import asyncio from datetime import datetime from typing import Dict, List from core.models import Task import logging logger = logging.getLogger(__name__) class MonetizationEngine: """ Monetization Engine for AutoSEO - handles all revenue generation logic """ def __init__(self): self.subscription_tiers = { "starter": { "price": 299, "features": ["basic_seo", "10_content_pieces", "monthly_report"], "cost_per_month": 50 # Estimated cost for resources }, "professional": { "price": 799, "features": ["full_seo", "30_content_pieces", "link_building", "weekly_report"], "cost_per_month": 120 }, "enterprise": { "price": 1499, "features": ["advanced_seo", "100_content_pieces", "white_label", "priority_support"], "cost_per_month": 250 } } self.customers = [] self.revenue_data = { "monthly_recurring_revenue": 0, "performance_bonus_revenue": 0, "one_time_revenue": 0, "total_revenue": 0 } self.pricing_strategies = [] self.customer_ltv = {} async def calculate_mrr(self) -> float: """Calculate Monthly Recurring Revenue""" mrr = 0 for customer in self.customers: tier = customer.get('tier', 'starter') mrr += self.subscription_tiers[tier]['price'] self.revenue_data['monthly_recurring_revenue'] = mrr return mrr async def calculate_customer_acquisition_cost(self) -> float: """Calculate average customer acquisition cost""" if not self.customers: return 0 # Simulated CAC calculation total_acquisition_cost = len(self.customers) * 150 # $150 per customer acquisition cac = total_acquisition_cost / len(self.customers) return cac async def calculate_customer_ltv(self, customer_id: str) -> float: """Calculate lifetime value for a specific customer""" # Simulate LTV calculation based on tier and tenure customer = next((c for c in self.customers if c['id'] == customer_id), None) if not customer: return 0 tier = customer.get('tier', 'starter') monthly_value = self.subscription_tiers[tier]['price'] # Estimate tenure in months (could be based on actual data) estimated_tenure_months = 12 # Average tenure assumption ltv = monthly_value * estimated_tenure_months self.customer_ltv[customer_id] = ltv return ltv async def calculate_roi_for_customer(self, customer_id: str) -> Dict[str, float]: """Calculate ROI for a specific customer's SEO investment""" # Simulate ROI calculation based on traffic and conversion improvements roi_data = { "investment": self.subscription_tiers.get("professional", {}).get("price", 799) * 12, # Annual subscription cost "traffic_increase_value": 25000, # Estimated value of traffic increase "conversion_increase_value": 15000, # Estimated value of conversion improvement "total_return": 40000, "roi_percentage": 333 # (40000-799*12)/(799*12)*100 } return roi_data async def generate_performance_bonus(self, customer_id: str, performance_metrics: Dict) -> float: """Generate performance bonus based on results achieved""" # Calculate bonus based on traffic, ranking, or revenue improvements bonus = 0 # Example: 10% of revenue increase as bonus revenue_increase = performance_metrics.get("revenue_increase", 0) bonus = revenue_increase * 0.10 self.revenue_data['performance_bonus_revenue'] += bonus return bonus async def calculate_white_label_licensing_revenue(self, licenses_sold: int) -> float: """Calculate revenue from white-label licensing""" price_per_license = 4999 # Annual license fee revenue = licenses_sold * price_per_license self.revenue_data['one_time_revenue'] += revenue return revenue async def calculate_niche_site_revenue(self, sites_sold: int) -> float: """Calculate revenue from selling niche authority sites""" avg_site_value = 25000 # Average value of a niche site revenue = sites_sold * avg_site_value self.revenue_data['one_time_revenue'] += revenue return revenue async def calculate_affiliate_revenue(self, referrals: int) -> float: """Calculate affiliate revenue from tool/service referrals""" commission_per_referral = 50 # Average commission per referral revenue = referrals * commission_per_referral self.revenue_data['one_time_revenue'] += revenue return revenue async def get_revenue_projection(self, months: int = 12) -> Dict[str, List[float]]: """Project revenue for the next N months""" current_mrr = await self.calculate_mrr() # Simulate growth projections projected_revenue = { "mrr": [], "cumulative_revenue": [] } cumulative = 0 for month in range(1, months + 1): # Simulate 10% monthly growth projected_mrr = current_mrr * (1.10 ** (month - 1)) projected_revenue["mrr"].append(projected_mrr) cumulative += projected_mrr projected_revenue["cumulative_revenue"].append(cumulative) return projected_revenue async def add_customer(self, customer_data: Dict): """Add a new customer to the system""" customer = { "id": f"cust_{len(self.customers) + 1}", "name": customer_data.get("name", "Unknown"), "tier": customer_data.get("tier", "starter"), "signup_date": datetime.now(), "status": "active" } self.customers.append(customer) logger.info(f"Added new customer: {customer['name']} ({customer['tier']} tier)") async def process_billing_cycle(self): """Process monthly billing cycle""" logger.info("Processing monthly billing cycle...") # Calculate MRR mrr = await self.calculate_mrr() # Calculate costs total_costs = 0 for customer in self.customers: tier = customer.get('tier', 'starter') total_costs += self.subscription_tiers[tier]['cost_per_month'] # Update total revenue self.revenue_data['total_revenue'] = mrr + self.revenue_data['performance_bonus_revenue'] + self.revenue_data['one_time_revenue'] logger.info(f"Billing cycle complete - MRR: ${mrr}, Costs: ${total_costs}, Net Revenue: ${mrr - total_costs}") async def get_monetization_dashboard(self) -> Dict: """Get comprehensive monetization dashboard data""" mrr = await self.calculate_mrr() cac = await self.calculate_customer_acquisition_cost() dashboard_data = { "revenue_summary": self.revenue_data, "customer_metrics": { "total_customers": len(self.customers), "mrr": mrr, "arpu": mrr / len(self.customers) if self.customers else 0, "cac": cac, "ltv_cac_ratio": (await self.calculate_customer_ltv(self.customers[0]['id']) / cac) if self.customers and cac > 0 else 0 }, "projection_12_months": await self.get_revenue_projection(12), "subscription_breakdown": { tier: len([c for c in self.customers if c.get('tier') == tier]) for tier in self.subscription_tiers.keys() } } return dashboard_data # Example usage and testing async def test_monetization_engine(): """Test the monetization engine""" engine = MonetizationEngine() # Add sample customers await engine.add_customer({"name": "Acme Corp", "tier": "professional"}) await engine.add_customer({"name": "Globex Inc", "tier": "enterprise"}) await engine.add_customer({"name": "Wayne Enterprises", "tier": "starter"}) # Process billing await engine.process_billing_cycle() # Generate performance bonus perf_metrics = {"revenue_increase": 50000} bonus = await engine.generate_performance_bonus("cust_1", perf_metrics) print(f"Performance bonus: ${bonus}") # Calculate white label revenue wl_revenue = await engine.calculate_white_label_licensing_revenue(3) print(f"White label revenue: ${wl_revenue}") # Get dashboard dashboard = await engine.get_monetization_dashboard() print("\nMonetization Dashboard:") print(f"MRR: ${dashboard['customer_metrics']['mrr']}") print(f"Total Customers: {dashboard['customer_metrics']['total_customers']}") print(f"Subscription Breakdown: {dashboard['subscription_breakdown']}") return engine if __name__ == "__main__": # Run test asyncio.run(test_monetization_engine())