Brand Sales Research Articles

Retracted: Analysis of the Influencing Factors of Urban Sports Brand Sales Volume Based on AHP

Retracted: Analysis of the Influencing Factors of Urban Sports Brand Sales Volume Based on AHP

A STUDY ON INFLUENCERS ENDORSEMENT IN SOCIAL MEDIA MARKETING

The rise social media has opened a new channel for brands to connect with consumer more directly. Social media brand influencers are on the rise, becoming one of the biggest marketing and public relation trends nowadays. Now influencers focus on working with companies whose products non-celebrity individual use in their daily lives. Influencer marketing based on traditional media has been used in public relations for many years, the rise of social media influencer marketing has successfully changed the way that brand interact with consumers. The main purpose of this study is to analyse the Influencers Endorsement in social media marketing. The Influencer's product is clearly endorsed by people (respondents) who might buy it. Social Media Marketing with influencers has a huge impact on brand awareness and sales because it allows businesses to make their products more visible and it helps them to increase brand awareness. Hence, if the lifestyle product is influenced by an influencer, the young audience will choose it more than other products. When an influencer endorses a product, respondents are more likely to purchase it. It is clear from this research that they will lose followers if they falsely promote the product, while others believe they will influence others to buy that product after they have tried it.

SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY'S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS

Social media interactions, the digital form of classical word-of-mouth marketing (AAP), used to strengthen the business-brand image, have become one of the most critical evaluation criteria today. It is known how effective social media is in maximizing brand awareness and sales. For this purpose, the social media contents of the users abroad of Getir, Turkey's largest unicorn company, were analyzed. In this direction, the contents of the tweets posted in English from July 1, 2021, when Getir was launched to the European market in general, until July 1, 2022, were analyzed. Python programming language was used for data collection, and R language was used for data analysis. Social network analysis (SAA) of the most used words in the context of positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, and trust of the emotional states of the tweets posted for Getir was performed. Social network analysis (SAA) was conducted in the context of positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, and trust of the most used words in the emotional states of tweets for Getir. As a result of the analysis, it was determined that the positive emotions of the users towards Getir were higher than the negative emotions. It has been determined that the company's development performance and social media analysis results are in parallel.

Research on sales strategy of electric vehicle target customers based on machine learning algorithm

Due to the influence of various subjective and objective factors, there is great uncertainty in consumers' willingness to purchase new energy vehicles. In this study, it is hoped that based on customer satisfaction and personal characteristic information, the main factors affecting whether the target customers are willing to purchase new energy vehicles are explored, so that corresponding sales strategies can be formulated. In this study, two different embedding methods based on penalty terms and tree models are used for feature selection, the former using three models LR, LASSO and SVM, and the latter using RF and LightGBM models for a total of five models for machine learning to find out the relevant features that affect the sales of different brands, and the voting method is applied to the selected features, and the results are found. The battery technology performance of electric vehicles, comfort, annual mortgage of target customers and the ratio of auto loan to annual household income have a significant impact on the sales of all three brands. In addition, affordability, safety and customer's work situation also had different degrees of influence on sales of the different brands. A multilayer perceptron (BP neural network) prediction model is built for each brand's target customers to predict their purchase intention. The prediction accuracy of the network is improved by balancing the positive and negative samples so that the ratio of the two types of samples in the dataset is approximately 1:1. The test set is also used for real-time testing to determine the fit status of the dataset. The accuracy of the final model was above 80% on both the training and test sets, and the model predicted the 1st, 5th, 6th, 7th, 12th, and 12th samples. The model predicted the purchase intention of the 1st, 5th, 6th, 7th, 12th and 13th customers.

The challenge and opportunity of LV under the pandemic and its future sustainability strategy

The novel Coronavirus pneumonia pandemic that began in early 2020 is still ongoing, resulting in great restrictions on international trade and heavy losses in the world economy. The shrinking income and rising unemployment rate have led to a serious decline in the market demand for luxury goods, and people's choice and pursuit of goods are more cost-effective and practical. In this era, the offline retail of luxury brands will inevitably be severely impacted. However, with the strong recovery of the luxury market in 2021, Especially in Chinese mainland, the luxury industry has unprecedented potential, so the luxury brands such as LV will usher in new challenges and opportunities. Even with the sudden outbreak of COVID-19 and the dismal sales of major brands in the past two years, LV has become one of the most resilient luxury brands under the pandemic by virtue of its brand image and marketing management. The measure it did in the post-pandemic era provides luxury brands with a reference. Therefore, the purpose of this study is the future prospects of the luxury industry and how LV will respond with this prospect, and also its future sustainable development under the pandemic. This paper analyses the future environment of the luxury industry in China and to provide some recommends to the transformation in various approaches to achieve sustainable development. The article will conduct a PEST analysis of the current luxury environment, and the port five-force analysis of the industry, aiming to explore and study the future development of luxury goods.

