A strategic framework for artificial intelligence in marketing

TLDR

The authors propose a three‑stage AI framework for strategic marketing planning that integrates mechanical, thinking, and feeling AI across research, strategy, and action. The framework assigns mechanical AI to automate tasks, thinking AI to analyze data for decisions, and feeling AI to interpret emotions, applying these roles to marketing research, segmentation, targeting, positioning, standardization, personalization, and relationalization across the 4Ps/4Cs.

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.