Authors - Jude Osakwe, Josephina Muntuumo, Daphine Gondo Abstract - Digital ecosystems have altered how organisations approach marketing decision-making, creating demand for advanced data management methods. This paper analyses 144 peer-reviewed articles published between 2013 and 2025, examining customer segmentation algorithms, real-time data processing systems, and integrated marketing analytics platforms. Organisations implementing these techniques report marketing return on investment improvements of 15 to 25 percent and conversion rate gains of 10 to 30 percent. A structured comparison of four technique categories, namely big data analytics, machine learning, AI and natural language processing, and predictive analytics, reveals distinct performance profiles and deployment trade-offs. Big data analytics delivers the broadest gains but demands the highest infrastructure investment, while predictive analytics offers a lower-cost entry point with shorter payback periods. Persistent challenges include data quality deficiencies, skills shortages, integration difficulties, privacy compliance obligations, and organisational resistance to change. The paper contributes a systematic framework and benchmarking evidence, and maps implementation constraints that explain the gap between reported performance benchmarks and operational outcomes
