#!/usr/bin/env python3
"""Financial simulation with 300 analysis tier"""
# ACTUAL COSTS from end-to-end testing
test_costs = [0.0208, 0.0281, 0.0242]
avg_cost_per_analysis = sum(test_costs) / len(test_costs)
print("="*80)
print("CLIPSENSE FINANCIAL SIMULATION - 300 ANALYSIS TIER")
print("="*80)
print(f"\nActual cost per analysis: ${avg_cost_per_analysis:.4f}")
print()
# Pricing options for 300 analyses/month
pricing_options = [
("Conservative", 79, 300),
("Standard", 99, 300),
("Competitive", 149, 300),
("Premium", 199, 300),
]
print("TEAM TIER: 300 ANALYSES/MONTH - PRICING OPTIONS:")
print("="*80)
for option_name, price, limit in pricing_options:
# Best case: user uses full allowance
full_usage_cost = limit * avg_cost_per_analysis
full_usage_profit = price - full_usage_cost
full_usage_margin = (full_usage_profit / price * 100)
# Average case: user uses 60% of allowance
avg_usage = int(limit * 0.6)
avg_usage_cost = avg_usage * avg_cost_per_analysis
avg_usage_profit = price - avg_usage_cost
avg_usage_margin = (avg_usage_profit / price * 100)
# Light case: user uses 30% of allowance
light_usage = int(limit * 0.3)
light_usage_cost = light_usage * avg_cost_per_analysis
light_usage_profit = price - light_usage_cost
light_usage_margin = (light_usage_profit / price * 100)
print(f"\n{option_name.upper()} - ${price}/mo for {limit} analyses:")
print("-" * 80)
print(f" Full usage ({limit} analyses): Cost=${full_usage_cost:6.2f} | Profit=${full_usage_profit:7.2f} | Margin={full_usage_margin:5.1f}%")
print(f" Avg usage ({avg_usage} analyses): Cost=${avg_usage_cost:6.2f} | Profit=${avg_usage_profit:7.2f} | Margin={avg_usage_margin:5.1f}%")
print(f" Light usage ({light_usage} analyses): Cost=${light_usage_cost:6.2f} | Profit=${light_usage_profit:7.2f} | Margin={light_usage_margin:5.1f}%")
# Complete tier structure comparison
print("\n" + "="*80)
print("RECOMMENDED COMPLETE TIER STRUCTURE:")
print("="*80)
tiers = [
("FREE", 0, 3),
("PRO", 29, 50),
("TEAM", 99, 300),
("ENTERPRISE", 299, 1000),
]
print(f"\n{'TIER':<12} | {'PRICE':>10} | {'LIMIT':>8} | {'COST (full)':>12} | {'PROFIT':>10} | {'MARGIN':>8}")
print("-" * 80)
for tier_name, price, limit in tiers:
cost = limit * avg_cost_per_analysis
profit = price - cost
margin = (profit / price * 100) if price > 0 else 0
limit_display = f"{limit:,}"
status = "✅" if profit > 0 else "❌"
print(f"{tier_name:<12} | ${price:>9} | {limit_display:>8} | ${cost:>11.2f} | ${profit:>9.2f} | {margin:>6.1f}% {status}")
print("\n" + "="*80)
print("COMPETITIVE ANALYSIS:")
print("="*80)
competitors = [
("Loom Pro", 15, "Unlimited", "Video messaging - different use case"),
("BugSnag Team", 99, "Unlimited", "Error tracking - no AI analysis"),
("Sentry Team", 26, "Unlimited", "Error monitoring - different category"),
("RunwayML Standard", 12, "125 videos", "AI video - limited processing"),
]
print("\n")
for name, price, limit, notes in competitors:
print(f"{name:<20} ${price:>3}/mo | {limit:<15} | {notes}")
print("\n" + "="*80)
print("FINAL RECOMMENDATION:")
print("="*80)
print("""
SAFEST PROFITABLE STRUCTURE:
- FREE: $0/mo | 3 analyses | Acquisition (7¢ cost)
- PRO: $29/mo | 50 analyses | $27.78 profit (96% margin)
- TEAM: $99/mo | 300 analyses | $91.69 profit (93% margin) ⭐
- ENTERPRISE: $299/mo | 1,000 analyses | $274.63 profit (92% margin)
- CUSTOM: Quote | 1,000+ analyses | Contact sales
WHY $99 for 300?
✅ 93% margin - highly profitable
✅ 6x value vs PRO (300 vs 50 analyses)
✅ Below break-even threshold (4,063 analyses)
✅ Room for heavy users without risk
✅ Competitive vs RunwayML ($12 for 125 videos)
✅ Positioned as premium AI debugging tool
COMPETITIVE POSITIONING:
- AI video analysis is unique - no direct competitors
- Priced higher than basic video tools (justified by AI)
- Lower than enterprise error tools (accessible to startups)
- Room to add Enterprise tier for larger teams
GROWTH PATH:
1. Launch with FREE (3), PRO (50), TEAM (300)
2. Monitor usage patterns for 30 days
3. Add ENTERPRISE tier if 10+ teams hit TEAM limit
4. Consider usage-based pricing above 1,000 analyses
""")
print("="*80)
