewhat agreed, and 18.3% strongly agreed. This suggests that 50.0% of respondents felt motivated to complete a purchase based on the product page design.

The design’s ability to encourage users to add the product to their cart was also rated. About 5.9% of respondents strongly disagreed, and 15.1% somewhat disagreed. A significant 30.1% were neutral, while 28.5% somewhat agreed, and 20.4% strongly agreed. This indicates that 48.9% of respondents felt the page design encouraged them to add the product to their cart.

Regarding the statement that the product page helps users understand why they would choose to buy the product, 7.5% of respondents strongly disagreed, and 10.2% somewhat disagreed. A notable 26.3% were neutral, while 30.1% somewhat agreed, and 25.8% strongly agreed. This shows that 55.9% of respondents found the product page persuasive in understanding why to buy the product.

Shopping Cart Abandonment Rate

The product page design’s effectiveness in minimizing distractions that might lead users to abandon their carts was evaluated. About 11.3% of respondents strongly disagreed, and 19.9% somewhat disagreed. A significant 33.9% were neutral, while 15.1% somewhat agreed, and 19.9% strongly agreed. This reflects a lower agreement (35.0%) that the design minimizes cart abandonment distractions.

Regarding the clarity and comprehensiveness of the information on the page, reducing reasons for cart abandonment, 9.1% of respondents strongly disagreed, and 17.7% somewhat disagreed. A notable 35.5% were neutral, while 19.9% somewhat agreed, and 17.7% strongly agreed. This indicates a moderate level of agreement (37.6%) that clear and comprehensive information reduces cart abandonment.

Finally, the statement that the product page seems unlikely to cause users to abandon their carts before checkout received mixed responses. About 11.3% of respondents strongly disagreed, and 19.4% somewhat disagreed. A significant 33.3% were neutral, while 18.3% somewhat agreed, and 17.7% strongly agreed. This shows a moderate agreement (36.0%) that the product page design does not contribute to cart abandonment.

These statistics highlight the significant role of product page design in influencing purchase intent, actual purchase behavior, and shopping cart abandonment rates. While respondents generally viewed these elements positively, the data suggest areas for improvement to further enhance the online shopping experience and reduce cart abandonment.

Effect of Product Page Design on Purchasing Influence in Online Marketplaces

This section aimed to establish the influence of Product Page Design (PPD) on purchasing influence within online marketplaces. The analysis focused on key PPD components, including the positioning of key elements, and conversion rate optimization. These elements were examined in relation to their impact on various dimensions of purchasing influence, such as purchase intent, actual purchase behavior, and shopping cart abandonment rates.

Other than the descriptive statistics conducted, it was necessary to get an in-depth insight on the relationships between product page design and consumer purchasing influence in online marketplaces. To achieve this, correlation analysis was deemed appropriate. However, before performing correlation analysis, it was important to ensure that certain assumptions and conditions were met to validate the results. Test for Normality was conducted. Table 4.4 shows the results for Kolmogorov-Smirnov Test (K-S Test) and Shapiro-Wilk Test for Normality.

Table 4.4: Tests of Normality

Table 4.4 presents the results of the Kolmogorov-Smirnov and Shapiro-Wilk tests for normality on the variables Purchasing Influence and Product Page Design. These tests were conducted to assess whether the distribution of these variables deviates significantly from a normal distribution.

The Kolmogorov-Smirnov test and the Shapiro-Wilk test yielded consistent results for all three variables. The significance values (Sig.) for both tests are less than the conventional alpha level of 0.05, indicating that the null hypothesis of normality can be rejected for each variable. In other words, there is sufficient evidence to conclude that the distributions of Purchasing Influence and Product Page Design are significantly different from a normal distribution. These findings suggest that parametric statistical tests, which assume normality, may not be appropriate for analyzing these variables and non-parametric alternatives should be considered.

Given the test of normality results, it was determined that parametric statistical tests, which rely on the assumption of normality, were not appropriate for further analysis of the variables. Consequently, non-parametric alternatives were considered. To assess the strength and direction of the relationship between Product Page Design and Purchasing Influence, Spearman’s Rank Correlation was deemed appropriate. The findings were as presented in Table 4.5.

Table 4.5: Spearman’s Rank Correlation Product Page Design and Purchasing Influence

Table 4.5 presents the results of the Spearman’s rank correlation analysis examining the relationship between Product Page Design and Purchasing Influence. The analysis involved a sample of 186 participants. The correlation coefficient (rho) between these two variables is .819, indicating a strong positive relationship. This suggests that as Product Page Design quality improves, Purchasing Influence tends to increase as well. The significance level (p-value) for this correlation is .000, which is less than the conventional alpha level of .01. Therefore, the relationship between Product Page Design and Purchasing Influence is statistically significant at the .01 level, implying a very strong likelihood that the observed correlation is not due to chance. These findings support the hypothesis that Product Page Design has a substantial positive impact on Purchasing Influence.

CONCLUSION AND RECOMMENDATION

The results highlighted a significant positive relationship between product page design and purchasing influence. Factors like layout, visual appeal, ease of navigation, and strategic placement of key elements (such as call-to-action buttons and product information) were crucial in influencing consumer decisions. Well-designed product pages were found to enhance user engagement, reduce bounce rates, and increase the likelihood of completing a purchase.

From this conclusion, the study recommends focusing on user-friendly layouts, clear product descriptions, high-quality images, and easy navigation. It also recommends testing different designs to find the most effective layout for conversion.

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