Abstract

The authors develop a three-stage framework for strategic marketing planning, incorporating multiple artificial intelligence (AI) benefits: mechanical AI for automating repetitive marketing functions and activities, thinking AI for processing data to arrive at decisions, and feeling AI for analyzing interactions and human emotions. This framework lays out the ways that AI can be used for marketing research, strategy (segmentation, targeting, and positioning, STP), and actions. At the marketing research stage, mechanical AI can be used for data collection, thinking AI for market analysis, and feeling AI for customer understanding. At the marketing strategy (STP) stage, mechanical AI can be used for segmentation (segment recognition), thinking AI for targeting (segment recommendation), and feeling AI for positioning (segment resonance). At the marketing action stage, mechanical AI can be used for standardization, thinking AI for personalization, and feeling AI for relationalization. We apply this framework to various areas of marketing, organized by marketing 4Ps/4Cs, to illustrate the strategic use of AI.

Details

Title
A strategic framework for artificial intelligence in marketing
Author
Ming-Hui, Huang 1 ; Rust, Roland T 2 

 National Taiwan University, Department of Information Management, College of Management, Taipei, Taiwan (GRID:grid.19188.39) (ISNI:0000 0004 0546 0241) 
 University of Maryland, Center for Excellence in Service at the Robert H. Smith School of Business, College Park, USA (GRID:grid.164295.d) (ISNI:0000 0001 0941 7177) 
Pages
30-50
Publication year
2021
Publication date
Jan 2021
Publisher
Springer Nature B.V.
ISSN
00920703
e-ISSN
15527824
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2475613868
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.