AI-DRIVEN INSIGHTS FOR PRODUCT MARKETING: ENHANCING CUSTOMER EXPERIENCE AND REFINING MARKET SEGMENTATION

Abstract

This systematic review examines how artificial intelligence enhances product marketing by improving customer experience and refining market segmentation. Following a predefined PRISMA protocol, we searched multidisciplinary databases for peer reviewed, English language studies through December 2021, applied dual independent screening, and extracted standardized information on context, techniques, outcomes, and governance. In total, 115 studies met eligibility and were included in the synthesis. Findings indicate that AI delivers consistent and economically meaningful gains when embedded in data mature workflows and evaluated with credible designs. Across the corpus, 67.8 percent of studies reported statistically positive primary outcomes. Typical improvements included higher conversion and stronger ranking quality in personalization systems, as well as revenue lift from pricing and offer optimization without eroding trust. Gains were more durable when deployment was supported by monitoring, calibration, explanation, fair allocation checks, and disciplined rollout practices. Evidence clusters across seven themes that map the decision surface of product marketing: personalization and next best action, segmentation, journey analytics and voice of customer, pricing and promotion, churn and lifetime value, explainability and fairness, and MLOps implementation. Limitations include heterogeneity in metrics and settings, the English language focus, and the pre 2022 cutoff. Overall, the review moves the conversation from whether AI helps to the conditions under which it produces reliable and sustained value. The contribution is threefold: a structured taxonomy of AI approaches relevant to product marketing, an evidence map that shows where results are strongest or thin, and a conceptual model that links data readiness to AI capability, insight quality, and measurable outcomes in customer experience and firm performance.