Final.Project.lead.scoring.mp4
Lead Scoring
This project developed as a part of the Data Analytics course at Ironhack Portugal, aims to streamline the lead scoring process using a comprehensive and user-friendly application. The project spans various Python scripts and Jupyter Notebooks, which handle data manipulation, model training, and other crucial methods integral to the application's functionality.
Score.it is an intelligent tool designed to revolutionize the lead-scoring process. Leveraging advanced machine learning techniques, it calculates the likelihood of different profiles converting into paying customers, aiding sales teams in making informed decisions. Additionally, the app conducts sentiment analysis of calls, offering deeper insights into the lead's journey and experience.
- Machine Learning Predictive Models: Utilizes machine learning to analyze and score leads based on their likelihood to convert.
- Sentiment Analysis: Conducts sentiment analysis on calls to provide insights into the lead's experience.
- Real-Time Call Analysis (Future Improvement): Aims to incorporate real-time analysis of calls to adapt the discourse using pre-established sales techniques.
- Recommendations (Future Improvement): Will recommend products purchased by consumers with similar profiles.
- CRM Integration (Future Improvement): Plans to integrate with CRM platforms for a smoother and automated workflow.
I warmly welcome contributions to the Score.it project! If you have any improvements or ideas, I would love to hear from you. Here are a few ways you can contribute:
- Suggesting Enhancements: If you have ideas for new features or improvements, feel free to open an issue to discuss it.
- Reporting Bugs: Help me by reporting bugs and issues you encounter while using the app.
- Code Contributions: If you'd like to contribute code to fix bugs or add new features, please open a pull request.
- Documentation: Help me improve the project's documentation, be it the user manual or the code documentation.
Feel free to contact me with your contributions and ideas. Your insights are valuable to me, and I look forward to collaborating with you to enhance Score.it!