The Future of Indirect Marketing in a Digital World
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Date
2024-09-27
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University of Sussex
Abstract
This dissertation explores the transformative impact of digital technologies on indirect
marketing strategies, focusing on how businesses adapt to the evolving digital landscape.
The study aims to assess the roles of artificial intelligence (AI), big data, and the Internet
of Things (IoT) in enhancing indirect marketing, with a specific focus on consumer
behaviour and brand loyalty.
The research methodology is based on secondary data analysis, drawing from academic
journals, industry reports, and case studies. This approach allows for a comprehensive
examination of current trends and technologies affecting marketing practices across
various industries.
The main findings indicate that AI, big data, and IoT significantly enhance marketing
effectiveness by improving customer targeting, personalization, and real-time
engagement. These technologies have enabled businesses to create more meaningful
consumer interactions, leading to increased customer loyalty and higher marketing ROI.
The integration of these technologies provides a synergistic effect that amplifies their
individual benefits.
In conclusion, the dissertation underscores the critical role of digital technologies in
shaping modern marketing strategies. The study highlights the importance of adopting
these technologies to remain competitive in a digital-first marketplace while addressing
challenges such as data privacy and the need for skilled personnel. These insights offer
valuable guidance for future research and practical application in the field of digital
marketing.
Description
This study has thoroughly explored the influence of consumer behaviour and digital
technology on indirect marketing strategies through secondary data analysis. By
leveraging a wide array of secondary sources—including academic journals, industry
reports, case studies, and authoritative online publications—the research has provided a
detailed and nuanced understanding of the role of artificial intelligence (AI), big data, and
the Internet of Things (IoT) in shaping contemporary marketing strategies. The chosen
sources were carefully selected for their credibility and relevance, ensuring that the data
reflected the latest trends and developments in the field.
Secondary data analysis has proven to be a cost-effective and time-efficient approach,
allowing for the examination of a broad spectrum of data without the need for primary
data collection. This method facilitated access to extensive datasets and high-quality.
information from reputable sources, which was instrumental in drawing comprehensive
insights into the research questions. Despite its advantages, secondary data analysis
comes with certain limitations. These include potential misalignment between the data
and specific research objectives, limited control over the original data collection
processes, and possible biases inherent in the sources. Nonetheless, the methodology
successfully provided a rich foundation of information, contributing valuable insights into
how digital technologies impact indirect marketing strategies.
Keywords
Indirect Marketing, Digital Transformation, Artificial Intelligence (AI), Consumer Engagement, Brand Loyalty