4.6 Article

A strategic framework for artificial intelligence in marketing

Journal

JOURNAL OF THE ACADEMY OF MARKETING SCIENCE
Volume 49, Issue 1, Pages 30-50

Publisher

SPRINGER
DOI: 10.1007/s11747-020-00749-9

Keywords

Artificial intelligence; Machine learning; Mechanical AI; Thinking AI; Feeling AI; Strategic AI marketing; Marketing strategy; Standardization; Personalization; Relationalization; Segmentation; Targeting; Positioning; 4Ps; 4Cs

Categories

Funding

  1. Ministry of Science and Technology, Taiwan [106-2410-H-002-056MY3, 107-2410-H-002-115-MY3]

Ask authors/readers for more resources

The authors propose a three-stage framework for strategic marketing planning integrating mechanical AI, thinking AI, and feeling AI. This framework can be applied to marketing research, strategy, and actions, utilizing various AI technologies in different stages.
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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available