Store Sales Research Articles

Data Visualization of Bike Store Sales in Europe

This paper presents a comprehensive analysis of bike sales and customer demographics in Europe based on a dataset obtained from Kaggle.com. The dataset covers the period from 2011 to 2016 and includes information on customer age, gender, product categories, order quantities, unit costs, unit prices, profit, and revenue. The analysis utilizes data visualization techniques to identify key trends, including the top-selling products, customer purchasing power across different age groups and customer genders, and product profit margins. The findings suggest opportunities for retailers to target specific customer segments and product categories to maximize profits. Additionally, the report highlights the growing popularity of cycling as a sport and a healthy lifestyle choice, indicating a potential for increased demand in the bike retail market. Overall, the insights provided in this report aim to assist retailer chains in developing effective strategies to capitalize on the opportunities presented by the European bike sales market.

СУЧАСНІ МЕТОДИ ІНТЕРНЕТ-ПРОСУВАННЯ НА РИНКУ ДВЕРЕЙ

This article highlights current strategies and effective methods of promoting products in the door market via the Internet in the competitive struggle for sales markets. Analyzing a highly competitive industry, the authors examine various aspects of an effective online presence to increase store traffic and sales. The article focuses on the analysis and comparison of various modern methods of Internet promotion in the context of the door market, with an emphasis on determining the most effective approaches to their application, in particular, such as: social networks, search engine optimization, e-commerce, video marketing, cooperation with influencers, retargeting, content -marketing and adaptive web design. The authors examine each of these methods in detail, evaluating their cost, complexity of setup, and potential effectiveness for different target audiences. Special attention is paid to analyzing the needs of different market segments, such as: young professionals, married couples, older generations, eco-conscious buyers, developers, owners of commercial premises and real estate investors. The article examines exactly how strategies can help increase competitiveness and effectively attract the attention of the target audience. The authors emphasize the importance of a comprehensive approach and individual targeting of each segment, taking into account their unique needs and preferences. The article also includes recommendations for the optimal combination of various Internet marketing methods to maximize the effectiveness of marketing efforts in the door market. Conclusions and proposals are based on a deep analysis of modern trends in digital marketing, as well as on the experience of the author team in this field. The article contains practical recommendations for companies specializing in the sale of doors, which seek to successfully market their products via the Internet. In particular, modern trends and innovative approaches for optimizing electronic business in the field of door production and their implementation are considered. This work can be useful for marketers, door manufacturers, and anyone interested in developing effective Internet marketing strategies in specific markets.

Proposed Marketing Mix to Increase Sales of Kliknik Stores in E-Commerce

Kliknik is a shop that sells medicines and vitamins. Kliknik operates on e-commerce at Tokopedia and Shopee. Kliknik's main problem is not achieving the target since March 2022. This is in line with the improving pandemic conditions in Indonesia. Compared with several pharmaceutical companies' net sales, the improving pandemic conditions do not affect a company's sales. It is necessary to propose a marketing mix that Kliknik can implement based on segmenting, targeting, and positioning analysis to achieve the specified Kliknik sales target. Data collection was carried out using a questionnaire. 97 respondent data was obtained, which could be analyzed. Segmentation analysis was done by using k-means clustering. Three clusters were obtained: general, loyal, and critical customers. Through a targeting process, loyal customers were selected as the target market for Kliknik Shop. The positioning statement for the Kliknik Shop is that loyal customers can always shop at the Kliknik because the Kliknik Shop appreciates the trust they have been given. The marketing mix proposal is general but still adheres to the 4P+2P+2C+3S marketing mix concept. The proposed marketing mix given is that Kliknik Shop can take part in some events held by e-commerce, Kliknik Shop admin can actively contact customers who have finished shopping via the chat feature in e-commerce and must be responsive to respond to all chats, comments, and discussions. Kliknik shops are also advised to create social media, Instagram, as a promotional media and extend store operating hours.

The prevalence and magnitude of price promotions in online alcohol retail outlets.

