🎯 Forecasting Final Ticket Sales - Example
Date: 2025-11-05 03:49:13

📊 Scenario: Event is 7 days away with 11 tickets sold
Question: How many tickets will be sold by event day?

🔍 How the Forecasting Engine Works:

1️⃣ Current Event Data:
   - Current tickets sold: 11
   - Days to event: 7
   - Current snapshot: D-7

2️⃣ Cohort Analysis:
   - Find similar past events (same venue, day, time)
   - Look at their sales at D-7 (same point in time)
   - Look at their final sales (D+1 snapshots)

3️⃣ Pacing Calculation:
   - Event A: 10 tickets at D-7 → 50 tickets final = 5.0x ratio
   - Event B: 15 tickets at D-7 → 75 tickets final = 5.0x ratio
   - Event C: 8 tickets at D-7 → 40 tickets final = 5.0x ratio
   - Event D: 12 tickets at D-7 → 60 tickets final = 5.0x ratio
   - Event E: 20 tickets at D-7 → 100 tickets final = 5.0x ratio

4️⃣ Forecast Calculation:
   - P50 ratio: 5.0x (median of ratios)
   - P25 ratio: 4.5x (25th percentile)
   - P75 ratio: 5.5x (75th percentile)

5️⃣ Final Prediction:
   - P50 forecast: 11 × 5.0 = 55 tickets
   - P25 forecast: 11 × 4.5 = 50 tickets
   - P75 forecast: 11 × 5.5 = 61 tickets

✅ Result: The event is predicted to sell 55 tickets (range: 50-61)
   This means 44 more tickets are expected to be sold in the next 7 days

🎯 Key Points:
   - Uses historical pacing patterns from similar events
   - Accounts for the fact that most sales happen closer to event date
   - Provides confidence intervals (P25, P50, P75)
   - Updates as new snapshots are taken

📈 This is exactly what the forecasting engine does!
   It looks at how similar events performed at the same point in time
   and predicts the final outcome based on historical patterns.

✅ Example complete.