Product Pages Research Articles

Dynamic Price Monitoring in E-Commerce: Leveraging Web Scraping, Data Analysis, and Email Automation for Dynamic Pricing Insights

This paper focuses on the development of a web application that leverages web scraping, data storage, and email automation technologies to track real-time price changes for specific products on e-commerce platforms. Built using Next.js for the frontend, MongoDB as the database, and Nodemailer for email notifications, the system aims to provide users with a comprehensive and user-friendly interface to monitor price fluctuations. By scraping data from product pages, the application gathers key pricing metrics, including the average, lowest, highest, and current prices, and presents this information visually to help users make informed purchasing decisions. By utilizing the combination of web scraping and real-time data analysis, this project provides a dynamic solution for both consumers and businesses, offering valuable insights into price changes and trends in the competitive e-commerce landscape.

An Empirical Examination of BuyBox Assignments in Online Grocery Retail

ABSTRACTIn Amazon's marketplaces across the globe, multiple sellers sell the same product, leading Amazon to introduce BuyBox. This box‐like feature, located on the top‐right corner of product pages, prominently displays a single seller at a given time. Using a choice model and a panel dataset of over 290,000 unique grocery products from five countries, our study investigates the key factors that influence BuyBox assignments. We found that winning the BuyBox is primarily determined by competitive pricing—being the lowest‐price seller for a 180‐day period significantly improves the chances of a BuyBox assignment. Furthermore, maintaining low current product prices, low sales ranks, and minimal out‐of‐stock percentages are crucial in becoming a BuyBox seller. These findings affect Amazon and its extensive network of over 2 million third‐party sellers, who navigate the increasingly competitive and dynamic E‐commerce landscape.

Quitting smoking with…smoke? Unauthorized claims used by herbal cigarette manufacturers.

Herbal cigarettes are made with non-tobacco plant materials (e.g., tea leaves, hemp), are typically sold pre-rolled in packs and with filters, and are combusted and smoked like tobacco cigarettes. Herbal cigarette manufacturers have a history of making misleading health claims and at least one company has previously settled with the US Federal Trade Commission over deceptive advertising. This study examined current claims and product characteristics of herbal cigarettes sold by a popular online retailer. We searched Amazon.com for "herbal cigarettes" and "hemp cigarettes" and identified all herbal cigarette products sold on the first page of search results (n=51). Two coders independently content analyzed each product's Amazon page for claims (e.g., smoking cessation, health), product characteristics (e.g., flavors), and presence of disclaimers and warnings. Overall, 78.4% of product pages made smoking cessation claims (e.g., "A more scientific way to quit smoking", "…decreases nicotine craving symptom and helps to quit tobacco smoking"). Further, 45.1% of product pages included claims describing lower risk/exposure compared to tobacco products (e.g., "…without the addictive nicotine and toxic chemicals found in tobacco cigarettes"). Some herbal products were available in multiple flavors, including menthol (21.6%) and fruit (17.7%). Only 35.3% of products included visible health warnings on product packaging. Many herbal cigarette products sold on Amazon.com make unauthorized cessation and health claims. Regulatory agencies must act decisively to stop the misleading advertising of these products and develop appropriate warnings to educate the public about the potential harms of herbal cigarettes. This content analysis documents the use of unauthorized and misleading claims made in the marketing of herbal cigarettes.These findings highlight the need for enforcement of existing federal regulations, which prohibit deceptive advertising.Research is needed to inform the development of appropriate warning labels that can be used to inform consumers of the potential harms of smoking herbal cigarettes.

Bayes goes big: Distributed MCMC and the drivers of E-commerce conversion

This work researches the drivers of e-commerce conversion of one of the largest e-commerce companies in the Netherlands. We focus on product page conversion, i.e., the probability that a customer who visits a specific product page also buys the product. This probability differs between products, which we explain by a variety of factors like pricing, delivery times, reviews, seller type, and the quality of the content. Understanding the drivers of conversion is the first step in increasing it, and therefore an important step in increasing overall sales. We describe the process of transforming Big Data into valuable insights using Bayesian statistics and apply a Bayesian Binomial model to a dataset of 15 million records using a distributed MCMC algorithm. In addition, we apply a simple Binomial GLM on a small sample of these 15 million records for comparison. We find that using the full 15 million records results in a significant reduction in the variance of the estimated parameters. In terms of the actual drivers of e-commerce conversion, we observe that products with competitive pricing, short delivery times, and good content all achieve a higher conversion on average. Furthermore, reviews, average review score, and the number of reviews for a product have a large positive effect on conversion compared to other characteristics. This provides a unique insight into what makes people decide whether or not to purchase a product.

