Book Title: Recent Advancements and Future Perspectives in Electronics and Computer Engineering
Editors: Mr. Lochan Nagar and Dr. M.Sucharitha
ISBN: 978-81-963849-5-1
DOI: https://doi.org/10.59646/ecebookc28/007
Author: Dr Giriraj Kiradoo, Associate Professor, Department of Management & Technology, Engineering College Bikaner, Bikaner, Rajasthan, India
Abstract:
The term “predictive analytics” refers to the use of sophisticated algorithms to both existing and future data in order to foretell how online shoppers will act. Businesses may optimise supply chain operations, anticipate consumer demands, and remove uncertainty from crucial choices with the aid of predictive analytics. Insights into consumer behaviour, such rates of shopping cart abandonment and clickstream data showing interest levels, aid in the prediction of purchase probability and the optimisation of the online experience. Businesses may better target promotions and cross-sell products by analysing customer purchase histories and sales data, which shows purchasing habits, purchase values, and product affinities. Proactive decision-making to optimise marketing efforts, personalise customer interactions, and maximise long-term profitability and customer pleasure is made possible by ecommerce indicators like as churn forecasts, conversion rates, and CLV, which further enhance predictive models. Predictive Analytics in Online Retail: A Data-Driven Strategy for Enhanced Consumer Satisfaction is the topic of this chapter.