E-cigarette Purchase Intention through Facebook Social Media: A Cross-Sectional Study

Predicting customer behavior in the context of e- commerce is becoming increasingly important as people shift from visiting physical stores to shopping online. By facilitating a more personalized shopping process, it can boost consumer happiness and sales, resulting in higher conversion rates and a competitive edge. Models for forecasting consumer behaviors can be constructed using and supplementing customer data. This research looks at how a prominent German apparel shop uses machine learning models to forecast purchases, which is a significant use case. Following that, by doing a descriptive data analysis and individually training the models on the distinct datasets, this study provides insight into the performance differences of the models on sequential and static customer data. Three different algorithms are used.

show abstract

Prediction of Customer Purchase Intention using Social Media Data

Kale

Bidwai

Maske

et al. 2022

IJARSCT

View full text Add to dashboard Cite

show abstract

Prediction of Consumer Purchase Intension

Paithankar

Pardeshi

Tate

et al. 2023

IJARSCT

View full text Add to dashboard Cite

The change in recent years from physical store visits to online purchasing has made it more crucial than ever to predict client behavior in the context of e-commerce. It can increase consumer satisfaction and sales by offering a more customized purchasing experience, improving conversion rates and giving businesses a competitive edge. Customer data can be added to and used to build models for predicting consumer behavior.In this study, a big German clothing shop uses machine learning models to forecast a purchase, which is an important use case. This study goes beyond simply evaluating the performance of the models on sequential and static customer data by conducting a descriptive data analysis and individually training the models on the various datasets. Total of three different algorithms.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

E-cigarette Purchase Intention through Facebook Social Media: A Cross-Sectional Study

Cited by 2 publications

References 23 publications

Prediction of Customer Purchase Intention using Social Media Data

Prediction of Customer Purchase Intention using Social Media Data

Prediction of Consumer Purchase Intension

Contact Info

Product

Resources

About