AI-POWERED SALES PREDICTION AND RECOMMENDATION SYSTEM

KEY BENEFITS DELIVERED:
OPTIMIZED SALES STRATEGY – INTELLIGENT
INSIGHTS REPLACE GUESSWORK.
INCREASED REVENUE – UNCOVERED
UPSELLING/DOWN-SELLING OPPORTUNITIES.
PERSONALIZED ENGAGEMENT – SMART
RECOMMENDATIONS FOR BETTER TARGETING.
ACCURATE FORECASTING – PREDICT FUTURE
TRENDS WITH CONFIDENCE.

Transcript

1. AI-POWERED SALES PREDICTION AND RECOMMENDATION SYSTEM
2. PROBLEM STATEMENT & CHALLENGES KEY CHALLENGES: ❌ LACK OF DATA-DRIVEN INSIGHTS – SALES PERFORMANCE VARIED DUE TO MANUAL AND SUBJECTIVE DECISIONS. 📉 MISSED SALES OPPORTUNITIES – NO CLEAR WAY TO IDENTIFY UPSELLING AND DOWN-SELLING POSSIBILITIES. 🔄 INEFFICIENT STRATEGY – REACTIVE SALES APPROACH LED TO UNDERPERFORMANCE AND LOST REVENUE.
3. SOLUTION APPROACH 1. Data Collection & Processing Integrated multi-source historical sales data into Snowflake. Cleaned and transformed data using Pandas and NumPy. HOW WE SOLVED IT: 2. Predictive Modeling Built ML models using XGBoost & Scikit-learn to forecast sales. Applied feature engineering to surface buying patterns and trends.
4. VALUE CREATION KEY BENEFITS DELIVERED: OPTIMIZED SALES STRATEGY – INTELLIGENT INSIGHTS REPLACE GUESSWORK. INCREASED REVENUE – UNCOVERED UPSELLING/DOWN-SELLING OPPORTUNITIES. PERSONALIZED ENGAGEMENT – SMART RECOMMENDATIONS FOR BETTER TARGETING. ACCURATE FORECASTING – PREDICT FUTURE TRENDS WITH CONFIDENCE.
5. TECHNOLOGIES USED PREDICTIVE MODELING DATA STORAGE DATA PROCESSING VISUALIZATION INTEGRATION
6. THANK YOU SCAN HERE TO SEE A DEMO ON YOUR DATASETS