Implementation of Data Mining to predict sales of Bogo helmets using the Naïve Bayes algorithm

Consumer needs for safety and comfort in driving are very important, especially for two-wheeled or motorcycle riders. A good helmet is a helmet that is safe and comfortable when worn. Helmet qualifications that meet SNI standards are open helmets and closed helmets. Transactions are carried out online, because it was still in a pandemic situation when it was established. By carrying the tag line "Ride Safety With Your Own Style", trying to educate the younger generation to keep paying attention to safety when driving but also not neglecting fashion. For the type of sale of bogo and retro helmet brands, with a variety of colors and affordable prices. A common problem faced is how to predict or forecast future helmet sales based on pre-recorded data. This prediction is very influential on the decision to determine the number of helmets that must be provided, if you order helmets in sufficient quantities and it turns out that only a few helmet sales are sold and this will cause the stock of helmets to accumulate. The results of predictions for the sale of bogo helmets in Baris True Instances amounted to 16 data, which means Valid with 53% data accuracy. Meanwhile, there are 10 data classified as Instancely Classified Instance which means Invalid, with data accuracy of 46.67%. The amount of accuracy in the Weka application is the same as the amount of accuracy in Excel calculations. From the explanation above, the Naïve Bayes algorithm method is the best solution for predicting important things in a business need and others.

Fluctuation in Grocery Sales by Brand: An Analysis Using Taylor’s Law

In recent years, Taylor’s law describing the power function relationship between the mean and standard deviation of certain phenomena has found an increasing number of applications. We studied the characteristics of Taylor’s law for branded product sales using point-of-sale (POS) data for brands sold in 72 grocery stores in the Greater Tokyo area. A previous study found that product sales follow Taylor’s law with a scaling exponent of 0.5 for low sales quantities and 1.0 for large sales quantities. In the current study, we observed Taylor’s law with cross-over for 54 product brands and estimated the value of the two coefficients in the theoretical curve to characterize the cross-over. The coefficients represent the fluctuations in the number of items purchased per consumer and the number of consumers in one store and in all stores. The estimated coefficients suggested the dependence of the features of Taylor’s law on the category to which the brands belong. We found that brands in the same category tend to share similar features under Taylor’s law. However, some brands exhibited specific features that differed from others in the same category. For example, for many brands in the Laundry Detergent and Instant Noodles categories, the number of customers purchasing the products in each store fluctuated significantly, whereas the number of purchased items per customer varied widely in the Japanese Tea category. In the coffee category, our results indicated that the degree of fluctuation in the number of purchasing customers largely depends on the brand.

Analysis of the Influencing Factors of Urban Sports Brand Sales Volume Based on AHP

In order to evaluate the brand image and help enterprises to build an ideal brand image, the influence factors of urban sports brand sales volume based on AHP are studied. The article takes the A sports brand as the research object, selects six dimensions including product dimension, enterprise dimension, and service image dimension, establishes a brand image evaluation model, and uses the AHP to study the A sports brand image. The experimental results show that: it is found that the overall evaluation value of A sports brand image is 81.153 points, which is rated as very satisfactory, it is proven that the research gives relevant recommendations for maintaining and developing brand image.

Motivating Factors to Self-Disclosure on Social Media: A Systematic Mapping

<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Background:</b> Self-disclosure on social media can cause some privacy risks, but it benefits users and businesses if adequately managed. Companies may benefit from users’ self-disclosure on social media to better understand the consumers’ needs, customize services or products, and address users’ concerns to sculpt positive brand reputation, trust, and sales. In addition, users’ better understanding of self-disclosure motivations helps them manage more suitable topic, platform, and concepts to match the intended online personal or professional persona. Finally, technical communicators’ understanding of the motivation for social media self-disclosures can help them leverage available self-disclosure in producing more effective technical communication and carefully plan self-disclosures with clear motivations. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Literature review:</b> Many researchers have studied the varying self-disclosure motivations, but to the best of our knowledge, no mapping studies are currently available summarizing the motivations of self-disclosure on social media. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Research question:</b> What does the current research about self-disclosure identify as users’ motivation for self-disclosure on social media? <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Research methodology:</b> We conducted a systematic mapping study that included relevant journal and conference publications. Mapping studies are suitable for structuring a broad research field concerning research questions about content, methods, or trends in the existing publications. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results:</b> We found four categories for social media self-disclosures: discloser-related, audience-related, platform- and affordances-related, and perceived risk- and cost-related. Within the main categories, we found varying submotivations. We also discuss the implications of our findings and future research needs. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusions:</b> The mapping of available studies helps researchers, academics, and practitioners understand existing self-disclosure motivations and research gaps. In addition, social media stakeholders planning to use social media self-disclosures within their areas of interest can use this study as a starting point to understand what drives social media self-disclosures.