Does Scarce Inventory Information Disclosure Strategy Promote Online Sales?

In pursuit of promoting sales, certain e-commerce vendors post scarce inventory messages on product pages to signal impending stockouts. To explore how disclosure information strategy regarding scarce inventory influences online sales, this study utilizes Chinese e-commerce data collected from February 1st to April 30th, 2023 and constructs an empirical model that delves into the relationship between the disclosure of scarce inventory information and online sales based on the signal theory. The empirical findings reveal a positive impact of scarce inventory information disclosure on online sales, with this impact being more pronounced under the moderating role of the commodity discount rate. These results hold substantial theoretical implications and offer valuable insights for practical applications in the e-commerce domain.

The absence of mandatory pregnancy warning labels in online alcohol purchasing contexts.

As people increasingly migrate to online shopping platforms, hard-won improvements in requirements for consumer information provision at the point of sale are being eroded. An example is the alcohol pregnancy warning label for packaged alcoholic beverages that has been recently introduced in Australia and New Zealand. The aim of the present study was to assess the extent to which the pregnancy warning was visible at the online point of sale when the requirement became mandatory in August 2023. Data for alcohol products sold on the websites of the two largest alcohol retailers in Australia were web-scraped from 1 to 3 August 2023. The captured data for 8343 alcoholic beverages were inspected to determine whether the pregnancy warning was visible. Virtually no products (0.1%) had the mandatory warning visible on the main sales page, and only 7% enabled visibility of the warning via optional product image rotation functionality. The almost complete absence of the mandatory pregnancy warnings on the main product pages of major alcohol retailers' websites highlights the regulatory problems posed by the emerging shift to online shopping. The very low prevalence of visible pregnancy warnings is likely to be an overestimate of the extent to which consumers would be exposed to warnings due to images being counted as being present regardless of their quality or readability. New regulation is needed to ensure that mandatory information requirements for harmful products are applied to online shopping contexts.

Implementasi Aplikasi Toko Creative Card Berbasis Website Menggunakan Metode Waterfall

The development of technology and the internet has triggered a significant transformation in consumer behavior, especially in the context of electronic commerce. This research aims to address growing market needs by developing a web-based online sticker shop application. This application is designed to provide convenience in the process of selling and purchasing stickers, optimize user experience, and increase product accessibility via online platforms. The development method used in this research involves the application of web technologies such as HTML, CSS, JavaScript, and PHP. This approach allows building systems in a structured and organized manner, with a focus on features that support intuitive user interaction. Some of the key features implemented include informative product pages, an efficient shopping cart system, and transaction history to provide transparency and order tracking for consumers. The result of this research is an online sticker shop application that not only makes the sales process easier for sellers, but also provides a comfortable online shopping environment for buyers. It is hoped that this application can increase efficiency in sales management, increase the competitiveness of the sticker business, and make a positive contribution to the growth of the e-commerce industry. As an innovative solution, this application is expected to be able to keep up with market trends and provide a satisfying online shopping experience for users.

Sistem Informasi Web Promosi Joker Vape dengan Agile Scrum dan Usability Testing

In the developing digital era, it is important for companies to have an effective web information system to promote their products to customers. In particular, the vape industry has experienced rapid growth, surely Joker Vape wants to take advantage of web technologies to increase the visibility and attractiveness of their products. This study aims to develop a Joker Vape Promotion Web Information System with Agile Scrum and usability testing. Agile Scrum is chosen as a development method because of its ability to address user needs. Usability testing is carried out to ensure that this web information system already has a good value in the appearance of the website and ease of using the website. The results of this study indicate that user needs in user story admins such as being able to manage products and the needs of visitors or website users need product pages, product details. In testing the usability of the website, it has already had a good usability value with the usability aspect getting 85.5%, the ease of use aspect getting 87.05%, the ease of learning aspect getting 87%, and the satisfaction aspect getting 85%.

