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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in April 2026 (Volume 30, Issue 1) Submit manuscript

Rethinking black Friday: How Ai can drive 'small batch' personalized deals

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  • Rethinking black Friday: How Ai can drive 'small batch' personalized deals

Anthonette Adanyin *

Department of Artificial Intelligence, University of Wolverhampton, United Kingdom.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(01), 2913-2924
Article DOI: 10.30574/wjarr.2024.21.1.2611
DOI url: https://doi.org/10.30574/wjarr.2024.21.1.2611
 
Received on 07 December 2023; revised on 25 January 2024; accepted on 28 January 2024
 
This paper discusses how Artificial Intelligence can revolutionize the traditional Black Friday retail event by making personalized deals in 'small batches'. In the ever-changing retail landscape due to changed consumer behavior and the technological advancement of emerging technologies, this study probes how AI-driven personalization can further drive effective and customer-centric promotional strategies.
The paper begins by putting into perspective the evolution of Black Friday from a one-day event into an extended shopping period, noting the shortcomings that retailers find themselves facing regarding inventory management, demand forecasting, and profitability of large-scale promotions. These challenges require innovative solutions; AI-powered personalization has become a solution.
A critical review of AI applications in retail and personalization with the 'small batch' deal capability, facilitated by AI algorithms, can provide personalized offers to individual customers or small micro-segments in correspondence with their preferences and behaviors. Some salient features of this approach include hyper-personalization, dynamic pricing, and contextual relevance ingredients for precision targeting and engagement.
The paper details the technical implementation involved in AI-powered deals to help draw insights into data collection, management, and the algorithms at play in driving personalization. It also categorically helps in considering several critical ethical and consumer privacy concerns that businesses must pursue in integrating AI in retail. Case studies of Nike, Nordstrom, and Best Buy illustrate how AI-driven personalization enhances customer engagement, increases conversion rates and boosts sales performance.
It takes into consideration some of the challenges considered, from technical limitations to data quality, and balancing personalization with inclusivity after potential solutions and best practices are reviewed. The future of retail personalization is considered, anticipating that continuous, year-round personalized shopping experiences will shift the need away from traditional events like Black Friday.
In all, AI-driven 'small batch' deals promise a glittering future of Black Friday and retail promotions with the capability of offering more relevant and profitable experiences to shoppers. This paper adds to the emergent literature on AI in retail and gives practical insights into advanced personalization that retailers might want to implement. Future research areas are also identified, such as the long-term effects of hyper-personalization and the ethical implications of AI in retail.
 
Artificial intelligence; Black Friday; Marketing; Retail
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2023-2611.pdf

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Anthonette Adanyin. Rethinking black Friday: How Ai can drive 'small batch' personalized deals. World Journal of Advanced Research and Reviews, 2024, 21(1), 2913-2924. Article DOI: https://doi.org/10.30574/wjarr.2024.21.1.2611

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