Moving Toward Economic and Digital Sustainability in Marketing Analytics

Muhammad Mohiuddin, Zhan Su, Matti Haverila, Kai Haverila, Md. Al-Azad

OAI: oai:igi-global.com:349129 • DOI: 10.4018/JGIM.349129

Despite analytical advancements, firms have yet to realize the full potential of big data marketing analytics (BDMA) because the poor quality data restricts customer predictions and insightful decisions. Technology and market uncertainty create challenges in understanding business needs, choosing analytical tools, determining customer insights, and market trends. This study aims to assess the quality of marketing analytics, including technology and information quality. Data were collected from 236 North American respondents working in firms with at least limited experience in the deployment of BDMA. The analysis tool was PLS-SEM. The findings supported the hypothesis that technology and market uncertainty negatively influence the quality of analytical outcomes. This study makes a significant theoretical and methodological contribution to BDMA literature by assessing the quality of analytics as an integrated formative construct.