Sentiment-based predictive models for online purchases in the era of marketing 5.0: a systematic review

Gooljar, Veerajay; Issa, Tomayess; Hardin-Ramanan, Sarita; Abu-Salih, Bilal

doi:10.1186/s40537-024-00947-0

J Big Data

2024

DOI: 10.1186/s40537-024-00947-0

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Sentiment-based predictive models for online purchases in the era of marketing 5.0: a systematic review

Veerajay Gooljar,

Tomayess Issa,

Sarita Hardin-Ramanan

et al.

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2024

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Cited by 2 publications

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Digital Transformation of Grocery In-Store Shopping-Scanners, Artificial Intelligence, Augmented Reality and Beyond: A Review

Wolniak,

Stecuła,

Aydın

2024

Foods

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This paper reviews the digital transformation of grocery shopping, focusing on the technological innovations that have redefined consumer experiences over the past decades. By analyzing both academic literature and up-to-date information from websites, the study provides a review of the evolution of grocery shopping from traditional methods to modern, technology-driven approaches. The review categorizes developments into two primary areas: in-store and online grocery shopping. In-store shopping has progressed from traditional interactions to the implementation of self-service checkouts, handheld scanners, mobile apps, and AI-based solutions, including augmented reality (AR) and facial recognition. This paper reviews the first area which are in-store technological solutions. This study aims to highlight the revolution in grocery shopping from a technological perspective, present the most significant digital achievements, and outline the future possibilities for further advancements in this field.

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Digital Transformation of Grocery In-Store Shopping-Scanners, Artificial Intelligence, Augmented Reality and Beyond: A Review

Wolniak,

Stecuła,

Aydın

2024

Foods

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Marketing digital y la personalización basada en inteligencia artificial

Pazmiño Arellano,

Pazmiño Rodríguez

2024

RCK

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El uso de la inteligencia artificial y sus implicaciones en la relación entre las marcas y el consumidor es igualmente un punto que marca la evolución. Por supuesto, la inteligencia artificial ha elevado la experiencia del consumidor, lo que solo puede ayudar a aumentar las estrategias de marketing. Tal alteración se realiza principalmente a través de la aplicación de numerosos algoritmos de esta inteligencia que logran superar las complejidades que se generan alrededor del patrón de comportamiento del consumidor. Hay una transición en el enfoque entre el trabajo y el consumidor, ya que la monitorización y optimización en tiempo real de la satisfacción del consumidor puede incluir elementos como análisis predictivos, codificación facial o métodos interactivos, predictivos y asistidos por animación. Este documento describe la personalización como un objetivo general en el comercio electrónico, con una descripción más detallada que incluye algunos cubos de comportamiento, emoción y cognición del consumidor. Tal comprensión amplia de la personalización también se basa en el análisis extenso de la literatura de arte económico cuyos trabajos son densos en el procesamiento moderno del lenguaje y algoritmos de aprendizaje automático para explicar cómo y por qué los consumidores actúan de la manera en que lo hacen. El gran reto que enfrentan, a su vez, se centra en la creación e implantación de estrategias de personalización que sean efectivas y que, además (y, quizás, lo que sería más importante), sean pertinentes en la pluralidad del entorno del marketing actual.

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Sentiment-based predictive models for online purchases in the era of marketing 5.0: a systematic review

Cited by 2 publications

References 172 publications

Digital Transformation of Grocery In-Store Shopping-Scanners, Artificial Intelligence, Augmented Reality and Beyond: A Review

Digital Transformation of Grocery In-Store Shopping-Scanners, Artificial Intelligence, Augmented Reality and Beyond: A Review

Marketing digital y la personalización basada en inteligencia artificial

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