RANCANG BANGUN PURECOMPUTE PLATFORM E-COMMERCE UNTUK BELANJA LAPTOP BERBASIS WEBSITE

The PureCompute Project is an exploration of the design and implementation of an e-commerce platform with a specific focus on laptop sales. The main goal of PureCompute is to provide an optimal online shopping experience, especially for users looking for technology products such as laptops. This report covers the entire development process, starting from needs analysis, system design, technology selection, to the implementation of key features such as login, register, product pages, shopping cart, and authentication and payment systems. The development methodology adopts a software development life cycle and an iterative approach, ensuring flexibility to accommodate changing user requirements. Thus, PureCompute is designed to be responsive to market dynamics and technological advancements. It is expected that PureCompute's positive contribution in providing an efficient and convenient shopping experience will meet the needs of consumers looking for laptops through the e-commerce platform. The success of this project is expected to support and advance the trend of online shopping in the current digital era, through affordable and innovative solutions for technology users.

Content and Style of Firm-Generated Posts on Social Media: A Study of User Engagement on Hedonic and Utilitarian Product Pages on Facebook

Social media platforms are increasingly crucial in corporate engagement, but there is limited research delineating how page characteristics influence firm behavior on these platforms. This paper examines the relationship between firm-generated content and user engagement on product pages and whether a page’s characteristics and content motivations moderate this relationship. Analyzing a sample of 29,267 posts on 85 Facebook product pages of 49 Fortune 1000 firms, we studied the relationship between the content (i.e., informational vs. emotional) and style (i.e., formal vs. informal) of a given post and the level of user engagement. The key finding is that in the content dimension, “incongruous” posts, i.e., content not traditionally expected for a product page of a given type, generate more favorable engagement. Also, informal style posts achieve more favorable engagement irrespective of the product page characteristics. The secondary discovery is attributable to Facebook’s function as a social media network where acquaintances engage with one another. The platform’s unwritten protocol of communication largely emphasizes informality, which is likely the driver of this observation. These findings contribute to the burgeoning social media strategy literature illustrating how product page characteristics moderate effective social media content strategies.

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

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.

Impact of Social Media Marketing on Purchase Intention: The Moderating Role of Perceived Enjoyment

The purpose of this study is to the effect of social media marketing on the purchase intention as the mediating role of perceive enjoyment. This study used the Theory of Planned Behavior (TPB) to examine the variables that influenced participants’ decisions about whether or not to buy tickets to events using social networking sites. This study presented an online survey disseminated through social media based on TPB, using a quantitative research approach. Controllers of events pages on Facebook, Twitter, and Instagram formed the sample population of the study. Convenience sampling technique use for this study and select ample of N= 125. The review showed that all research protocols were accepted. Among all the independent variables of event fans intention, event fans behavior EWOM and brand loyalty had a significant positive effect on the dependent variable of intention to purchase event tickets. This study provided statistical support for the performance of the TPB when it comes to event marketing and social media activities. This suggests a deeper understanding of rational decision-making and social influences in the formation of behavioral intentions and intentions. The model also included a component of subjective pleasure. While there was perceived interest, the event’s social media pages were well received. This emphasizes the importance of presenting information and content in an engaging and simple way. When it comes to promoting events, perceived enjoyment seems to be an important influence. This highlights the need to create a great user experience for the product page, emphasizing customer feedback, information sharing through their engaging product-related stories and experiences between social media, for customers connect, communicate, share with their friends and help, that’s a brand new marketing strategy. Event marketers should use social media to help create, promote and organize events. If the marketing goal is to spark broad interest in the event, social media is a great way to reach a core group of customers, members and donors.

Intangible cultural heritage in industrial design

Abstract The research aims to develop an original product design using elements of intangible cultural heritage (ICH). It attempts to evaluate the attractiveness of design with elements of ICH in individual countries and on the world stage. A Master of Art History from Korea National University of Arts participated in the analysis and research of ICH objects. Based on the Gmarket online store, the authors conducted fake door testing to determine the attractiveness of this design for consumers. The method of paired comparisons allowed the authors to assess the attractiveness of a design with the ICH elements on the world stage. Following the project’s objectives, the study demonstrated 211 thousand views of the product page with the developed design and 767 thousand views of pages with similar products during one calendar month.

