Sarcouncil Journal of Engineering and Computer Sciences

Sarcouncil Journal of Engineering and Computer Sciences

An Open access peer reviewed international Journal
Publication Frequency- Monthly
Publisher Name-SARC Publisher

ISSN Online- 2945-3585
Country of origin-PHILIPPINES
Impact Factor- 3.7
Language- English

Keywords

Editors

Marketing Mix Modeling: A Statistical Approach to Measuring and Optimizing Marketing Effectiveness

Keywords: Marketing Mix Modeling, Econometric Analysis, Budget Optimization, Channel Attribution, Predictive Forecasting

Abstract: Marketing Mix Modeling represents a sophisticated econometric framework that transforms marketing measurement from intuitive decision-making to evidence-based strategic planning through advanced statistical modeling techniques. The procedure employs multivariate regression analysis and time-series econometric approaches to decompose aggregate business performance into constituent elements attributable to specific marketing channels while accounting for external market factors and baseline trends. Contemporary implementations leverage computer-assisted optimization algorithms that navigate complex multi-channel investment landscapes, incorporating cross-channel synergistic effects and temporal variations to identify optimal resource allocation strategies. Predictive capabilities within MMM frameworks utilize multimedia communication synergies and adaptive learning mechanisms to generate reliable forecasts about future marketing effectiveness while maintaining statistical rigor through comprehensive validation techniques. The integration of Marketing Mix Modeling with enterprise planning systems enables organizations to translate analytical insights into actionable strategic decisions, addressing critical business challenges including budget optimization, channel performance evaluation, and marketing accountability demonstration across diverse industry sectors

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