#!/usr/bin/env python3
"""
Marketing Automation MCP Demo for DoorDash Interview
Demonstrates key capabilities with realistic sample data
"""
import asyncio
import json
import random
from datetime import datetime, timedelta
from typing import Dict, List, Any
import os
from pathlib import Path
# For demo purposes, we'll simulate API responses
DEMO_MODE = os.getenv("DEMO_MODE", "true").lower() == "true"
class MarketingAutomationDemo:
"""Demo showcasing Marketing Automation MCP capabilities"""
def __init__(self):
self.sample_campaigns = self._generate_sample_campaigns()
self.demo_results = {}
def _generate_sample_campaigns(self) -> List[Dict[str, Any]]:
"""Generate realistic DoorDash marketing campaign data"""
campaigns = [
{
"campaign_id": "dd_search_001",
"name": "DoorDash Search - Food Delivery",
"platform": "google_ads",
"budget": 15000.0,
"impressions": 850000,
"clicks": 17000,
"conversions": 425,
"cost": 14500.0,
"revenue": 21250.0,
"ctr": 2.0,
"conversion_rate": 2.5,
"cpa": 34.12,
"roi": 46.55,
"status": "underperforming"
},
{
"campaign_id": "dd_display_002",
"name": "DoorDash Display - Brand Awareness",
"platform": "google_ads",
"budget": 10000.0,
"impressions": 2000000,
"clicks": 20000,
"conversions": 800,
"cost": 9800.0,
"revenue": 40000.0,
"ctr": 1.0,
"conversion_rate": 4.0,
"cpa": 12.25,
"roi": 308.16,
"status": "performing"
},
{
"campaign_id": "dd_social_003",
"name": "DoorDash Social - New User Acquisition",
"platform": "facebook_ads",
"budget": 20000.0,
"impressions": 1500000,
"clicks": 30000,
"conversions": 1200,
"cost": 19500.0,
"revenue": 60000.0,
"ctr": 2.0,
"conversion_rate": 4.0,
"cpa": 16.25,
"roi": 207.69,
"status": "performing"
},
{
"campaign_id": "dd_video_004",
"name": "DoorDash Video - Restaurant Partners",
"platform": "facebook_ads",
"budget": 8000.0,
"impressions": 500000,
"clicks": 5000,
"conversions": 100,
"cost": 7800.0,
"revenue": 5000.0,
"ctr": 1.0,
"conversion_rate": 2.0,
"cpa": 78.0,
"roi": -35.90,
"status": "critical"
},
{
"campaign_id": "dd_retarget_005",
"name": "DoorDash Retargeting - Cart Abandoners",
"platform": "google_ads",
"budget": 5000.0,
"impressions": 250000,
"clicks": 10000,
"conversions": 800,
"cost": 4800.0,
"revenue": 40000.0,
"ctr": 4.0,
"conversion_rate": 8.0,
"cpa": 6.0,
"roi": 733.33,
"status": "star_performer"
}
]
return campaigns
async def run_demo(self):
"""Run the complete demo workflow"""
print("\n" + "="*80)
print("🚀 DoorDash Marketing Automation Demo")
print("="*80)
# Step 1: Connect to marketing accounts
await self.connect_to_accounts()
# Step 2: Analyze current performance
await self.analyze_performance()
# Step 3: Identify underperforming campaigns
await self.identify_underperformers()
# Step 4: Generate AI optimization recommendations
await self.generate_optimizations()
# Step 5: Show projected improvements
await self.show_projections()
# Step 6: Display savings dashboard
await self.display_savings_dashboard()
# Generate presentation
await self.generate_presentation()
return self.demo_results
async def connect_to_accounts(self):
"""Simulate connecting to marketing platforms"""
print("\n📡 Step 1: Connecting to Marketing Platforms")
print("-" * 50)
platforms = [
("Google Ads", "✓ Connected - 3 accounts, $58,000 monthly budget"),
("Facebook Ads", "✓ Connected - 2 accounts, $28,000 monthly budget"),
("Google Analytics", "✓ Connected - Tracking 5 properties")
]
for platform, status in platforms:
print(f" {platform}: {status}")
await asyncio.sleep(0.5) # Simulate connection time
print("\n✅ All platforms connected successfully!")
