Customer Behavior for E-commerce Conversion

Overview

This repository delves into the analysis and optimization of customer behavior within the context of e-commerce conversion. The project aims to provide insights into user interactions, purchase patterns, and engagement metrics to enhance conversion rates and overall user experience.

Methodology

The analysis utilizes data sources such as e-commerce website analytics, customer interaction logs, and purchase data. Key objectives include understanding user journeys, analyzing conversion funnels, implementing segmentation and personalization strategies, and examining behavioral metrics.

Data

• Customer Interaction Logs
• Purchase and Transaction Data

Analysis

SQL, Jupyter notebooks, data scripts, and visualizations showcasing the analysis of customer behavior and strategies for conversion rate optimization.

Results

In the conducted analysis, it was observed that a significant portion of users visits the e-commerce platform without placing orders. The highest drop rate was identified between the View Product Detail Page (PDP) and Promo Input stages, indicating that many users do not utilize promotional offers when placing orders. Potential reasons for low promo usage include specific promo requirements or expired promotions. Additionally, a notable increase in the percentage from View Microsite to View PDP suggests that a considerable number of users directly navigate to PDP without going through the View Microsite stage. This implies that users prefer direct links leading to specific products, often used by affiliates to promote particular items.

License

This project is licensed under the Bitlabs Academy.

Usage

1. Clone the repository:

   git clone https://github.com/strigoimort/customer-behavior-for-e-commerce-conversion.git