Retail Cloud AI Strategies: Balancing Cost, Speed, and Customer Satisfaction in a Digital Landscape

Authors

  • Venkata Nagendra Kumar Kundavaram IT Manager | Goodwill Easter-Seals Minnesota| Davidson, NC, USA. Author

DOI:

https://doi.org/10.63397/ISCSITR-IJCC_2024_05_02_003

Keywords:

Retail AI, Cloud Strategy, Digital Transformation, Cost Optimization, Customer Experience, Cloud Architecture, Retail Analytics, AI-driven Personalization, Smart Retail

Abstract

In the rapidly evolving digital economy, the retail sector is leveraging Cloud and Artificial Intelligence (AI) technologies to optimize operations, reduce costs, enhance speed, and improve customer satisfaction. This paper explores strategic frameworks for implementing AI-driven cloud solutions tailored to retail businesses. It provides a comparative analysis of different cloud-AI strategies focusing on their impact on operational efficiency, customer experience, and scalability. The paper also presents real-world use cases, architectural designs, and decision-making frameworks, helping retailers to strike the right balance among cost, speed, and customer satisfaction. A thorough literature review contextualizes the research within current and prior technological developments up to 2023. Graphical models, infographics, and charts further illustrate core ideas, facilitating practical understanding and implementation.

References

Kim, D., & Kim, M. (2022). Retail innovation using cloud AI: A framework for customer value enhancement. Journal of Retail Analytics, 18(4), 45–60. https://doi.org/10.1016/j.jretail.2022.04.005

Ahmed, S., & Goyal, R. (2021). Impact of AI-powered cloud services on retail supply chains. International Journal of Logistics Systems, 10(2), 88–101. https://doi.org/10.1504/IJLSM.2021.117420

Zhang, Y., & Li, P. (2020). Cloud-edge collaboration for smart retail: Opportunities and challenges. IEEE Cloud Computing, 7(3), 45–55. https://doi.org/10.1109/MCC.2020.2991982

Kumar, A., & Sinha, R. (2023). Customer experience analytics in retail using cloud-based AI systems. International Journal of Consumer Studies, 47(1), 34–46. https://doi.org/10.1111/ijcs.12895

Nandhini, R., & Thomas, G. (2021). AI-driven personalization in retail: A cloud perspective. International Journal of Retail & Distribution Management, 49(7), 811–829. https://doi.org/10.1108/IJRDM-01-2021-0020

Liu, X., & Wang, H. (2022). Evaluating the ROI of cloud-based AI investments in retail. Journal of Business Research, 139, 508–517. https://doi.org/10.1016/j.jbusres.2021.09.059

Singh, P., & Roy, A. (2023). Cloud-native AI systems for retail forecasting and recommendation. ACM Transactions on Internet Technology, 23(2), Article 27. https://doi.org/10.1145/3491297

Ferreira, D., & Santos, A. (2020). Serverless computing for scalable AI services in retail. Future Generation Computer Systems, 109, 493–504. https://doi.org/10.1016/j.future.2019.07.011

Sharma, R., & Gupta, M. (2019). AI and cloud computing synergy: A roadmap for digital retail transformation. Journal of Retail Technology, 5(3), 101–114. https://doi.org/10.1016/j.jrettec.2019.05.001

Zuo, Y., & Zhang, T. (2021). A comparative study of cloud AI platforms for enterprise retail applications. Computers in Industry, 130, 103448. https://doi.org/10.1016/j.compind.2021.103448

Davis, J. M., & Lee, K. (2020). Accelerating customer-centric innovation in retail through AI and cloud adoption. Harvard Business Review, 98(4), 75–82.

Chowdhury, A., & Roy, S. (2023). Leveraging cloud-based AutoML tools for customer behavior prediction. Expert Systems with Applications, 208, 118221. https://doi.org/10.1016/j.eswa.2022.118221

Mishra, N., & Dey, L. (2022). Real-time cloud analytics for retail pricing using AI models. International Journal of Information Management, 63, 102444. https://doi.org/10.1016/j.ijinfomgt.2021.102444

Patel, V., & Rao, K. (2021). Secure data handling in cloud AI environments for retail personalization. Computer Security, 103, 102152. https://doi.org/10.1016/j.cose.2021.102152

Lin, S., & Chou, M. (2018). Customer sentiment analysis using cloud NLP services in omnichannel retail. Journal of Retailing and Consumer Services, 43, 262–270. https://doi.org/10.1016/j.jretconser.2018.04.006

Alam, M., & Khatun, F. (2019). Edge computing in AI-enhanced retail: A hybrid model. IEEE Internet of Things Journal, 6(3), 4973–4981. https://doi.org/10.1109/JIOT.201

Downloads

Published

2024-09-08

How to Cite

Retail Cloud AI Strategies: Balancing Cost, Speed, and Customer Satisfaction in a Digital Landscape. (2024). ISCSITR-INTERNATIONAL JOURNAL OF CLOUD COMPUTING (ISCSITR-IJCC) - ISSN (Online): 3067-7378, 5(2), 26-42. https://doi.org/10.63397/ISCSITR-IJCC_2024_05_02_003