Academic literature on the topic 'CUSTOMISED ADVERTISEMENTS'

Retargeting is a type of online advertising in which the consumer's previous activities are used to target them. In this paper it reflects the “impact of behavioural retargeting on the purchase pattern of consumers Using this relatively new method, businesses can now give customers customised recommendations in real time when they visit their websites, allowing them to remember their intents and possibly persuading them to make a purchase. This paper study the change in purchase pattern of the customers and it was found that the behavioural change is not influenced by retargeting advertisements.

Existing digital signage advertisements send advertisements to unspecified people, so there is a limit to the advertisement exposure effect, and it is very difficult to analyze advertisement effects because several advertisements are repeatedly exposed for a certain period of time. This paper proposes an AI digital signage system that automatically analyzes the user hierarchy based on deep learning and displays customized advertisements to users. For this, a system that learns the face of an ad viewer is built using a convolutional neural network. For preliminary training, we used face images from Korean face image data, and layered them into six using the gender and age information provided. The facial features of these pictures were quantified using a convolutional neural network, and these values were stored in a database for learning. Real-time automatic hierarchy was tested using the data set produced in this way, and the success rate was between 84% and 95% for each hierarchy. It is thought that a system with a higher success rate can be created if the user hierarchy learning model learns images of various face poses and collects and learns data used in the automatic classification process through tracking.

Location-Based Systems enable novel business models that can locate a person and send an action or message to him/her. One of the most commonly adopted location-based business models is location-based advertisements. Companies can send customized messages to target customers by using location-based ads. The model is promising since the conversion rate of the customers is high. On the other side, since the customers can be targeted based on their locations and interests, the price of the advertisement should be modeled a dynamic pricing model. In this study, we propose a dynamic pricing model for location-based ads by using the Spherical Fuzzy AHP method.

Applying bleeding edge courses of action in advertising is always a case on the table of decision makers. In online case, lack of a practice to place right advertisement in a right time for the right user has been counted as biggest challenage. On the other hand, “ad clutter”, the key criticism on online advertising; is about to put online advertisement's benefits away and annoying users more than before. Accordingly, this article aims at scrutinizing this critical problem by incorporating one of the next generation technologies, Lead Generation. This study introduces an e-business framework in advertisement intermediating in the form of a framework so that lets advertisers advertise in customized way. In this approach, the authors focused on displaying a personalized ad for each user by which marketers could redirect their visiting prospects into becoming their own consumers. At the end, the managerial implications are reported.

With advancements in information and communication technology, a lot of changes have come in the way the products are being promoted by the marketers across the globe. Viral marketing incites the consumers to disseminate marketing content through various modes and one of which includes viral advertisements. The study analysed the content of global advertisements to explore the dominating factors in the ad content which makes them viral across the globe. Survey was conducted online among the respondents of Indian and American origin for measuring the effectiveness of the dominating elements on brand attitude and respondents’ intentions to purchase the advertised brand and to share the corresponding advertisements. Structural equation modeling (SEM), a multivariate technique, was used on two samples to measure effectiveness of advertising content across two countries. The content analysis results show that although a standardized advertising strategy is used across the global level, but as indicated by the distinctions revealed from the empirical analysis of choices of two cultures, it can be inferred that advertisement should be fairly similar across the different cultures. The study leaves an implication for the advertisers to customize their advertising content in compliance with the uniqueness of culture in different countries.

Classified advertisement sites often follow two different approaches to filter classified advertisement data to customers and potential customers. The first approach is to reach out to the broader market, allowing the customers to filter to their target market on the classified website. The downside of this approach is that it lacks the customization and specialization people in a niche market tend to prefer. The second approach is to create classified advertisement websites that are customized to meet the needs of a target or niche market. This specialization is more appealing to niche market customers. However, the second approach is more focused. Therefore, the customer base is smaller, and expanding to more markets requires building more websites, which can be costly in time, money and effort. In this paper the authors propose a framework that allows website developers to quickly and efficiently create targeted market websites. The framework proposed enables website developers to quickly customize text, context and features offered on the newly created targeted market website. In addition, the framework overcomes the entry barrier new websites face by obtaining the starting classified listings required to make a new classified website viable to potential buyers and sellers.

PurposeThe purpose of this paper is to examine the effectiveness of a targeted email advertising method that informs university students about library resources relevant to their major.Design/methodology/approachOver the course of one semester, students with business and communications majors who reserved group study rooms received customized confirmation emails that included targeted advertisements for library databases. These advertisements invited students to click a link that led to a database related to a student's major. Near the end of the semester, students were invited to complete a short survey about the advertisements. Survey questions were designed to discover whether the advertisements were seen and to measure database relevancy. The survey also gathered participant perceptions about the value of this targeted awareness advertising approach.FindingsOverall, the technique of appending database advertisements to reservation emails proved ineffective; very few students recalled seeing the advertisements or clicking the links. On the positive side, this study showed that very few of the survey respondents disapproved of receiving advertisements. Another positive result was that a majority indicated the selected library databases were relevant to their needs. Respondents also offered suggestions for improving this marketing technique.Originality/valueThis research introduces a novel, unobtrusive approach to advertising library resources to a targeted audience. The results can be used by library administrators as a starting point for experimenting with similar (yet improved) methods of sharing information about relevant library resources with specific user populations.

