Abstract
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.
Keywords
PersonalizationFeelingMarket segmentationMarketing researchMarketing and artificial intelligenceMarketingComputer scienceMarketing strategyArtificial intelligencePersonalized marketingMarketing managementStandardizationKnowledge managementBusinessReturn on marketing investmentPsychologyBusiness-to-government
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Publication Info
- Year
- 2020
- Type
- article
- Volume
- 49
- Issue
- 1
- Pages
- 30-50
- Citations
- 1211
- Access
- Closed
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Cite This
Ming‐Hui Huang,
Roland T. Rust
(2020).
A strategic framework for artificial intelligence in marketing.
Journal of the Academy of Marketing Science
, 49
(1)
, 30-50.
https://doi.org/10.1007/s11747-020-00749-9
Identifiers
- DOI
- 10.1007/s11747-020-00749-9