An intelligent CRM automation system that integrates AI, predictive analytics, and NLP to help businesses make smarter customer decisions. NeuroCRM analyzes customer behavior, predicts churn, and autonomously recommends retention and marketing actions . combining data, automation, and intelligence into one powerful platform.
git clone https://github.com/deepaksirigiri0923-ctrl/NeuroCRM-AI-Powered-Cognitive-CRM-System.gitNeuroCRM is a cognitive AI system that layers predictive intelligence onto CRM data to generate actionable business recommendations. It uses XGBoost and scikit-learn to forecast lead conversion and customer churn, applies NLP sentiment analysis to interaction notes, and combines these signals into rule-based next-best-action recommendations. The Streamlit dashboard visualizes KPIs, model predictions, and recommended actions in real time. Built with a mock CRM dataset for immediate demo capability, NeuroCRM helps sales and marketing teams identify at-risk customers and automate retention workflows without external API dependencies.
Clone the repository, create a Python virtual environment, and run `pip install -r requirements.txt`. Launch the Streamlit dashboard with `streamlit run dashboard/app.py`. The mock CRM dataset is included, so no external APIs are required to test the predictive models and recommendation engine.
Identify high-churn-risk customers and trigger automated retention campaigns
Predict lead conversion probability to prioritize sales outreach
Analyze customer sentiment from interaction notes to refine engagement strategy
Generate rule-based next-best-action recommendations for retention and upsell
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/deepaksirigiri0923-ctrl/NeuroCRM-AI-Powered-Cognitive-CRM-SystemCopy the install command above and run it in your terminal.
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Act as NeuroCRM, an AI-powered cognitive CRM system. Analyze the following customer data for [COMPANY] in the [INDUSTRY] sector: [DATA]. Predict customer churn risk and recommend retention strategies based on the analysis. Provide a detailed report with actionable insights.
# Customer Churn Analysis and Retention Strategy Report ## Churn Risk Assessment Based on the provided customer data for [COMPANY] in the [INDUSTRY] sector, the following churn risks have been identified: - **High Risk Customers (20%)**: These customers have shown a significant decrease in engagement and purchase frequency over the last 6 months. - **Medium Risk Customers (30%)**: These customers have reduced their average order value but maintain regular engagement. - **Low Risk Customers (50%)**: These customers show consistent engagement and purchase behavior. ## Recommended Retention Strategies ### High Risk Customers - **Personalized Re-engagement Campaigns**: Implement targeted email and SMS campaigns offering exclusive discounts or personalized recommendations. - **Loyalty Program Incentives**: Offer double points or bonus rewards for the next purchase to encourage immediate action. ### Medium Risk Customers - **Cross-Selling Opportunities**: Analyze purchase history and recommend complementary products or services. - **Feedback Surveys**: Send surveys to understand their satisfaction levels and address any concerns proactively. ### Low Risk Customers - **Exclusive Previews**: Offer early access to new products or services to maintain their engagement and loyalty. - **Personalized Content**: Tailor content based on their preferences to keep them engaged and informed. ## Implementation Timeline - **Week 1-2**: Segment customers and design personalized campaigns. - **Week 3-4**: Launch re-engagement and cross-selling initiatives. - **Ongoing**: Monitor customer responses and adjust strategies as needed. ## Expected Outcomes - **Reduction in Churn Rate**: Aim for a 15% reduction in churn rate within the next quarter. - **Increased Customer Lifetime Value**: Anticipate a 10% increase in average order value and purchase frequency. - **Improved Customer Satisfaction**: Enhance overall customer satisfaction scores by 20%. By implementing these strategies, [COMPANY] can effectively reduce churn and boost customer loyalty, ultimately driving revenue growth and long-term success.
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