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The Role of Machine Learning in Digital Marketing

Author

Listed:
  • Mithun S. Ullal
  • Iqbal Thonse Hawaldar
  • Rashmi Soni
  • Mohammed Nadeem

Abstract

Artificial Intelligence has been under researched. Machines with deep learning abilities can take digital marketing to new heights with their Artificial Intelligence making all the difference. This research aims to identify the outcomes from the study of Indian customer’s responses across varying demographics to machines and their abilities to sell, which will well be the future of digital marketing. We find that software developers need to build the architecture is partnership with digital marketers who use machines with deep learning by taking attitude of the customers, behavior and choices into consideration. This will unlock huge benefits to the companies as accurate information about customers will be easily available to the marketers in future. How the machines are going to perform under various conditions are explained using a causal model using regression models. SPSS version 24 and R software were used for analysing the data and data regarding the customer’s behaviors, their choices and emotions are collected and based on fuzzy-set qualitative comparative analysis (fsQCA) approach how they can be influenced to use the services of the machine, fsQCA is used to compare case oriented and variable oriented quantitative analysis.

Suggested Citation

  • Mithun S. Ullal & Iqbal Thonse Hawaldar & Rashmi Soni & Mohammed Nadeem, 2021. "The Role of Machine Learning in Digital Marketing," SAGE Open, , vol. 11(4), pages 21582440211, October.
    • Handle: RePEc:sae:sagope:v:11:y:2021:i:4:p:21582440211050394
    DOI: 10.1177/21582440211050394
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    2. Ravneet Kaur & Rajesh Singh & Anita Gehlot & Neeraj Priyadarshi & Bhekisipho Twala, 2022. "Marketing Strategies 4.0: Recent Trends and Technologies in Marketing," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    3. Honglin Xiong & Chongjun Fan & Hongmin Chen & Yun Yang & Collins Opoku ANTWI & Xiaomao Fan, 2022. "A Novel Approach to Air Passenger Index Prediction: Based on Mutual Information Principle and Support Vector Regression Blended Model," SAGE Open, , vol. 12(1), pages 21582440211, January.

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