Customer Relationship Management (CRM) Using Python Full Stack (Django and MySQL)

Abstract

Customer Relationship Management (CRM) plays a critical role in improving customer engagement, satisfaction, and retention. Traditional CRM systems often face inefficiencies due to manual processes, lack of integration, and poor scalability. This paper presents the design and development of a web-based CRM system using Python Full Stack technology, integrating Django for backend and MySQL for database management. The system automates customer data handling, sales tracking, feedback monitoring, and reporting through a user-friendly interface. The architecture follows the MVC pattern, ensuring scalability, security, and modularity. This study demonstrates that open-source full-stack frameworks can provide cost-effective, customizable, and efficient CRM solutions, especially for small and medium enterprises (SMEs).

Introduction

In today’s digital age, Customer Relationship Management (CRM) is vital for business growth. However, many small and medium enterprises (SMEs) face challenges in adopting CRM systems due to high costs, complexity, and lack of customization. This study proposes a web-based, full-stack CRM system using Python Django and MySQL to offer an affordable, scalable, and secure solution tailored for SMEs.

???? Literature Review:

Past research highlights the importance of CRM in improving customer engagement, loyalty, and business outcomes. However, most studies:

• Lack practical deployment (Sardjono & Kristin, 2023)

• Miss user-friendly interfaces (Krishnareddy et al., 2022)

• Require heavy infrastructure (Rahman et al., 2018)

• Lack advanced analytics (Sharma et al., 2024)

These gaps underline the need for an integrated, automated, and analytics-driven CRM system.

?? Problem Statement:

Many SMEs still use manual methods to manage customer interactions, causing inefficiencies and data inconsistencies. Existing CRM tools are either expensive, overly complex, or not tailored to small business needs.

???? Objectives:

1. Build a Django-MySQL-based CRM application.

2. Automate tasks like sales tracking and feedback handling.

3. Provide real-time insights through interactive dashboards.

4. Ensure security, scalability, and modular design.

5. Demonstrate the effectiveness of full-stack solutions for SMEs.

???? Methodology:

• Architecture: Follows MVC (Model-View-Controller) using Django.

• Backend: Python Django.

• Database: MySQL.

• Frontend: HTML, CSS, JavaScript.

• Modules: Customer Management, Lead Tracking, Feedback, Reporting.

• Validation: Django’s built-in tools + manual usability testing.

? Expected Outcomes:

• Fully operational CRM web app for SMEs.

• Streamlined customer and data management.

• Real-time dashboards for business insights.

• Secure, open-source, and scalable architecture.

• Improved customer satisfaction and operational efficiency.

???? Future Enhancements:

1. Add AI/ML features for predictive analytics.

2. Cloud deployment for global access and uptime.

3. Develop a mobile app for on-the-go use.

4. Integrate automated marketing tools (email/SMS campaigns).

Conclusion

This study successfully demonstrates the implementation of a full-stack CRM system using Python Django and MySQL. The proposed system enhances automation, scalability, and usability for SMEs, providing a cost-effective and efficient alternative to existing CRM solutions. The platform ensures better customer engagement and operational efficiency through its modular design and real-time analytical capabilities.

References

[1] W. Sardjono and D. M. Kristin, “Model of CRM Systems Evaluation Using Factor Analysis,” ICIMTech, 2023. [2] K. R. Krishnareddy et al., “AI-based Fuzzy Clustering System for Improving CRM,” I-SMAC, 2022. [3] Li, R. C., & Tee, M. L., “Developing an Implementation Framework for Automated Customer Support,” IEEM, 2021. [4] S. R. Rahman et al., “CRM Integration with ERP Systems,” ICITR, 2018. [5] P. Sharma et al., “Cloud-Based CRM Solution for SMEs,” ICCMSO, 2024. [6] ICIPCA 2025 Paper, “CRM with Predictive Analytics,” DOI… [7] ICPCT 2025 Paper, “Real-Time CRM Dashboard,” DOI… [8] ICKECS 2024 Paper, “CRM Data Management Optimization,” DOI… [9] TQCEBT 2024 Paper, “AI for Customer Retention,” DOI… [10] ICCMSO 2024 Paper, “CRM Automation Using Web Technologies,” DOI…

Copyright

Copyright © 2025 R. Kalai Selvi, V. Pallavi, V. Sangeetha, Y. R. Charan Kumar, S. Jagadeesh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.