A strategic framework for artificial intelligence in marketing

By Ming-Hui Huang, Roland T. Rust. Journal of the Academy of Marketing Science, 2020

1,315 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/d020b66a033ab1adc121010e116c594415cb2cea

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yogesh Kumar Dwivedi
2. Nir Kshetri
3. Shivendra Kumar Pandey
4. Ali Abdallah Alalwan

In Marketing

1. Yogesh Kumar Dwivedi
2. Nir Kshetri
3. Shivendra Kumar Pandey

In Sociology and Political Science

1. Yogesh Kumar Dwivedi
2. Nir Kshetri
3. Niki Panteli
4. Shivendra Kumar Pandey
5. Nripendra P. Rana
6. Ali Abdallah Alalwan
7. Kuttimani Tamilmani

Citations in the corpus

• Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda (2023, background): “Marketers also benefit from personalized outcomes such as personalized recommendation systems (Huang & Rust, 2021).”
• Artificial intelligence in marketing: A systematic literature review (2021, background): “An extensive study outlining a strategic framework for AI in marketing by Huang and Rust (2020) proposed a three-pronged approach for strategic marketing planning.”