STM Journals Peer-reviewed research from Consortium e-Learning Network

E-Commerce for Future & Trends

Impact of Big Data Analytics for Efficient Consumer Behavior Prediction

  1. Nadipudi Shanmukhi Satya
  2. Dontamsetti Sahithi
  3. Marri Durga Naga Chaitanya Lahari
  4. Manas Kumar Yogi

Abstract

Big data analytics plays a critical role in predicting customer behavior by analyzing large and complex data sets from various sources. By applications of predictive modelling principles, it will be acting as a weapon for uncovering patterns and insightful for leveraging from the consumer’s point of view. In our study, we incur sincere efforts to discuss the current trends in the domain of prediction methods involved in consumer behavior. Personalization of consumer behavior will be directed by big data analytics and it will definitely be helpful in identifying potential risks and opportunities, such as customer churn or cross-selling opportunities, enabling businesses to take proactive measures to mitigate risks and capitalize on opportunities. Though times are changing dynamically, it is quite evident that none of the traditional analytical methods are robust enough to handle massive data efficiently without much computational complexity. Keeping in view all these factors, the methods in analytical study are here to stay and provide backbone to the data analysts to handle big data and also use it in a meaningful way to predict the consumer behavior. This will help the organizations to stay in the competitive market.

Keywords

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