ANALISIS SEARCH ENGINE OPTIMIZATION (SEO) PADA UMKM DOA IBU KOSMETIK DI TOKOPEDIA

The existence of social restrictions during the COVID-19 pandemic has had many impacts, one of which is limiting direct sales of SMEs. One of them is Doa Ibu Kosmetik which sells various personal needs like cosmetics and body care. Doa Ibu Kosmetik opens a digital shop through Tokopedia to encourage sales. Search Engine Optimization (SEO) method was implemented in the Tokopedia account to compete with others. The method used to optimize the shop page is to upgrade the shop's status to Power Merchant and activate the features provided by Tokopedia. Product page optimization is carried out by adding titles, prices, descriptions, and product photos so that they comply with Tokopedia's recommendations and can compete with other sellers. The TopAds feature, which is Tokopedia's paid advertising feature, has also been implemented to help increase traffic on the Tokopedia Doa Ibu Kosmetik page. The research results show that optimization on Tokopedia can increase visits and sales.

Survey on the Current Advertising and Sales of Mucuna pruriens in Consumer-to-consumer Internet Trading in Japan

Mucuna pruriens (MP) is leguminous plant which contains 5% of L-3,4-dihydroxyphenylalanine (levodopa) in its seeds. It may have a potential to be used as an alternative therapy for Parkinson's disease (PD). Meanwhile, there is a concern in terms of public health that MP products can be overused by patients with PD. As an entry for patients with PD to acquire MP products in Japan, they are often purchased via internet auctions or free markets. MP products are not reagrded as 'pharmatheutical' by Japanese law as long as the specific legal requirements on advertisements are met, so that the MP products can be advertised or sold without any permission from the authorities. In this study, we aimed to conduct internet survey as to the complianse status of these legal requirements. Several major internet auction or free market websites in Japan were surveyed in May-June 2023 by the authors, and 1157 MP product pages were examined. We found approximately 30-40% of the MP products were suspected to have potential legal risks in terms of their advertisements in their website descriptions, such as claiming pharmatheutical efficacy or describing pharmatheutical-like dosages. In addition, approximately 30-40% of the MP products also did not refer to cautions not to take MP products excessively because of the levodopa ingredients. Current study suggested the need of careful description of the MP products in the auction or free market websites for the MP products exhibitors or sellers, in order to fullfill legal requirements as well as to prevent MP abuse.

Human behavior in free search online shopping scenarios can be predicted from EEG activation using Hjorth parameters.

The present work investigates whether and how decisions in real-world online shopping scenarios can be predicted based on brain activation. Potential customers were asked to search through product pages on e-commerce platforms and decide, which products to buy, while their EEG signal was recorded. Machine learning algorithms were then trained to distinguish between EEG activation when viewing products that are later bought or put into the shopping card as opposed to products that are later discarded. We find that Hjorth parameters extracted from the raw EEG can be used to predict purchase choices to a high level of accuracy. Above-chance predictions based on Hjorth parameters are achieved via different standard machine learning methods with random forest models showing the best performance of above 80% prediction accuracy in both 2-class (bought or put into card vs. not bought) and 3-class (bought vs. put into card vs. not bought) classification. While conventional EEG signal analysis commonly employs frequency domain features such as alpha or theta power and phase, Hjorth parameters use time domain signals, which can be calculated rapidly with little computational cost. Given the presented evidence that Hjorth parameters are suitable for the prediction of complex behaviors, their potential and remaining challenges for implementation in real-time applications are discussed.

Current food labelling practices in online supermarkets in Australia

BackgroundFood product labelling can support consumer decision-making. Several food product labels (nutrition information panels (NIPs), ingredients lists, allergen declarations and country-of-origin) are mandated for physical product packaging in Australia, with a voluntary front-of-pack nutrition labelling system, Health Star Ratings (HSRs), also available. However, labelling requirements are not explicitly extended to online settings and the extent to which this information is available in these increasingly important food environments has not been assessed.MethodsData from all individual food product pages was collected from the online stores of the two dominant supermarket retailers in Australia using automated web scraping in April–May 2022 (n = 22,077 products collected). We assessed the proportion of pages displaying NIPs, ingredients, allergens, country-of-origin and HSRs after excluding products ineligible to display the respective label. We also assessed whether HSRs were differentially available for higher- (healthier) and lower-scoring (less healthy) products, with HSR scores drawn from a comprehensive Australian food composition database, FoodSwitch. A manual inspection of randomly selected product pages (n = 100 for each label type per supermarket), drawn from products displaying the relevant label, was conducted to assess whether the labels were immediately visible to users (i.e. without scrolling or clicking). Differences in labelling prevalence and visibility were compared using chi-squared tests.ResultsAcross both supermarkets, country-of-origin labelling was almost complete (displayed on 93% of food product pages), but NIPs (49%), ingredients (34%) and allergens (53%) were less frequently displayed. HSRs were infrequently displayed (14% across both supermarkets) and more likely to be applied to higher-scoring products (22% on products with ≥ 3.5HSR v 0.4% on products with < 3.5HSR, p < 0.001). One supermarket was far more likely to make NIPs (100% v 2%, p < 0.001), ingredients (100% v 19%, p < 0.001) and allergens (97% v 0%, p < 0.001) information immediately visible, though the other made HSRs more apparent (22% v 75%, p < 0.001). Both supermarkets displayed country-of-origin labels prominently (100% v 86%, p < 0.001).ConclusionsFood product labelling varies in online supermarkets in Australia overall and between supermarkets, while the design of online stores resulted in differences in labelling visibility. The near-complete display of country-of-origin labels and differential application of HSRs to higher-scoring products may reflect their use as marketing tools. Our findings highlight an urgent need for food labelling regulations to be updated to better account for online retail food environments.