What is There in pH?—A Soap Opera

In 2021, Sebamed’s campaign appealed to consumers that ‘Do not listen to Film stars, Listen to Science’ ( Film stars kee Nahi, science kee suno—in Hindi). The campaign intended to persuade consumers to make more informed choices when they buy personal care products and to compare Sebamed’s attributes (pH) with its competitors—Dove and Lux (Hindustan Unilever—HUL). Sebamed highlighted the pH as an attribute and how soap’s high pH value (7 and more) can be harmful to the skin. The campaign was comparing the pH value of Sebamed with HUL’s Dove and Lux. HUL reacted to this campaign and highlighted the research, development and testing process adopted for its different products. HUL also did a counter-campaign highlighting that water also has a pH of 7 and suggested that consumers use common sense when buying soaps. Even though the campaign by Sebamed was interesting it did not have any significant impact on the sales of HUL brands—Dove and Lux. The interesting question is: what should be the focus of campaigns in a hypercompetitive market?

Luxury or Masstige: Role of Global and Local Identities, Luxuriousness Variances, Price Luxuriousness Inferences, and Consumer Flexibility

Masstige or mass prestige luxury brands are considered one of the principal drivers behind increased luxury consumption. Literature has proposed increasing globalization as one of the primary reasons behind the sales of these masstige brands. Given the impact of globalization, this research proposes and examines the impact of consumers’ global and local identities on their propensity to purchase traditional luxury and masstige brands. Results from a survey of 278 Indian respondents show a differential impact of global and local identities of consumers on these preferences. Further, the results show the serial mediation of luxuriousness variances and price luxuriousness inferences behind this impact. The results also indicate that the mediating effect of price luxuriousness inference is moderated by consumer flexibility, where consumer flexibility is a facet of consumer wisdom. The traditional luxury and masstige brand managers can use these results to formulate segmenting, targeting, and positioning strategies for their brands.

Research on Marketing Strategy of Electric Vehicle Based on Bayesian Processing and Natural Language Analysis

The automobile industry is an important pillar of the national economy, and the new energy automobile industry is a strategic emerging industry. This paper carries on the mathematical modeling analysis of the new energy electric vehicle. First of all, using the naive Bayesian processor in natural language processing, make a judgment through theme analysis and emotion analysis, define the coefficient into the model, and finally compare target customers' satisfaction with different brands of cars. Then use DBSCAN and UMAP algorithm to divide the fluctuating data index on the sequence, analyze its linkage by establishing linkage factor to study its correlation degree, and then quantify the problem, establish abnormal coefficient, analyze the persistence of data run out for a single index, and establish an algorithm for evaluating abnormal coefficient. According to the distribution of different data indicators, the impact index of different factors on the sales of different brands of electric vehicles is determined.

Effects of Customer Reviews on Product Sales of Strong Brands:

Effects of Customer Reviews on Product Sales of Strong Brands:

Social Gratification and Second-Hand Fashion: An Exploratory Study of Luxury Brand Watches in Thailand

Objective - The sales of luxury brands are escalating worldwide and are predicted to have a steady growth. However, the outbreak of COVID-19 epidemic has put a halt on world markets of luxury brand watches, providing the opportunity for the second-hand luxury watches to grow. This study aims at examining the factors impacting consumers’ social gratification of second-hand luxury brand watch. Methodology/Technique - The data were collected from two hundred members of second-hand luxury brand watches Facebook group which is a private and closed group on Facebook in Thailand. Findings – The structural equation model was conducted to analyze the results of the study. The research findings reveal several factors which significantly influence subjects’ social gratification of second-hand luxury brand watch. Novelty - The results also showed that the perceived symbolic value plays an important mediating role between the perceived experiential value and the social gratification. Type of Paper: Empirical JEL Classification: M30, M31 Keywords: Second-Hand Luxury Brand Watch, Social Gratification, Thailand Reference to this paper should be made as follows: Hansanti, P. (2022). Social Gratification and Second-Hand Fashion: An Exploratory Study of Luxury Brand Watches in Thailand, J. Mgt. Mkt. Review, 7(2), 66 – 78. https://doi.org/10.35609/jmmr.2022.7.2(2)

Wavelet Time-Scale Modeling of Brand Sales and Prices

Marketing is the way we ensure our sales are the best in the market, our prices the most accessible, and our clients satisfied, thus ensuring our brand has the widest distribution. This requires sophisticated and advanced understanding of the whole related network. Indeed, marketing data may exist in different forms such as qualitative and quantitative data. However, in the literature, it is easily noted that large bibliographies may be collected about qualitative studies, while only a few studies adopt a quantitative point of view. This is a major drawback that results in marketing science still focusing on design, although the market is strongly dependent on quantities such as money and time. Indeed, marketing data may form time series such as brand sales in specified periods, brand-related prices over specified periods, market shares, etc. The purpose of the present work is to investigate some marketing models based on time series for various brands. We will precisely study the effect of the time scale on the persistence of brand sales in the market and on the forecasting of such persistence, according to the characteristics of the brand and the related market competition or competitors. Our study is based on a sample of Saudi brands during the period 22 November 2017 to 30 December 2021.