O presente artigo tem por objetivo analisar a resposta de usuários do YouTube à existência de propaganda inserida dentro do conteúdo de vídeosPara se chegar a tal objetivo foi realizada uma pesquisa exploratória e qualitativa através do método netnográfico. Como principais resultados foi observado que existem cinco modelos utilizados pelos produtores de conteúdo para a inserção de propagandas no conteúdo de vídeos. Os modelos com maior resposta por parte dos usuários foram aqueles que apresentavam o produto por um período maior de tempo. Sendo que as propagandas que apresentaram uma resposta mais positiva dos usuários foram aquelas que geraram informação, entretenimento ou eram customizadas para o público que as assistiram.
 
 PALAVRAS-CHAVE: YouTube; Propaganda; Netnografia.
 
 
 ABSTRACT
 This article purpose to analyze the response of YouTube users to advertisement inserted within the content of videos. To reach this aim, an exploratory and qualitative research was carried out through the netnographic method. As main results it was perceived that there are five models used by content producers for the insertion of advertisements in the content of videos. The models with the highest response from users were those who presented the product for a longer period of time. Since the advertisements that presented a more positive response from the users were those that generated information, entertainment or were customized for the audience that attended them.
 
 KEYWORDS: YouTube; Advertising; Netnography.
 
 
 RESUMEN
 El presente artículo tiene como objetivo analizar la respuesta de usuarios de YouTube a propagandas insertadas em el contenido de videos. Para llegar a tal objetivo se realizó una investigación exploratoria y cualitativa por médio del método netnográfico. Como principales resultados se observó que existen cinco modelos utilizados por los productores de contenido para la inserción de propagandas en el contenido de los vídeos. Los modelos con más respuesta por parte de los usuarios fueron aquellos que presentaban el producto por un período mayor de tiempo. Siendo que las propagaciones que presentaron una respuesta más positiva de los usuarios fueron aquellas que generaron información, entretenimiento o eran personalizadas al público que las asistieron.
 
 PALABRAS CLAVE: YouTube; publicidad; Netnografía.

In response to consumer demand for personalized content, the customized cosmetics market continues to grow, centering on the beauty industry. This study was conducted to find out the awareness and brand awareness of customized cosmetics. From February 2023, a total of 313 adult men and women residing in Korea were surveyed on the degree of awareness of customized cosmetics, domestic and foreign brand awareness and use experience, evaluation of major brands of customized cosmetics, and expectations. Statistical analysis was performed on the data collected after the survey using SPSS version 25.0 for Windows. As a result, the recognition level of customized cosmetics was 'normal' (45.4%), and the product path was 'online advertisement' (42.8%), 'new purchase and plan to use' of customized cosmetics (62.6%), and product purchase and use plan. As for the place, 'online shopping mall' (46.3%) accounted for a high proportion. Brand recognition and usage status at home and abroad was 'know' (53.6%), the number of recognized brands was 'more than 4' (53.0), and the evaluation of domestic and foreign brand image was very high as 'positive' (80.7%). In terms of product diversity, 'satisfaction' (68.6%) was found to be high. The experience of purchasing and using domestic and foreign brands for customized cosmetics was higher than that of foreign brands, showing a significant difference. As for the purchase of customized cosmetics and the level of expectation for domestic and foreign brands, the expectation level was high with 'expectation' for domestic brands (92.9%) and 'expectation' for foreign brands (94.8%). As a result of comparative analysis by classifying groups according to general characteristics, the degree of recognition of customized cosmetics and intention to purchase showed significant differences in part according to gender, residential area, and final education level. Domestic and foreign brand awareness and experience of customized cosmetics, and expectations for customized cosmetics showed differences according to gender, region of residence, and final education level. Therefore, based on these results, it can be applied as basic data for research on the activation of customized cosmetics.

As the amount of sales increases rapidly, amount of data become very huge, and the management of customers’ relationship also becomes a more complex problem. Using data mining to analyze data to discover the rules and knowledge among them so that customized services in electronic commerce could be sustained and enterprises’ sales could be more intelligential. With data mining, we can do the following things. Firstly, it analyzes the customers’ shopping behavior and preference with association rules so that it can provide the recommending in the shopping process to make customers getting the right goods more convenient and faster. Secondly, it uses decision tree to classify the customers so that it makes a better communication between customers, provides customized shopping user interface to them and gives the pertinent advertisement to them.