Integrated Web and Social Media Analytics for Marketing Decisions in Project-Based Organizations

Abstract

Project-based organizations need rapid marketing decisions but often rely on disconnected web and social-media metrics collected under changing campaign objectives. This integrative review synthesizes 289 publications across digital analytics, attribution, content evaluation, segmentation, experimentation, privacy, and organizational learning. Six dimensions organize the evidence: cross-channel measurement, attribution quality, content effectiveness, audience segmentation, campaign experimentation, and privacy-aware reporting. The synthesis shows that integrated reporting improves decisions only when teams define comparable measures, distinguish exposure from causal effect, document assumptions, and preserve learning across projects. Short campaign cycles increase the value of experimentation but also intensify sample-size, attribution, and privacy constraints. The paper contributes a measurement-to-learning framework, decision indicators, and propositions for evaluating whether analytics changes resource allocation, content choices, and campaign outcomes. The framework supports transparent reporting and cumulative learning in temporary and project-based settings.