Research of ways to improve the effectiveness of remote sales in pharmacies

Aim. To audit the websites of pharmacy chains to identify the main problems and directions for improving the effectiveness of the sale of medicines using information and communication systems remotely.&#x0D; Materials and methods. The content analysis, desk research methods, logical summarization of results, and the graphic method were used to achieve the goal. Data from website analytics were used for the analysis.&#x0D; Results. Six sites of pharmacy chains in Ukraine have been analyzed. It has been found that on average one user views three pages per session, the duration of the session is one minute on average, and the buyer on average collects a basket of four products in the amount of UAH 300. It has been determined that the main login pages are: product page, product list, and main page. It has been determined that search is a key feature of product selection and is used in 15 % of all sessions. It has been found that in 70 % of cases, mobile devices are used, desktops are used in on average in 26 % of cases, and tablets are used in 4 % of cases. It has been determined that, on average, twice as many conversions are made through the desktop than when using mobile devices and tablets. For the analysis, the most common scenarios of user behavior on the pharmacy chain sites have been selected. While implementing the most frequent errors on websites have been identified, when the interface does not respond to important requests of consumers, which affects their purchase decisions. The analysis and systematization of the main errors on the websites of pharmacy chains have been carried out; recommendations for their elimination have been formulated. This will make it possible to increase the effectiveness of information support for electronic sales of pharmacies in accordance with the requirements of proper pharmacy practice, will affect the customer loyalty and the economic indicators of the activity of pharmacies. &#x0D; Conclusions. Based on the results of the study, it can be concluded that usability errors and factors contributing to growth should not be underestimated since they can significantly affect conversion rates; even a slight rapid change can improve the site’s KPIs; it is necessary to make the interface equally user-friendly on different devices.

TEE: Real-Time Purchase Prediction Using Time Extended Embeddings for Representing Customer Behavior

Real-time customer purchase prediction tries to predict which products a customer will buy next. Depending on the approach used, this involves using data such as the customer’s past purchases, his or her search queries, the time spent on a product page, the customer’s age and gender, and other demographic information. These predictions are then used to generate personalized recommendations and offers for the customer. A variety of approaches already exist for real-time customer purchase prediction. However, these typically require expertise to create customer representations. Recently, embedding-based approaches have shown that customer representations can be effectively learned. In this regard, however, the current state-of-the-art does not consider activity time. In this work, we propose an extended embedding approach to represent the customer behavior of a session for both known and unknown customers by including the activity time. We train a long short-term memory with our representation. We show with empirical experiments on three different real-world datasets that encoding activity time into the embedding increases the performance of the prediction and outperforms the current approaches used.

WIERT: Web Information Extraction via Render Tree

Web information extraction (WIE) is a fundamental problem in web document understanding, with a significant impact on various applications. Visual information plays a crucial role in WIE tasks as the nodes containing relevant information are often visually distinct, such as being in a larger font size or having a brighter color, from the other nodes. However, rendering visual information of a web page can be computationally expensive. Previous works have mainly focused on the Document Object Model (DOM) tree, which lacks visual information. To efficiently exploit visual information, we propose leveraging the render tree, which combines the DOM tree and Cascading Style Sheets Object Model (CSSOM) tree, and contains not only content and layout information but also rich visual information at a little additional acquisition cost compared to the DOM tree. In this paper, we present WIERT, a method that effectively utilizes the render tree of a web page based on a pretrained language model. We evaluate WIERT on the Klarna product page dataset, a manually labeled dataset of renderable e-commerce web pages, demonstrating its effectiveness and robustness.