How Pulse Works
Pulse learns from your promotion history to understand what works and recommend optimized promotional strategies.
Promotion Analysis
For each historical promotion, Pulse calculates:
- Baseline Demand: What sales would have been without promotion
- Incremental Lift: Additional sales due to promotion
- Cannibalization: Sales pulled forward from future periods
- Halo Effect: Lift on related products
- True ROI: Profit considering all factors
Optimal Discount Depth
Pulse determines the optimal discount level by analyzing the relationship between discount depth and incremental profit:
- Too shallow: Insufficient lift to cover margin loss
- Too deep: Excess margin sacrifice beyond lift benefit
- Optimal: Maximum incremental profit
Timing Optimization
Pulse recommends optimal timing based on:
- Seasonality patterns in your category
- Competitive promotion schedules
- Inventory levels and expiration dates
- Customer purchase cycles
Decision Types
Promotion Recommendation
Optimal products, depth, and timing for upcoming promotion
Planning
Promo Modification
Adjust running promotion based on early results
In-flight
ROI Alert
Current promotion performing below expected ROI
Real-time
Opportunity Detection
Products that would benefit from promotion
Proactive
Inputs Required
| Data Type | Required | Description |
|---|---|---|
| Sales History | Yes | Transaction data with promotion flags |
| Promotion Calendar | Yes | Historical and planned promotions |
| Product Costs | Yes | For ROI calculations |
| Customer Segments | Optional | For targeted promotion recommendations |
Promotion Metrics
Pulse tracks and reports on key promotion KPIs:
- Lift %: Sales increase during promotion
- Incremental Units: Additional units sold
- Incremental Profit: Profit from incremental sales
- Promo Cost: Margin sacrificed on baseline sales
- True ROI: (Incremental Profit - Promo Cost) / Promo Cost
- Payback Period: Days to recover promo investment
Cannibalization Detection
Pulse identifies and quantifies cannibalization effects:
- Time Cannibalization: Customers buying early, depressing post-promo sales
- Product Cannibalization: Promo product stealing from related SKUs
- Brand Cannibalization: Same-brand products competing
These effects are factored into true ROI calculations to give you an accurate picture of promotion value.
Example Recommendation
Promotion Recommendation
Confidence: 91%
Campaign: Weekend Flash Sale - Audio Category
Optimal Discount
20%
Expected Lift
+85%
Forecast ROI
2.4x
Recommended Products (8 SKUs):
- AUDIO-EARB-001: Wireless Earbuds Pro
- AUDIO-SPKR-002: Portable Bluetooth Speaker
- AUDIO-HEAD-003: Over-ear Headphones
- ...and 5 more
Why These Products:
- High elasticity (respond well to discounts)
- Adequate stock for expected lift
- Low cannibalization risk
- Above-average margin buffer
Optimal Timing: Saturday-Sunday, 10am-6pm (based on traffic patterns)
Expected Results:
- Incremental Revenue: ₹1.8L
- Incremental Profit: ₹48K
- Promo Investment: ₹20K
- Net ROI: 140%
Best Practices
- Tag all promotions in your sales data for accurate analysis
- Allow 2-4 weeks post-promo to measure cannibalization
- Start with Pulse recommendations before customizing
- Track actual vs predicted performance to improve accuracy