self.demo_results["connections"] = {
"total_accounts": 5,
"total_monthly_budget": 86000,
"platforms_connected": 3
}
async def analyze_performance(self):
"""Analyze current campaign performance"""
print("\n📊 Step 2: Analyzing Campaign Performance")
print("-" * 50)
total_spend = sum(c["cost"] for c in self.sample_campaigns)
total_revenue = sum(c["revenue"] for c in self.sample_campaigns)
total_conversions = sum(c["conversions"] for c in self.sample_campaigns)
avg_roi = ((total_revenue - total_spend) / total_spend) * 100
print(f"\n Campaign Summary (Last 30 Days):")
print(f" • Total Campaigns: {len(self.sample_campaigns)}")
print(f" • Total Spend: ${total_spend:,.2f}")
print(f" • Total Revenue: ${total_revenue:,.2f}")
print(f" • Total Conversions: {total_conversions:,}")
print(f" • Average ROI: {avg_roi:.1f}%")
print("\n Performance by Campaign:")
for campaign in self.sample_campaigns:
status_emoji = {
"star_performer": "⭐",
"performing": "✅",
"underperforming": "⚠️",
"critical": "🚨"
}[campaign["status"]]
print(f" {status_emoji} {campaign['name']}")
print(f" ROI: {campaign['roi']:.1f}% | CPA: ${campaign['cpa']:.2f} | "
f"Conv Rate: {campaign['conversion_rate']:.1f}%")
self.demo_results["current_performance"] = {
"total_spend": total_spend,
"total_revenue": total_revenue,
"total_conversions": total_conversions,
"average_roi": avg_roi
}
async def identify_underperformers(self):
"""Identify and analyze underperforming campaigns"""
print("\n🔍 Step 3: Identifying Optimization Opportunities")
print("-" * 50)
underperformers = [c for c in self.sample_campaigns
if c["status"] in ["underperforming", "critical"]]
print(f"\n Found {len(underperformers)} campaigns needing optimization:")
for campaign in underperformers:
print(f"\n 🎯 {campaign['name']}")
print(f" Current ROI: {campaign['roi']:.1f}%")
# Identify specific issues
issues = []
if campaign["ctr"] < 1.5:
issues.append(f"Low CTR ({campaign['ctr']:.1f}% vs 2.5% benchmark)")
if campaign["conversion_rate"] < 3.0:
issues.append(f"Low conversion rate ({campaign['conversion_rate']:.1f}% vs 4% benchmark)")
if campaign["cpa"] > 30:
issues.append(f"High CPA (${campaign['cpa']:.2f} vs $25 target)")
print(" Issues identified:")
for issue in issues:
print(f" • {issue}")
self.demo_results["underperformers"] = underperformers
async def generate_optimizations(self):
"""Generate AI-powered optimization recommendations"""
print("\n🤖 Step 4: AI-Generated Optimization Recommendations")
print("-" * 50)
optimizations = [
{
"campaign": "DoorDash Search - Food Delivery",
"recommendations": [
{
"action": "Implement dayparting strategy",
"details": "Increase bids 30% during lunch (11am-2pm) and dinner (5pm-9pm)",
"impact": "Expected 25% increase in conversions",
"confidence": 0.92
},
{
"action": "Refine keyword targeting",
"details": "Add 15 negative keywords, pause 8 low-performing keywords",
"impact": "Reduce wasted spend by $2,000/month",
"confidence": 0.88
},
{
"action": "Update ad copy",
"details": "Test 'Free delivery on first order' messaging",
"impact": "Projected 15% CTR improvement",
"confidence": 0.85
}
]
},
{
"campaign": "DoorDash Video - Restaurant Partners",
"recommendations": [
{
"action": "Pause campaign and reallocate budget",
"details": "Move $6,000 to high-performing retargeting campaign",
"impact": "Avoid $3,000 monthly loss, gain $18,000 from reallocation",
"confidence": 0.95
},
{
"action": "Redesign creative strategy",
"details": "Focus on restaurant success stories instead of features",
"impact": "Expected 3x improvement in engagement",
"confidence": 0.78
}
]
}
]
for opt in optimizations:
print(f"\n 📋 {opt['campaign']}:")
for i, rec in enumerate(opt['recommendations'], 1):
print(f"\n {i}. {rec['action']}")
print(f" Details: {rec['details']}")
print(f" Impact: {rec['impact']}")
print(f" Confidence: {rec['confidence']*100:.0f}%")
self.demo_results["optimizations"] = optimizations
async def show_projections(self):
"""Show projected improvements from optimizations"""
print("\n📈 Step 5: Projected Impact Analysis")
print("-" * 50)
# Calculate projections
current_total_spend = sum(c["cost"] for c in self.sample_campaigns)
current_total_revenue = sum(c["revenue"] for c in self.sample_campaigns)
current_roi = ((current_total_revenue - current_total_spend) / current_total_spend) * 100
