TY - JOUR
T1 - The Role of Machine Learning in Digital Marketing
AU - Ullal, Mithun S.
AU - Hawaldar, Iqbal Thonse
AU - Soni, Rashmi
AU - Nadeem, Mohammed
N1 - Publisher Copyright:
© The Author(s) 2021.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
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U2 - 10.1177/21582440211050394
DO - 10.1177/21582440211050394
M3 - Article
AN - SCOPUS:85117129483
SN - 2158-2440
VL - 11
JO - SAGE Open
JF - SAGE Open
IS - 4
ER -