The contribution of Data Analytics in predicting the future purchase intentions of consumers

In today’s global market, the impact of technology can be felt in every sector and marketing is no exception to it. This study seeks to explore the role of Data Analytics in forecasting the consumers’ future buying intentions. An extensive literature review reveals that in the last couple of decades, marketing processes have undergone remarkable transformations in the way consumer data is treated and in achieving this, emerging information technologies like Data Analytics have played a significant role. The study demonstrates that meeting customers’ needs is critical for companies to acquire and retain customers and to accomplish this, anticipating consumer needs ought to be a priority for companies. While the study highlights the reasons that make data-driven techniques more reliable than the traditional theories and frameworks for the study of consumer behaviour, certain gaps have been identified in the literature including lack of relevant resources pertaining to the research topic. For the completion of this study, the qualitative research method was chosen. 15 participants from 7 different countries participated in this study through semi-structured interviews. The interviewees are Marketing and Data professionals working in the IT industry. The final outcome of this study indicates that Data Analytics is being implemented in most of the organizations to forecast consumers’ buying behaviour. Specifically, the Clustering technique and Bayesian network algorithm are considered to be the most effective models for making predictions about consumer data. The empirical findings collected through interviewing participants coupled with the extant literature contributes to the flourishing literature pertaining to the contribution of Data Analytics in forecasting consumer behaviour