We examined the prevalence of price promotions (i.e., proportion of products on price promotion) and the magnitude of price promotions (i.e., size of the price discount compared to the regular price) among online alcohol retailers. In August 2023, we web-scraped product information for all alcoholic beverages available for sale in the online stores of two leading alcohol retailers in Sydney, Australia. Products were classified into five primary alcohol categories: wine, spirits, beer, cider and premix drinks. We considered three types of price promotion: temporary price discounts (e.g., 'was $5 now $4'), multi-buy discounts (e.g., buy one get one free) and 'any six' discounts (e.g., 5% off when purchased in a bundle of any six similar products). The prevalence and mean magnitude of price promotions were estimated overall and by product category and price promotion type. In total, data for 11,184 products were collected. Of these, 62% were the subject of at least one of the assessed forms of price promotion. The most frequently price-promoted category was wine (91% of products), followed by spirits (35%), premix drinks (30%), cider (28%) and beer (21%). Of all price promotions, 61% were 'any six' discounts, 31% were temporary price discounts, and 7% were multi-buy discounts. Across all price promotions, the mean magnitude of price discount relative to the regular price was 11% and ranged from less than 1% to 71%. Policymakers should consider restricting price promotions as part of a suite of strategies to reduce alcohol-related harms.

The relationship between alcohol availability and drink-driving policies and admissions to substance use disorder treatment during pregnancy.

Pregnancy-specific alcohol policies are widely adopted yet have limited effectiveness and established risks. It is unknown whether general population alcohol policies are effective during pregnancy. This study investigated associations between general population policies and alcohol treatment admission rates for pregnant people specifically. Data are from the Treatment Episodes Data Set: Admissions and state-level policy data for 1992-2019 (n=1,331 state-years). The primary outcome was treatment admissions where alcohol was the primary substance, and the secondary outcome included admissions where alcohol was any substance. There were five policy predictors: 1) Government spirits monopoly, 2) Ban on Sunday sales, 3) Grocery store sales, 4) Gas station sales, and 5) Blood alcohol concentration (BAC) laws. Covariates included poverty, unemployment, per capita cigarette consumption, state and year fixed effects, and state-specific time trends. In models with alcohol as the primary substance, prohibiting spirits sales in grocery stores (vs. allowing heavy beer and spirits) had lower treatment admission rates [IRR=0.88, 95% CI: 0.78-0.99, p=0.028]. States with BAC laws at 0.10% (vs. no law) had higher treatment admission rates [IRR=1.24, 95% CI: 1.08-1.43, p=0.003]. When alcohol was any substance, prohibiting spirits sales in grocery stores (vs. allowing heavy beer and spirits) was again associated with lower treatment admission rates [IRR=0.89, 95% CI: 0.80-0.98, p=0.021], but there was no association for BAC laws. Restrictions on grocery store spirits sales and BAC laws were associated with lower and higher alcohol treatment admission rates among pregnant people, respectively, suggesting general population alcohol policies are relevant for pregnant people's treatment utilization.

PENERAPAN ADVANCED ENCRYPTION STANDARD UNTUK SISTEM LOGIN DAN REGISTRASI PADA SISTEM INFORMASI PENJUALAN (STUDI KASUS:TOKO ILHAM BANJAR)

Data security in sales information systems has become a critical priority in today's digital era. Ilham Banjar Store needs a system that can effectively protect user data, especially in login and registration features, which are vulnerable to security threats. The lack of encryption mechanisms in the current system results in user data, such as passwords, being transmitted in plaintext, increasing the risk of unauthorized access and data modification. Therefore, this study aims to enhance the security of the Ilham Banjar Store's sales information system by implementing the Advanced Encryption Standard (AES) 256-bit Cipher Block Chaining (CBC) method in the login and registration processes. The research method used is Research and Development (RD), consisting of stages such as literature review, needs analysis, system design, implementation, testing, evaluation, and analysis. The implementation of the Advanced Encryption Standard (AES) involves the encryption processes of AddRoundKey, SubBytes, ShiftRows, and MixColumns, and the decryption processes are the inverse of these encryption steps. Testing includes measuring encryption and decryption times as well as verifying data integrity using HMAC (Hash-Based Message Authentication Code). The research results show that the performance testing indicates encryption and decryption times remain within acceptable limits, and the encrypted and decrypted data maintain their integrity. Thus, the new system meets both security and performance requirements.

The Impact of New Jersey's 2020 E-Cigarette Flavor Ban on E-Cigarette, Cigarette, and Cigar Sales in NJ.