# Projected improvements
projected_spend = current_total_spend - 2000 # Reduced waste
projected_revenue = current_total_revenue * 1.28 # 28% improvement
projected_roi = ((projected_revenue - projected_spend) / projected_spend) * 100
roi_improvement = projected_roi - current_roi
print("\n Current State vs. Projected (After Optimizations):")
print(f"\n {'Metric':<20} {'Current':>15} {'Projected':>15} {'Change':>15}")
print(" " + "-"*65)
print(f" {'Monthly Spend':<20} ${current_total_spend:>14,.2f} ${projected_spend:>14,.2f} "
f"${projected_spend-current_total_spend:>14,.2f}")
print(f" {'Monthly Revenue':<20} ${current_total_revenue:>14,.2f} ${projected_revenue:>14,.2f} "
f"${projected_revenue-current_total_revenue:>14,.2f}")
print(f" {'ROI':<20} {current_roi:>14.1f}% {projected_roi:>14.1f}% "
f"{roi_improvement:>14.1f}%")
print(f" {'Conversions':<20} {sum(c['conversions'] for c in self.sample_campaigns):>15,} "
f"{int(sum(c['conversions'] for c in self.sample_campaigns) * 1.35):>15,} "
f"{int(sum(c['conversions'] for c in self.sample_campaigns) * 0.35):>15,}")
print(f"\n 💰 Projected Annual Impact:")
print(f" • Additional Revenue: ${(projected_revenue - current_total_revenue) * 12:,.2f}")
print(f" • Cost Savings: ${(current_total_spend - projected_spend) * 12:,.2f}")
print(f" • Net Benefit: ${((projected_revenue - current_total_revenue) + (current_total_spend - projected_spend)) * 12:,.2f}")
self.demo_results["projections"] = {
"monthly_revenue_increase": projected_revenue - current_total_revenue,
"monthly_cost_savings": current_total_spend - projected_spend,
"roi_improvement": roi_improvement,
"annual_net_benefit": ((projected_revenue - current_total_revenue) +
(current_total_spend - projected_spend)) * 12
}
async def display_savings_dashboard(self):
"""Display time and cost savings from automation"""
print("\n⏱️ Step 6: Automation Savings Dashboard")
print("-" * 50)
# Automation metrics
tasks = [
{"name": "Campaign Performance Analysis", "manual_hours": 8, "automated_minutes": 2},
{"name": "Budget Optimization", "manual_hours": 6, "automated_minutes": 1},
{"name": "A/B Test Analysis", "manual_hours": 4, "automated_minutes": 0.5},
{"name": "Report Generation", "manual_hours": 10, "automated_minutes": 3},
{"name": "Audience Segmentation", "manual_hours": 12, "automated_minutes": 2}
]
hourly_rate = 75 # Marketing analyst hourly rate
print("\n Weekly Time Savings by Task:")
print(f" {'Task':<35} {'Manual':>10} {'Automated':>12} {'Time Saved':>12}")
print(" " + "-"*70)
total_manual_hours = 0
total_automated_hours = 0
for task in tasks:
manual = task["manual_hours"]
automated = task["automated_minutes"] / 60
saved = manual - automated
total_manual_hours += manual
total_automated_hours += automated
print(f" {task['name']:<35} {manual:>9.1f}h {automated:>11.1f}h {saved:>11.1f}h")
total_saved = total_manual_hours - total_automated_hours
weekly_cost_saved = total_saved * hourly_rate
annual_hours_saved = total_saved * 52
annual_cost_saved = weekly_cost_saved * 52
print(" " + "-"*70)
print(f" {'TOTAL':<35} {total_manual_hours:>9.1f}h {total_automated_hours:>11.1f}h "
f"{total_saved:>11.1f}h")
print(f"\n 💼 Resource Savings Summary:")
print(f" • Weekly hours saved: {total_saved:.1f} hours")
print(f" • Weekly cost saved: ${weekly_cost_saved:,.2f}")
print(f" • Annual hours saved: {annual_hours_saved:,.0f} hours")
print(f" • Annual cost saved: ${annual_cost_saved:,.2f}")
print(f" • Equivalent to: {annual_hours_saved/2080:.1f} full-time employees")
# ROI of automation
automation_cost = 50000 # Annual cost of automation platform
total_benefit = annual_cost_saved + self.demo_results["projections"]["annual_net_benefit"]
automation_roi = ((total_benefit - automation_cost) / automation_cost) * 100
print(f"\n 📊 Automation ROI:")
print(f" • Total Annual Benefit: ${total_benefit:,.2f}")
print(f" • Automation Cost: ${automation_cost:,.2f}")
print(f" • ROI: {automation_roi:.0f}%")
print(f" • Payback Period: {automation_cost/total_benefit*12:.1f} months")
self.demo_results["savings"] = {
"weekly_hours_saved": total_saved,
"annual_cost_saved": annual_cost_saved,
"fte_equivalent": annual_hours_saved/2080,
"automation_roi": automation_roi
}
async def generate_presentation(self):
"""Generate presentation slides"""
print("\n📑 Generating Presentation Deck...")
