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Investigating the Effects of Emerging Technologies on AIDA and Marketing Mix in Indian Digital Marketing

Prasenjit Chakrabarty

Advances in Consumer Research2025https://doi.org/10.61336/acr/25-04-05article
AJG 2ABDC B
Weight
0.37

Abstract

This research examines how emerging technologies—especially artificial intelligence (AI) and machine learning (ML)—influence digital marketing outcomes in India’s Over-the-Top (OTT) media sector. OTT refers to streaming services delivered directly to viewers via the internet, bypassing traditional broadcast platforms. The study explores the effectiveness of digital marketing communication through the lens of the AIDA model, which tracks customer journey stages: Attention, Interest, Desire, and Action. Using a structured questionnaire with a sample of 506 OTT subscribers in India, the study measured consumer responses to key marketing variables such as brand recall, promotional timing, customer support quality, pricing, and content type. We analyzed responses using regression methods and machine learning tools like SHAP (Shapley Additive Explanations), which reveal how much each factor contributed to the outcome. Findings show that effective customer support and ease of access strongly influence consumer attention, while brand recognition and timely promotions impact purchase decisions. Interestingly, price sensitivity plays a role—but only within certain limits. This study offers practical insights for digital marketers operating in India’s crowded OTT market. It suggests that success lies in blending emotional triggers like brand trust with functional aspects like content delivery and support. By aligning strategies with data-driven insights, marketers can improve both customer acquisition and retention

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https://doi.org/https://doi.org/10.61336/acr/25-04-05

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@article{prasenjit2025,
  title        = {{Investigating the Effects of Emerging Technologies on AIDA and Marketing Mix in Indian Digital Marketing}},
  author       = {Prasenjit Chakrabarty},
  journal      = {Advances in Consumer Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.61336/acr/25-04-05},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.