On April 20, 2020, New Jersey (NJ) implemented a comprehensive ban on the sale of flavored e-cigarettes. This study compares sales of e-cigarettes, cigarettes, and cigars before and after the law. Data were biweekly retailer scanner sales in NJ convenience stores for e-cigarettes, cigarettes, and cigars between August 2019 and December 2020. We used Joinpoint regression to assess sales trends for cigarettes (non-menthol, menthol), cigars (unflavored, flavored), and e-cigarettes (unflavored, fruit/sweet/concept flavor, menthol flavor) in the 36 weeks before and 36 weeks after a statewide ban on flavored e-cigarettes. Flavored e-cigarette sales, not including menthol, significantly decreased over the study period while menthol e-cigarette sales significantly increased until the e-cigarette flavor ban took effect, after which these sales rapidly declined through May 2020, then slowed. Unflavored e-cigarette sales declined through September 2019, then grew modestly until the flavored e-cigarette ban, after which sales significantly increased. Flavored cigar sales increased between March and May 2020, then declined; non-flavored cigar sales increased between mid-February and early July 2020, then declined. Cigarette sales were decreasing before the flavored e-cigarette ban but after, significantly increased until June 2020. Overall, there was no significant trend in the average biweekly percent change for cigarette sales. Flavored e-cigarette sales were declining prior to the ban but the pace of the decline accelerated following federal and state restrictions on flavored e-cigarette sales, then slowed by the second half of 2020, with a brief period of increased cigarette and cigar sales immediately following the ban. New Jersey's 2020 statewide e-cigarette flavor ban offered the opportunity to observe how sales of e-cigarette, cigarette, and cigar products shifted after the change. The effect of the state law, at least in the short-term, was decreased sales of flavored e-cigarettes and increased sales of unflavored e-cigarettes. Research on long term policy effects is needed.

External Nonfinancial Measures in Substantive Analytical Procedures: Contributions of Weather Information

ABSTRACT Recent studies and new standards suggest that auditors can use information from expanded external sources to verify their clients’ financial information. We propose advanced substantive analytical procedures with external nonfinancial measures derived from weather information to test whether it helps detect misstatements. Using computational simulations and daily store-level sales data, we test whether the proposed procedures with weather indicators outperform the procedures without such indicators in substantive analytical procedures to identify overstated daily store sales. For the multilocation retail firm examined in this study, we find that the models with one or more weather indicators perform better at detecting misstatements than the models without them. When the reliability of relevant internal information is in question, the usefulness of weather indicators is apparent. Overall, our results provide evidence suggesting the potential value of external nonfinancial measures in auditing.

Research on the Impact of Store Sales Share on Consumer Purchase Intentions in the Catering Industry

Research on the Impact of Store Sales Share on Consumer Purchase Intentions in the Catering Industry

Research on the Development Direction and Countermeasures of Civil Aviation Ticketing Offices

With the popularization of electronic tickets and the development of information technology, aviation e-commerce has rapidly developed. The marketization of civil aviation in China has made agents no longer limited by the original ticket management and terminal maintenance. In order to pursue greater marginal profits, various sales prices and measures have spread through the network, and sales channels are becoming more and more diversified. The forms of air ticket sales are also diverse. Based on the analysis of the advantages and disadvantages of online platform sales and traditional ticket office store sales under e-commerce, the author believes that ticket offices can develop towards joint tourism integration and upgrading, and provide diversified services according to their own situation.

BUILDING SALES CHANNELS FOR NEW TIRE BRANDS USING STRATEGIC MANAGEMENT THEORY: A CASE STUDY OF BRAND A

As competition within the tire industry intensifies, Brand A faces an urgent imperative to enhance its market share through the strategic construction of effective sales channels. Grounded in strategic management theory, this study aims to conduct a thorough analysis of the current situation and challenges facing the sales channels of new A-brand tires, and explore feasible optimization strategies. This study uses Brand A tires as an example. By analyzing the current status of marketing channels for Brand A tires, this study proposes an optimization strategy. Prioritizing channel optimization principles should be the first priority. In order to improve channel synergy as well as strengthen incentives for retailers, the study proposes measures such as providing training to enhance store sales capabilities, offering incentives to implement promotional activities, and providing incentives to sell high-profit products. Finally, for the management of cross-channel goods, the study recommends establishing a systematic product sales record and implementing an inspection and supervision system. In summary, this study addresses the challenges present in the sales channels of A-brand tires, focusing on optimizing the layout of physical marketing channels, enhancing channel synergy, strengthening retailer incentives, and improving channel cross-stocking management. We anticipate that the implementation of these strategies will enhance the efficiency and competitiveness of Brand A tires' sales channels.

