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The performance of behavioral targeting (BT) mainly relies on the effectiveness of user classification since advertisers always want to target their advertisements to the most relevant users. In this paper, the authors frame the BT as a user classification problem and describe a machine learning–based approach for solving it.

To perform such a study, two major research questions are investigated: the first question is how to represent a user’s online behavior. A good representation strategy should be able to effectively classify users based on their online activities. The second question is how different representation strategies affect the targeting performance. The authors propose three user behavior representation methods and compare them empirically using the area under the receiver operating characteristic curve (AUC) as a performance measure.

The experimental results indicate that ad campaign effectiveness can be significantly improved by combining user search queries, clicked URLs and clicked ads as a user profile. In addition, the authors also explore the temporal aspect of user behavior history by investigating the effect of history length on targeting performance. The authors note that an improvement of approximately 6.5% in AUC is achieved when user history is extended from 1 day to 14 days, which is substantial in targeting performance.

This paper confirms the effectiveness of BT on user classification and provides a validation of BT for Internet advertising.

The influence of technology on marketing communications is rising in both applications and value created. Artificial intelligence (AI) and, as a result, smart speakers are benefiting both brands and customers at many levels. In particular, AI opens up the possibility to establish human-like dialogs with customers and to advertise brands in a new and engaging way. Therefore, the purpose of this paper is to understand why and how consumers would accept receiving advertising (ad) via AI-enabled devices such as smart speakers.

A total of 326 individuals participated in a study that explored the factors influencing ad acceptance in smart devices. A partial least squares-structural equation model technique was used to validate the results.

The findings show that customer acceptance of ads via smart assistants is influenced by smart assistant usefulness and hedonic motivations. However, privacy risk moderates the relationship between smart speaker ease of use and smart speaker usefulness.

This paper explores the main drivers of ad acceptance via smart speakers and goes beyond the existing knowledge of smart speaker acceptance to further explore how this can become an important channel for brands to communicate.

La influencia de la tecnología en las comunicaciones de marketing está aumentando tanto en las aplicaciones desarrolladas como en el valor creado. La inteligencia artificial (IA) y, en consecuencia, los altavoces inteligentes están beneficiando tanto a las marcas como a los clientes a muchos niveles. En particular, la IA abre la posibilidad de establecer diálogos similares a los humanos con los clientes y de publicitar las marcas de una manera nueva y atractiva. Por lo tanto, es necesario entender por qué y cómo los consumidores aceptarían recibir publicidad (anuncios) a través de dispositivos con IA, como los altavoces inteligentes.

Un total de 326 personas participaron en un estudio que exploró los factores que influyen en la aceptación de la publicidad en los dispositivos inteligentes. Se utilizó una técnica PLS-SEM para validar los resultados.

Los resultados muestran que la aceptación de los anuncios a través de los asistentes inteligentes por parte de los clientes está influenciada por la utilidad del asistente inteligente y las motivaciones hedónicas. Sin embargo, el riesgo para la privacidad modera la relación entre la facilidad de uso del altavoz inteligente y su utilidad.

El artículo explora los principales impulsores de la aceptación de la publicidad a través de los altavoces inteligentes y va más allá del conocimiento existente sobre la aceptación de los altavoces inteligentes para explorar más a fondo cómo esto puede convertirse en un canal importante para que las marcas se comuniquen.

科技对营销传播的影响在应用和价值创造方面都在上升。人工智能（AI）以及智能音箱在很多层面都对品牌和客户有益。尤其是, 人工智能开辟了与客户建立类似人类对话的可能性, 并以一种新颖的、有吸引力的方式宣传品牌。因此, 了解消费者为什么以及如何接受通过人工智能设备（如智能音箱）接收广告（广告）是有必要的。

本研究的326名参与者探讨了影响智能设备中广告接受度的因素。PLS-SEM技术被采用以对结果进行验证。

研究结果显示, 客户通过智能助手接受广告会受智能助手有用性和享乐动机的影响。然而, 隐私风险调节了智能音箱的易用性和智能音箱的有用性之间的关系。

本文探讨了通过智能音箱接受广告的主要驱动因素, 并超越了现有的关于智能音箱接受度的知识, 进一步探讨了这如何能成为品牌沟通的重要渠道。

This paper aims to investigate advertising effectiveness in Instagram and Facebook, the two most important social media platforms. It helps to understand which should be chosen depending on the target audience of the campaign.

The study examines advertising effectiveness in these social media in terms of ad attitude, ad intrusiveness and loyalty intentions. An online survey was conducted with 303 social media users. Age and gender are proposed as moderators.

The results indicate that Instagram Stories not only enhances consumer attitude toward ads but also increases perceived intrusiveness, compared to Facebook Wall. Millennials are more disturbed by Facebook Wall ads than non-millennial users. A triple interaction effect reveals that non-millennial men are more loyal toward Facebook Wall ads, whereas millennials of both genders and non-millennial women are more loyal to ads on Instagram Stories.

Advertisers should be aware of the differential features and segmentation possibilities in social media to better address their target audiences. More precisely, the research findings suggest that professionals should focus on Instagram Stories when targeting millennials and non-millennial women, and on Facebook Wall when targeting non-millennial men.