Should you change your ad messaging or execution? It depends on brand age

Should advertisers change their message (what is said), just as they do the execution (how it is said) to reflect changing consumer preferences? This paper is the first to quantify how these ad components and their interplay affect brand sales. The authors define the concepts of market consistency and changes in ad executions and show how they interact with each other and with the brand’s age in their sales outcome. The empirical analysis confirms the hypotheses in the US minivan market. As a brand matures, executional variations become increasingly beneficial, but changing advertising messaging to remain consistent with customer preferences becomes less effective. For older brands with little executional variation, changing the ad message even reduces sales. The authors thus uncover important boundary conditions for the opposing theories that brands should ‘stick with their message’ versus ‘change with the times’ and advise how to manage advertising as the brand matures.

Implications of Digital Marketing Strategy The Competitive Advantages of Small Businesses in Indonesia

In the current era of technology, it provides many impacts and innovations that can provide more effective solutions in various fields. With digital marketing as an alternative solution, digital marketing can now overcome problems such as lack of funds and limited promotions faced by medium to low-income businesses. The alternative solution is obtained with the current social media such as Twitter, Instagram, Website, and Facebook to create brand awareness, loyalty, sales, and engagement. So the purpose of this study is to find out the use of marketing strategies from several lower-middle businesses that have gone online and their implications for the competitive advantage of these lower-middle businesses. The method used in this study uses quantitative methods with causality analysis with a population of more than 21,000,000 consumers using a non-probability sampling technique using random sampling with a total sample of 2,100 respondents. So based on the research that has been done, it was found that in marketing products with a digital strategy, 78% of the results were obtained, with the remaining 22% being factors originating from other factors such as a supply of resources, capital, and managerial professionalism.

Implications of Digital Marketing Strategy The Competitive Advantages of Small Businesses in Indonesia

In the current era of technology, it provides many impacts and innovations that can provide more effective solutions in various fields. With digital marketing as an alternative solution, digital marketing can now overcome problems such as lack of funds and limited promotions faced by medium to low-income businesses. The alternative solution is obtained with the current social media such as Twitter, Instagram, Website, and Facebook to create brand awareness, loyalty, sales, and engagement. So the purpose of this study is to find out the use of marketing strategies from several lower-middle businesses that have gone online and their implications for the competitive advantage of these lower-middle businesses. The method used in this study uses quantitative methods with causality analysis with a population of more than 21,000,000 consumers using a non-probability sampling technique using random sampling with a total sample of 2,100 respondents. So based on the research that has been done, it was found that in marketing products with a digital strategy, 78% of the results were obtained, with the remaining 22% being factors originating from other factors such as a supply of resources, capital, and managerial professionalism.

E-Tailing in Odisha: Its Expansion, Problems, Opportunities, and Development

India's retail sector is undergoing a transformation. The recent web-technique e-commerce process is still in its early stages, indicating a period of rapid change, confrontation, and opportunity in Indian retail. In the new internet-based world, e-commerce and e-marketing are two key concepts. E-commerce is a business model in which organizations and people conduct e-tailing over the internet. E-tailing, also known as internet shopping, web shopping, or online shopping, is the online promotion of products or services. E-tailing, on the other hand, is the sale of different brands over the internet. The term "e-tailing" refers to electronic retail conducted over the internet. In this present era of electronic retailing importance and market viabilities and developments, various things are discussed in this paper.

A semiparametric approach to estimating reference price effects in sales response models

It is well known that store-level brand sales may not only depend on contemporaneous influencing factors like current own and competitive prices or other marketing activities, but also on past prices representing customer response to price dynamics. On the other hand, non- or semiparametric regression models have been proposed in order to accommodate potential nonlinearities in price response, and related empirical findings for frequently purchased consumer goods indicate that price effects may show complex nonlinearities, which are difficult to capture with parametric models. In this contribution, we combine nonparametric price response modeling and behavioral pricing theory. In particular, we propose a semiparametric approach to flexibly estimating price-change or reference price effects based on store-level sales data. We compare different representations for capturing symmetric vs. asymmetric and proportional vs. disproportionate price-change effects following adaptation-level and prospect theory, and further compare our flexible autoregressive model specifications to parametric benchmark models. Functional flexibility is accommodated via P-splines, and all models are estimated within a fully Bayesian framework. In an empirical study, we demonstrate that our semiparametric dynamic models provide more accurate sales forecasts for most brands considered compared to competing benchmark models that either ignore price dynamics or just include them in a parametric way.