Spatiotemporal mapping of urban trade and shopping patterns: A geospatial big data approach

The economic viability of an urban area in terms of trade and shopping significantly impacts its residents’ quality of life and is crucial for any sustainable development initiative. Geographic information systems (GIS) are well established, but the use of GIS technology within finance and trade analysis is still in its infancy. In this article, we highlighted the potential of GIS technology and big data analytics and demonstrated the importance of thinking in spatial terms for analysing patterns within the trade and finance industries. We studied spatiotemporal trade and shopping patterns in the city of Tabriz using data generated by customer purchase transactions obtained from 5200 stores, shopping, business and service centres. We employed time series transaction data collected from the points of sale in stores, shopping, service and business centres located in different areas of the city. We applied four well known geospatial big data driven approaches including machine learning nearest neighbour, kernel density estimation, space–time pattern mining and spatiotemporal coupling tele-coupling for detecting and mapping of spatial trade hotspot patterns. The results of this study indicated the potential of GIScience methods for the explicit spatial mapping of trade and shopping patterns. The results revealed that the city centre, particularly the Bazaar of Tabriz, acts as the city’s heart of trade, and we identify additional major business hotspots. Furthermore, the results allow for studying the impacts of unbalanced urban development in Tabriz, where the wealthy suburbs with high quality of life, such as Valiasr and Elguli, host the major shopping hotspots. The spatial patterns obtained enable local stakeholders, decision makers and authorities to develop strategic plans for urban sustainable development in Tabriz. The geospatial big data approach used can stimulate novel and progressive research. Results of this study demonstrate methodological advancements in GIScience by ’spatializing’ individual purchase data and therefor proposing an explicit geospatial big data analysis approach.

Perspective on the consumption of ultra-processed foods among university students

The study examines the perspective on the consumption of ultra-processed foods among university students. The consumption of ultra-processed foods by university students has always been a concern for nutrition specialists and university specialists because there is no law that regulates sales in sales centers or stores near the university as there is for regular education. There is also no culture of healthy food consumption in university students, despite being trained in healthy food and eating habits that students immediately fall back on, so the purpose of this research is to analyze and describe the prospects of consumption of ultra-processed foods among university student in the province of Sullana. For which a descriptive design was used with a quantitative, correlational, and intentional sampling approach due to the ease of digital communication, a survey was used in which any student could participate voluntarily and anonymously. This questionnaire had 26 questions whose answers were on a Likert scale of five points, in which 827 university students participated. The results show that there is a high level of consumption of ultra-processed foods among university students, with preferences for pastry products, cookies, and chocolates. It is concluded that university students do not have a culture of healthy food consumption and consume all kinds of products found in the surroundings of the university, and these are what are called "junk" foods that damage health sooner or later.

Strategic Impact: Ross Store Commercial and Sales Strategies in Quevedo 2023

The research set out to analyze the commercial strategies and their influence on Ross Store's sales in Quevedo during the year 2023. To achieve this objective, detailed procedures were carried out, including the collection of data on the commercial strategies implemented by the company, such as promotions, advertising, and inventory management. Interviews were conducted with key personnel and relevant financial data was collected. The analysis focused on the correlation between the strategies employed and sales performance, assessing their impact on profitability and market share. The results revealed significant insights into the most effective tactics, identifying areas for improvement and providing strategic recommendations to optimize Ross Store's business performance in the future. This study not only provides an in-depth understanding of the specific business dynamics of Ross Store in Quevedo, but also provides valuable insights for the retail sector in general, highlighting successful business practices that could be replicated in other similar companies.

Marketing Strategy Through Social Media in Increasing Sales at Zheni Rz Furniture Store East Lampung

The problem that occurs in Zheni Rz Furniture Store is the lack of marketing through social media, considering the large number of social media users who can be a means to promote as a marketing strategy to face increasingly fierce competition. This study aims to analyze methods that can be used to increase sales at Zheni Rz Furniture Store. Method analysis in research using a qualitative descriptive approach. Where, research does not use quantitative measurements to describe and explain phenomena. This research uses SWOT analysis as a means of qualitative descriptive approach. The results show that Zheni Rz Furniture Store is in quadrant 1 with a very advantageous position because it has strengths and opportunities that can be optimized there. In this quadrant 1, Zheni RZ Furniture store East Lampung can use an aggressive growth policy. The SWOT diagram table shows the strategies that Zheni Rz Furniture Store can use to help increase store sales.