This study is one of the first to contribute to the literature on Instagram Stories as an advertising platform and compare its differential features with those of more established social media, such as Facebook Wall.

Esta investigación compara la efectividad publicitaria en Instagram y Facebook en función del público objetivo.

La investigación analiza las diferencias entre cada formato de red social en términos de actitud hacia el anuncio, intrusividad percibida y lealtad hacia el producto o marca anunciado. Mediante una encuesta online a 303 consumidores, se proponen efectos directos y efectos moderación de la edad y el género.

Los resultados indican que Instagram Stories mejora la actitud hacía el anuncio, pero aumenta también la intrusividad en comparación con Facebook Wall. La publicidad en Facebook Wall es más intrusiva para los millennials que para los no-millennials. Instagram Stories incrementa la lealtad entre los usuarios millennial de ambos sexos y las mujeres no-millennial; en cambio, los hombres no-millennial son más leales a la publicidad en Facebook Wall.

Los anunciantes deben aprovechar los nuevos formatos y las posibilidades de segmentación que les brindan las redes sociales para llegar a su público objetivo de manera más efectiva. Concretamente, los hallazgos de la investigación sugieren que deberían centrarse en Instagram Stories para dirigirse a un público millennial y a mujeres no-millennial; y en Facebook Wall, cuando su público objetivo sean los hombres no-millennial.

Este estudio es uno de los primeros que aborda el uso de Instagram Stories como soporte publicitario y lo compara con formatos publicitarios consolidados como Facebook Wall.

The purpose of this paper is to provide comprehensive, theoretical and practical knowledge that will assist decision-makers in making informed decisions when promoting several religious sites in the Kingdom of Saudi Arabia (KSA). Specifically, this study examines the popularity of several religious sites, the personas of prospective visitors and their intentions to visit.

The study uses several methodological approaches to fulfil its main objective, namely, Google Trends analysis, K-means cluster analysis and linear regression analysis.

The results reveal that several religious sites in the KSA are popular and have potential for further consideration by various stakeholders. In addition, four personas were identified which can aid decision-makers and marketing practitioners in designing suitable plans for prospective visitors based on the participants’ motivation and demographics. Furthermore, a significant association was observed among three motivational variables (self-esteem, relationship and physiological needs) and the participants’ intentions to visit.

This study makes an original contribution to the literature, as it examines several religious sites in Saudi Arabia in addition to the sites that are part of the practices of Hajj and Umrah. Furthermore, this study provides comprehensive knowledge in this area to assist both future researchers and practitioners.

The purpose of this study is to examine the different results and the level of success obtained with advertising campaigns developed on Facebook to promote postgraduate programs to create awareness and engagement.

This study combined the data envelopment analysis technique to measure advertising efficiency with multidimensional scaling (MDS) representation, thus offering alternatives for practitioners and organizations on how to evaluate social advertising performance.

Investments on social paid advertising are an affordable and effective way both to promote postgraduate programs and create engagement with prospective students. Facebook advertisements maximize visibility, which improves social and online positioning and encourages student recruitment.

Higher education institutions can efficiently promote their programs with a minimal social investment contributing to dissemination and engagement. Compared to other forms of traditional or digital advertising, social media ads can be efficient and affordable with wider segmentation and targeting options. Moreover, results are immediate and measurable and campaigns can be instantly modified to better suit the audience’s requirements.

This study is unique as it offers a new, alternative way of measuring efficiency, in addition to the classic ratios of payment models in digital advertising that combine clicks and impressions, on a sector where there are few empirical studies. Moreover, it can be easily applied to many other sectors in public and private organizations.

El objetivo de esta investigación es examinar los diferentes resultados y el nivel de éxito obtenido con las campañas publicitarias desarrolladas en Facebook para promover programas de postgrado que aumenten la notoriedad y la participación de los mismos.

Combinamos la técnica de análisis de envolvente de datos (DEA) para medir la eficiencia de la publicidad con la representación de escalado multidimensional (MDS), ofreciendo alternativas tanto a profesionales como a organizaciones sobre cómo evaluar el rendimiento de la publicidad social.

Las inversiones en publicidad social pagada son una forma asequible y efectiva tanto para promover programas de postgrado como para crear un compromiso con los posibles estudiantes. Los anuncios en Facebook maximizan la visibilidad, lo que también mejora el posicionamiento social y en línea, fomentando la captación de estudiantes.

Las instituciones de educación superior pueden promover eficazmente sus programas con una inversión social mínima que contribuya a la difusión y el engagement. En comparación con otras formas de publicidad tradicional o digital, los anuncios de los medios sociales pueden ser eficientes y asequibles, con una segmentación y opciones de orientación más amplias. Además, los resultados son inmediatos y cuantificables y las campañas pueden modificarse instantáneamente para adaptarse mejor a las necesidades del público objetivo.

Esta investigación es única ya que ofrece una nueva y alternativa forma de medir la eficiencia, además de los ratios clásicos de los modelos de pago en la publicidad digital que combinan clics e impresiones, en un sector en el que hay pocos estudios empíricos. Además, puede aplicarse fácilmente a muchos otros sectores en organizaciones públicas y privadas.