Project Topic: Data-driven marketing strategies and customer segmentation
Table Of Contents
1. Introduction
1.1 Background and Motivation
1.2 Objectives of the Project
2. Literature Review
2.1 Data-driven Marketing and Customer Segmentation
2.2 Techniques for Customer Behavior Analysis
3. Data Collection and Preprocessing
3.1 Data Sources and Acquisition
3.2 Data Cleaning and Transformation
4. Customer Segmentation Techniques
4.1 Clustering Algorithms for Segmentation
4.2 Feature Selection and Dimensionality Reduction
5. Data-driven Marketing Strategies
5.1 Personalization and Targeted Campaigns
5.2 A/B Testing and Performance Evaluation
Thesis Abstract
This project aims to explore the application of data-driven marketing strategies and customer segmentation in the context of modern businesses. The project will focus on leveraging advanced data analytics techniques to understand customer behavior, preferences, and purchasing patterns. By analyzing large volumes of customer data, the project seeks to develop personalized marketing strategies that can enhance customer engagement and drive business growth. The project will also investigate the ethical considerations and privacy implications associated with data-driven marketing practices
Thesis Overview
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