Revenue Intelligence
Sales Forecasting
Predict future revenue with 90%+ accuracy using AI-driven models that factor in market trends, seasonality, and leading indicators.
What's Included
Multi-model ensemble forecasting
Pipeline velocity analysis
Seasonality decomposition
External factor integration (weather, econ)
Scenario modeling
SKU-level predictions
Sales team weighting
Anomaly detection
Key Benefits
85-95% forecast accuracy
Reduced stockouts/overstocks
Optimized staffing/resources
Improved cash flow planning
Data-driven quota setting
Early warning signals
Our Process
A proven methodology that delivers consistent results
1
Data Preparation
Cleaning historical sales/pipeline data
2
Model Selection
Choosing optimal forecasting techniques
3
Validation
Backtesting against historical periods
4
Deployment
Integrating forecasts into business systems
Success Story
Client project highlights
Automotive Parts Distributor
Challenge:
35% forecast error causing ₹8M in excess inventory
Solution:
ML model incorporating weather, repair trends, and economic data
92% (from 65%)
Forecast Accuracy
-₹5.2M annual savings
Inventory Costs
-81%
Stockout Rate