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<p>The marketing sphere has shifted from mass broadcast strategies to highly customized, data-driven strategies fueled by advanced analytics, especially in fast digitizing countries such as India, in an era characterized by digital transformation and omnipresent connectivity. The goal of this study is to analyze the way in which organizations are using complex analytics in custom-made marketing to enhance customer involvement, address organizational and ethical challenges, and establish a framework for improved performance, personalization and privacy. Quantitative surveys with 300 Indian consumers and qualitative interviews with 15–20 marketing experts are estimated to be used in the study using a mixed-methods approach. While the data analysis was done using SPSS, AMOS and NVivo. On confirming the measurement strength, the results reveal that the constructs have excellent internal consistency and validity – Cronbach’s α prediction is between 0.80 and 0.90, the CR values range between 0.84 and 0.92, and all AVEs are over 0.50. Further, Perceived Relevance has significant correlations with Personalization (<i>r</i> = 0.72**), Real-time Responsiveness (<i>r</i> = 0.70**) and Customer Engagement (<i>r</i> = 0.76**). Thus, we can confirm the central mediating role of Perceived Relevance. The relationships of the paths specified in the conceptualized model were all established when running SEM. Perceived Relevance was found to be significantly influenced by Personalization (β 0.44), Real-time Responsiveness (β 0.42) and Data Analytics Capability (β 0.39). The most significant, direct influence of Perceived Relevance is on Customer Engagement, with standardised regression weighting (β 0.67, CR 16.75, <i>p</i> &lt; 0.001). These findings signify the validation of the Integrated Smart Marketing Model.</p>

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Smart marketing in the data age: personalization meets advanced analytics

  • 期刊论文

  • 发表日期：

    2026年5月13日

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  • Priya Sachdeva,
  • Archan Mitra,
  • Prachi Malhotra,
  • Rakesh Prakash,
  • P.V. Satya Prasad,
  • Kaushik Mishra

摘要

The marketing sphere has shifted from mass broadcast strategies to highly customized, data-driven strategies fueled by advanced analytics, especially in fast digitizing countries such as India, in an era characterized by digital transformation and omnipresent connectivity. The goal of this study is to analyze the way in which organizations are using complex analytics in custom-made marketing to enhance customer involvement, address organizational and ethical challenges, and establish a framework for improved performance, personalization and privacy. Quantitative surveys with 300 Indian consumers and qualitative interviews with 15–20 marketing experts are estimated to be used in the study using a mixed-methods approach. While the data analysis was done using SPSS, AMOS and NVivo. On confirming the measurement strength, the results reveal that the constructs have excellent internal consistency and validity – Cronbach’s α prediction is between 0.80 and 0.90, the CR values range between 0.84 and 0.92, and all AVEs are over 0.50. Further, Perceived Relevance has significant correlations with Personalization (r = 0.72**), Real-time Responsiveness (r = 0.70**) and Customer Engagement (r = 0.76**). Thus, we can confirm the central mediating role of Perceived Relevance. The relationships of the paths specified in the conceptualized model were all established when running SEM. Perceived Relevance was found to be significantly influenced by Personalization (β 0.44), Real-time Responsiveness (β 0.42) and Data Analytics Capability (β 0.39). The most significant, direct influence of Perceived Relevance is on Customer Engagement, with standardised regression weighting (β 0.67, CR 16.75, p < 0.001). These findings signify the validation of the Integrated Smart Marketing Model.