Predicting sales funnel with a customer-relationship-management tool

Inhaltsverzeichnis (Table of Contents)

• BUSINESS CHALLENGE
• TECHNICAL APPROACH
  • Information sources
    • Company information
    • Internal company data
  • Artificial Intelligence
    • Machine Learning techniques
    • Deep Learning techniques
  • Tested architectures
  • Final architecture
• CONCLUSION
  • Objectives revision and functional requirements
  • Future guidelines

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This Bachelor's thesis aims to develop a customer retention model, specifically focusing on churn prevention. The model aims to accurately predict opportunities with a high likelihood of being lost, allowing salespersons to identify and react quickly.

• Customer retention and churn prevention
• Predictive modeling using Artificial Intelligence
• Machine learning and deep learning techniques
• Data analysis and model development
• Salesperson support and decision-making

Zusammenfassung der Kapitel (Chapter Summaries)

• BUSINESS CHALLENGE: This chapter introduces the problem of customer churn and its impact on businesses. It discusses the need for accurate prediction of churn risks to facilitate effective interventions and improve customer retention rates.
• TECHNICAL APPROACH: This chapter outlines the technical framework of the thesis. It explores the information sources used, including company information and internal data, and introduces the concept of Artificial Intelligence and its application in developing the churn prediction model. This chapter covers machine learning and deep learning techniques utilized in the project and explains the tested architectures leading to the final model architecture.

Schlüsselwörter (Keywords)

The core focus of this thesis lies in customer retention, churn prediction, Artificial Intelligence, machine learning, deep learning, data analysis, model development, and sales support. The project emphasizes the practical application of these technologies to improve business outcomes and enhance customer satisfaction.