This paper is published in Volume-7, Issue-4, 2021
Area
Data Science
Author
Jaswanth Kankanala, Sravya Sri V., Venkatesh narahari
Org/Univ
MODAK, Analytics, Gachibowli, Telangana, India
Pub. Date
23 July, 2021
Paper ID
V7I4-1484
Publisher
Keywords
Bank Marketing, Telemarketing, Machine learning, Logistic regression

Citationsacebook

IEEE
Jaswanth Kankanala, Sravya Sri V., Venkatesh narahari. Analysis of bank telemarketing data using Microsoft Azure machine learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Jaswanth Kankanala, Sravya Sri V., Venkatesh narahari (2021). Analysis of bank telemarketing data using Microsoft Azure machine learning. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Jaswanth Kankanala, Sravya Sri V., Venkatesh narahari. "Analysis of bank telemarketing data using Microsoft Azure machine learning." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

predict customers' responses to future marketing campaigns & increase the effectiveness of the bank's telemarketing campaign Here in this paper we will empower the bank to foster a more granular comprehension of its client base, foresee clients' reaction to its selling crusade and build up an objective client profile for future advertising plans. By investigating client highlights, like socioeconomics and exchange history, the bank will actually want to anticipate client saving practices and recognize which sort of clients is bound to set aside term installments. The bank would then be able to zero in its promoting endeavors on those clients. This won't just permit the bank to get stores all the more successfully yet in addition increment consumer loyalty by decreasing unwanted ads for specific clients.