Relationships Between Alcohol Policies and Infant Morbidities and Injuries

Previous research has found that policies specifically focused on pregnant people's alcohol use are largely ineffective. Therefore, the purpose of this study is to analyze the relationships between general population policies regulating alcohol physical availability and outcomes related to pregnant people's alcohol use, specifically infant morbidities and injuries. Outcome data were obtained from Merative MarketScan, a longitudinal commercial insurance claims data set. Policy data were obtained from the National Institute on Alcohol Abuse and Alcoholism's Alcohol Policy Information System, the National Alcohol Beverage Control Association, and Liquor Handbooks and merged using policies in effect during the estimated year of conception. Relationships between state-level policies regulating sites, days/hours, and government monopoly of liquor sales and infant morbidities and injuries were examined. Analyses used logistic regression with individual controls, fixed effects for state and year, state-specific time trends, and SEs clustered by state. The study analysis was conducted from 2021 to 2023. The analytic sample included 1,432,979 infant-birthing person pairs, specifically people aged 25-50 years who gave birth to a singleton between 2006 and 2019. A total of 3.1% of infants had a morbidity and 2.1% of infants had an injury. State government monopoly on liquor sales was associated with reduced odds of infant morbidities and injuries, whereas gas station liquor sales were associated with increased odds of infant morbidities and injuries. Allowing liquor sales after 10PM was associated with increased odds for infant injuries. No effect was found for allowing liquor sales in grocery stores or on Sundays. Findings suggest that limiting alcohol availability for the general population may help reduce adverse infant outcomes related to pregnant people's alcohol use.

Strategic Advancements: Crafting a Data-Driven Growth Plan for Retail Excellence using Data Analysis

In the realm of modern business, crafting a data-driven growth plan for retail excellence is a crucial endeavour. This project draws inspiration from the retail giant Walmart, utilizing extensive datasets to unravel intricate interrelationships that significantly influence sales. By applying data analysis techniques, including exploratory data analysis, the aim is to provide practical insights into the impact of factors such as temperature, fuel prices, and holidays on weekly retail store sales. The ultimate goal is to contribute valuable insights to the ongoing conversation about revenue enhancement strategies, with Walmart serving as a benchmark. The project emphasizes the compilation and evaluation of large datasets to decipher complex interrelationships, allowing for the formulation of more efficacious revenue-oriented programs and tactics. By focusing on exploratory data analysis, the analysis sheds light on how various elements impact retail store sales, providing practical insights that contribute to the evolving discourse on revenue in the retail sector

Research on feature coding theory and typical application analysis in machine learning algorithms

Nowadays, the world is still in the environment of economic depression. In order to promote economic recovery, improve Relations of production and production efficiency, stimulate consumption expansion and upgrading, and accelerate industrial transformation and upgrading, problems such as industrial upgrading need to be solved urgently. Solving the above problems requires more useful tools, and artificial intelligence is one of them. Machine learning is the key to distinguishing artificial intelligence from ordinary program code. Unlike people learning knowledge, machine learning has its own unique language algorithms and behavioral logic. Machine learning, as a technology active in the field of artificial intelligence in recent years, specializes in studying how computers learn, simulate and realize part of human learning behavior, so as to provide data mining and behavior prediction for humans, to obtain new knowledge or skills, or to strengthen the original basic ability of machines. In this study, a variety of common coding algorithms and learning strategies in machine learning are discussed, supervised learning algorithms are selected as examples in the learning strategies, models are further selected and evaluated for a variety of algorithms, and parameters are adjusted and performance is analyzed. As for the theoretical analysis in the research, the paper makes a tentative application in the three fields of housing price, physical store sales and digital recognition, explores and selects the corresponding application method in the appropriate scenario, and expands the application field of machine learning.

Pendampingan Operasional Toko Online “BUMDes Mart Mulyoagung

The purpose of mentoring activities for service partners, namely Bumdes Mart Mulyoagung in Mulyoagung village, Dau sub-district, Malang district, is to develop a shopping business unit by opening a shop on the Shopee marketplace. By opening a shop on the marketplace, it is hoped that it can increase store sales, which so far have experienced problems with delays in the delivery of goods and no increase in sales due to limited consumers, namely only those with shop business WhatsApp numbers. Village community products will also be able to reach a wider range of consumers by opening shops on the marketplace. Activities are carried out in stages starting from the preparation, implementation, and evaluation stages. The results of the activity were the formation of the Bumdes Mart Mulyoagung online store on the Shopee marketplace as well as online sales transactions. It is hoped that increased sales through the marketplace will increase shop profits so that they can be used for store operational costs, and the excess can provide input for Village Original Income.

The Influence of Store Atmosphere and Sales Promotion on Customer Satisfaction and its Impact on Customer Loyalty Coffee Shop Kopilogi

This study aims to determine the effect of store atmosphere and sales promotion on customer satisfaction and its impact on customer loyalty of the Kopilogi coffee shop. The survey was conducted on consumers of the Coffee Shop Kopilogi Garut, the research method used was descriptive and verification method with a total sample of 94 respondents, the data analysis used was path analysis. The results of the study show that in structure I there is an influence of store atmosphere and sales promotion on customer satisfaction by 52.7%. In structure II there is an influence of store atmosphere and sales promotion on loyalty through customer satisfaction of 76.0%.