PENGUKURAN EFEKTIVITAS KAMPANYE MARKETING MULTI-CHANNEL: PENDEKATAN STATISTIK UNTUK MENGIDENTIFIKASI FAKTOR KUNCI KEBERHASILAN

Abstract

This research develops a framework for measuring the effectiveness of multi-channel marketing campaigns using a statistical approach to identify key success factors in the Indonesian market context. Through a quantitative cross-sectional research design involving 145 companies with at least three active marketing channels, this study integrates structured surveys, secondary data on campaign performance metrics, and marketing data audits. Multivariate statistical analysis reveals significant correlations between channel integration levels and campaign effectiveness, with social media excelling in customer engagement (β=0.42), email marketing in conversion rate (β=0.37), and content marketing in brand awareness (β=0.45). Path analysis identifies significant synergistic effects between combinations of social media and email marketing (path coefficient=0.56) that increase conversion rates by 2.3 times. Using random forest algorithm (83.7% accuracy), five key success factors were identified: message personalization based on audience segmentation, visual and narrative consistency across channels, optimal communication timing, cross-platform data integration, and content alignment with customer journey. Machine learning-based attribution models proved significantly more accurate (89.3%) than traditional models. The research also found significant variations in multi-channel strategy effectiveness based on industry characteristics and audience segments, encouraging differentiated approaches. The measurement framework developed offers practical tools for marketers to optimize multi-channel campaigns and maximize return on marketing investment.

Keywords: multi-channel marketing, attribution modeling, campaign effectiveness, statistical approach, channel integration