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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65619
Volume:
10 |
6 |
Jun 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of commerce
Government city college

Department of commerce
Government city college

Department of commerce
Government city college
Marketinghas undergone a significant transformation in recent years due to rapid technological advancements, changing consumer behaviour, and increasing concerns about sustainability. Artificial Intelligence (AI), digital influencers, and sustainable marketing strategies have emerged as key drivers reshaping modern marketing practices. Businesses are increasingly adopting AI-powered analytics to gain deeper insights into customer preferences, predict market trends, and enhance decision-making processes. At the same time, digital influencers have become powerful tools for brand promotion, customer engagement, and influencing purchase decisions through social media platforms. The present study titled “The Role of AI Analytics, Digital Influencers, and Sustainable Strategies” examines the impact of these emerging trends on contemporary marketing practices. The study focuses on understanding how AI analytics improves customer targeting, personalization, and marketing effectiveness; how digital influencers shape consumer perceptions and buying behaviour; and how sustainable marketing strategies contribute to long-term brand value and customer loyalty. The study is based on secondary data collected from research journals, industry reports, company publications, books, and online sources. It analyses the integration of advanced technologies and sustainability initiatives in marketing activities across various industries. The research also explores the opportunities and challenges associated with the adoption of AI-driven tools, influencer marketing campaigns, and environmentally responsible business practices. The findings reveal that AI analytics significantly enhances marketing efficiency through data-driven decision-making, predictive analysis, and personalized customer experiences. Digital influencers strengthen brand awareness and consumer trust by creating authentic and engaging content. Sustainable marketing strategies improve corporate reputation, customer loyalty, and long-term business performance by addressing environmental and social concerns. The study concludes that the successful integration of AI analytics, digital influencers, and sustainable marketing practices can provide organizations with a competitive advantage in the evolving business environment. The research offers valuable insights for marketers, business organizations, researchers, and policymakers in developing innovative, customer-centric, and sustainable marketing strategies for future growth and success.
KEYWORDS
The first thought and fundamental question which ignited the thesis was “how to satisfy customers with limited product differentiation?” from the extant literature the research identified key dimensions of service quality. The thesis concluded that overall service quality has a positive significant relationship with customer satisfaction. The finding was supported by other researchers Cronin CTaylor, 1992; Buttle ,1996; Koushiki Choudhury, 2010; Awantha Priyanath, 2018.Further, it was established that Tangibility, Reliability, and Responsiveness have great predictive power on customer satisfaction, implying that enhancement of these three dimensions will result in increased customer satisfaction. From 11 hypotheses 5 hypotheses have been accepted by statistical analysis, resulting in understanding the dynamic relationship of service in an enhanced way. Furthermore, the thesis was able to differentiate between different customer groups on the basis of their demographics C transactions and their influence on different dimensions of service quality. The finding of the study pointed out those female customers, old aged customers, lower income group, occasional visitors and saving accounts holders of the amazon have more impact on service quality than other groups of customers. The findings of the thesis are simple yet effective in providing services according to the customer’s preference. A service provider can easily segregate customer and serve them with their preference. Moreover, crucial dimensions of service quality had been identified by the research which can be improved and enhanced for better results. The thesis will of great interest for new amazons that will enter the market soon. Overall, the study can be replicated by amazons and financial institution. The findings of the study should be valuable as it will help in increasing customer satisfaction and ultimately increased market share. To conclude this thesis has achieved what it intended to focus, that is to understand the service quality and its dynamic relationship with customer satisfaction. It is hoped that amazons can be benefitted from the research by means of differentiating itself from others and achieve synergy between satisfaction with improved service quality.
Kumar, V., & Reinartz, W. (2020). Customer relationship management: Concept, strategy, and tools. Springer. Chatterjee, S., Rana, N. P., C Dwivedi, Y. K. (2020). The impact of artificial intelligence on customer relationship management. Journal of Business Research, 117, 1–10. Davenport, T. H., Guha, A., Grewal, D., C Bress Gott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J., Fabian, N., C Haenlein, M. (2021). Digital transformation and customer experience. Journal of Business Research, 122, 889–901. Huang, M. H., C Rust, R. T. (2021). Artificial intelligence in service. Journal of Service Research, 24(1), 3–19. Payne, A., Frow, P., C Eggert, A. (2021). The customer value proposition and CRM performance. Industrial Marketing Management, 93, 294–304. WEBSITES https://www.salesforce.com https://www.hubspot.com https://www.oracle.com https://www.microsoft.com https://www.gartner.com
Publication Date
6/29/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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