IJCOPE Journal

UGC Logo DOI / ISO Logo

International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
Journal Information
ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 7

Published on: July 2026

ANALYZING THE KEY BEHAVIORAL FEATURES INFLUENCING CUSTOMER DECISIONS IN E-COMMERCE ENVIRONMENTS USING HISTORICAL AND REAL-TIME DATA

Purnima Verma Virendra Tiwari

AKS, University, Satna, MP, India

DOI:https://doi.org/10.55041/ijcope.v2i7.185

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Download PDF Review Report

Abstract

The rapid growth of e-commerce has generated vast amounts of customer data, enabling businesses to better understand consumer decision-making processes. This study aims to analyze key behavioral features influencing customer decisions in e-commerce environments by integrating both historical and real-time data. The research identifies critical behavioral indicators such as browsing patterns, clickstream activity, purchase history, session duration, and engagement metrics. A hybrid analytical framework combining machine learning and statistical techniques is proposed to extract meaningful insights. The study demonstrates that integrating historical customer characteristics with real-time behavioral signals significantly enhances prediction accuracy and customer segmentation. The findings contribute to improved personalization, recommendation systems, and strategic decision-making in e-commerce platforms.

 

Keywords: E-commerce, decision making, pattern analysis, velocity streaming,

How to Cite this Paper

Verma, P. & Tiwari, V. (2026). Analyzing the Key Behavioral Features Influencing Customer Decisions in E-Commerce Environments Using Historical and Real-Time Data. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(7), 1-9. https://doi.org/10.55041/ijcope.v2i7.185

Verma, Purnima, and Virendra Tiwari. "Analyzing the Key Behavioral Features Influencing Customer Decisions in E-Commerce Environments Using Historical and Real-Time Data." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i7.185.

Verma, Purnima, and Virendra Tiwari. "Analyzing the Key Behavioral Features Influencing Customer Decisions in E-Commerce Environments Using Historical and Real-Time Data." International Journal of Creative and Open Research in Engineering and Management 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i7.185.

Search & Index

Google Scholar Crossref DOI ResearchGate

References

[1]. Li, H. (2023). Research on Consumer Behavior Prediction Based on E-commerce Data Analysis. BCP Business & Management.

 

[2]. Kamangar, A. (2020). A Literature Review of Customer Behaviour Patterns on E-Commerce Websites Using an Eye Tracker. The Marketing Review.

[3]. Predicting online customer purchase: The integration of customer characteristics and browsing patterns (2024). Decision Support Systems.

[4]. Caroline, Y., Yuswardi, & Rofi'i, Y. U. (2023). Analysis of E-Commerce Purchase Patterns Using Big Data. International Journal of Software Engineering and Computer Science.

[5]. Hajli, N., et al. (2021). Consumer Behavior in Social Commerce: Results from a Meta-Analysis. Technological Forecasting and Social Change.

[6]. Devi, P. (2023). Consumer Behavior towards E-Commerce in India. Innovative Research Thoughts.

[7]. Customer Behavior Analysis and Purchase Prediction in E-Commerce (2024).

[8]. E-commerce Customer Behavior Dataset Analysis (2024).

[9]. Kral, P., et al. (2022). Two Decades of Research on Consumer Behavior and Analytics. Journal of Global Information Management.

[10]. Li, S., et al. (2026). Big Data in Consumer Behavior Research: A Systematic Review. Journal of Marketing Analytics.

[11]. Hendriksen, M., et al. (2020). Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs  Identified Customer

 

Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Jul 20 2026
CCBYNC

This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

View License
Back to Volume 02, Issue 7View All Issues Next Article

← Previous Article

Analysing India’s Export Strengths: An RCA-Based Assessment of Top Merchandise Exporting States (FY2018–FY2025)

Next Article →

Application of Sentiment Analysis in IT Employee Performance and Management in Coimbatore
Scroll to Top