Upload agents/conversion_cro_agent.py with huggingface_hub

agents/conversion_cro_agent.py

@@ -0,0 +1,151 @@
+import asyncio
+from typing import Dict, List, Any
+from core.agent import BaseAgent
+from core.models import AgentConfig, Task, AgentMessage, SEOData
+import logging
+import random
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+class ConversionCROAgent(BaseAgent):
+    """Conversion & CRO Agent responsible for landing page optimization"""
+    
+    def __init__(self, config: AgentConfig):
+        super().__init__(config)
+        self.landing_page_analytics = {}
+        self.cro_experiments = []
+        self.conversion_funnel_data = {}
+        self.revenue_attribution = {}
+        
+    async def execute(self):
+        """Execute conversion and CRO functions"""
+        logger.info(f"{self.name} executing conversion optimization...")
+        
+        # Analyze landing pages
+        await self.analyze_landing_pages()
+        
+        # Set up CRO experiments
+        await self.setup_cro_experiments()
+        
+        # Analyze conversion funnels
+        await self.analyze_funnels()
+        
+        # Attribute revenue to SEO efforts
+        await self.attribute_revenue()
+    
+    async def analyze_landing_pages(self):
+        """Analyze landing page performance"""
+        logger.info(f"{self.name} analyzing landing pages...")
+        
+        # Simulate landing page analysis
+        analytics_data = {
+            "top_pages": [
+                {"url": "/landing1", "views": 12500, "cvr": 3.2, "bounce_rate": 45.2},
+                {"url": "/landing2", "views": 8900, "cvr": 2.8, "bounce_rate": 52.1},
+                {"url": "/landing3", "views": 6200, "cvr": 4.1, "bounce_rate": 38.7}
+            ],
+            "avg_cvr": 3.3,
+            "improvement_areas": ["cta_visibility", "form_length", "page_speed"]
+        }
+        
+        self.landing_page_analytics.update(analytics_data)
+        
+        # Log analytics
+        logger.info(f"Landing page analytics: {analytics_data}")
+    
+    async def setup_cro_experiments(self):
+        """Set up CRO experiments and A/B tests"""
+        logger.info(f"{self.name} setting up CRO experiments...")
+        
+        # Simulate CRO experiment setup
+        experiments = [
+            {
+                "name": "CTA Button Color Test",
+                "page": "/landing1",
+                "variations": ["red_cta", "green_cta", "blue_cta"],
+                "goal": "click_through_rate",
+                "status": "running",
+                "duration": "2_weeks"
+            },
+            {
+                "name": "Form Length Optimization",
+                "page": "/contact",
+                "variations": ["long_form", "short_form", "progressive_form"],
+                "goal": "form_submissions",
+                "status": "scheduled",
+                "duration": "3_weeks"
+            },
+            {
+                "name": "Headline Testing",
+                "page": "/pricing",
+                "variations": ["feature_based_headlines", "benefit_based_headlines"],
+                "goal": "demo_requests",
+                "status": "draft",
+                "duration": "2_weeks"
+            }
+        ]
+        
+        self.cro_experiments.extend(experiments)
+        
+        # Log experiments
+        logger.info(f"Set up {len(experiments)} CRO experiments")
+    
+    async def analyze_funnels(self):
+        """Analyze conversion funnels"""
+        logger.info(f"{self.name} analyzing conversion funnels...")
+        
+        # Simulate funnel analysis
+        funnel_data = {
+            "visitor_to_lead": {"rate": 8.5, "drop_off_points": ["/pricing", "/contact-form"]},
+            "lead_to_customer": {"rate": 22.1, "drop_off_points": ["/checkout", "/payment"]},
+            "customer_lifetime_value": 1250,
+            "acquisition_cost": 45
+        }
+        
+        self.conversion_funnel_data.update(funnel_data)
+        
+        # Log funnel data
+        logger.info(f"Funnel analysis: {funnel_data}")
+    
+    async def attribute_revenue(self):
+        """Attribute revenue to SEO efforts"""
+        logger.info(f"{self.name} attributing revenue to SEO...")
+        
+        # Simulate revenue attribution
+        revenue_data = {
+            "organic_traffic_revenue": 25000,
+            "seo_contribution": 0.65,  # 65% of traffic comes from SEO
+            "revenue_per_visitor": 2.10,
+            "roi_from_seo": 4.2  # 420% ROI
+        }
+        
+        self.revenue_attribution.update(revenue_data)
+        
+        # Send revenue attribution to CEO and client management
+        await self.send_message(
+            recipient="ceo_strategy",
+            content=f"Revenue attribution: {revenue_data}",
+            message_type="info"
+        )
+        
+        await self.send_message(
+            recipient="client_management",
+            content=f"Revenue attribution: {revenue_data}",
+            message_type="info"
+        )
+    
+    async def _execute_task_logic(self, task: Task) -> Dict[str, Any]:
+        """Execute specific task logic for Conversion & CRO agent"""
+        if task.type == "analyze_landing_pages":
+            await self.analyze_landing_pages()
+            return {"status": "completed", "result": self.landing_page_analytics}
+        elif task.type == "setup_cro_experiments":
+            await self.setup_cro_experiments()
+            return {"status": "completed", "result": self.cro_experiments}
+        elif task.type == "analyze_funnels":
+            await self.analyze_funnels()
+            return {"status": "completed", "result": self.conversion_funnel_data}
+        else:
+            return {"status": "error", "message": f"Unknown task type: {task.type}"}