print("-" * 50)
# Create presentation data
presentation = PresentationGenerator(self.demo_results)
presentation.generate_slides()
print("✅ Presentation deck generated: doordash_demo_deck.html")
print(" Open in browser to view interactive slides")
class PresentationGenerator:
"""Generate HTML presentation deck from demo results"""
def __init__(self, demo_results: Dict[str, Any]):
self.results = demo_results
def generate_slides(self):
"""Generate HTML presentation"""
html_content = f"""
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>DoorDash Marketing Automation Demo</title>
<style>
body {{
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
margin: 0;
padding: 0;
background: #1a1a1a;
color: #ffffff;
overflow: hidden;
}}
.slide {{
width: 100vw;
height: 100vh;
display: none;
padding: 60px;
box-sizing: border-box;
position: relative;
}}
.slide.active {{
display: flex;
flex-direction: column;
justify-content: center;
}}
h1 {{
font-size: 48px;
margin: 0 0 20px 0;
color: #ff3008;
}}
h2 {{
font-size: 36px;
margin: 0 0 30px 0;
color: #ffffff;
}}
h3 {{
font-size: 28px;
margin: 20px 0;
color: #ff3008;
}}
.metric {{
font-size: 64px;
font-weight: bold;
color: #ff3008;
margin: 20px 0;
}}
.sub-metric {{
font-size: 24px;
color: #cccccc;
margin: 10px 0;
}}
.grid {{
display: grid;
grid-template-columns: repeat(2, 1fr);
gap: 40px;
margin: 30px 0;
}}
.card {{
background: #2a2a2a;
padding: 30px;
border-radius: 12px;
border: 2px solid #ff3008;
}}
.progress-bar {{
width: 100%;
height: 8px;
background: #333;
border-radius: 4px;
overflow: hidden;
margin: 20px 0;
}}
.progress {{
height: 100%;
background: #ff3008;
transition: width 1s ease;
}}
.controls {{
position: fixed;
bottom: 30px;
right: 30px;
display: flex;
gap: 10px;
}}
button {{
background: #ff3008;
color: white;
border: none;
padding: 12px 24px;
border-radius: 6px;
font-size: 16px;
cursor: pointer;
transition: all 0.3s;
}}
button:hover {{
background: #e62a00;
transform: translateY(-2px);
}}
.highlight {{
color: #ff3008;
font-weight: bold;
}}
.savings-grid {{
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 30px;
margin: 40px 0;
}}
.savings-card {{
text-align: center;
padding: 20px;
background: #2a2a2a;
border-radius: 8px;
}}
.icon {{
font-size: 48px;
margin-bottom: 10px;
}}
@keyframes fadeIn {{
from {{ opacity: 0; transform: translateY(20px); }}
to {{ opacity: 1; transform: translateY(0); }}
}}
.fade-in {{
animation: fadeIn 0.6s ease forwards;
}}
</style>
</head>
<body>
<!-- Slide 1: Title -->
<div class="slide active">
<h1>Marketing Automation with AI</h1>
<h2>Transforming DoorDash's Marketing Operations</h2>
<div class="sub-metric">Powered by Model Context Protocol (MCP)</div>
<div style="margin-top: 60px;">
<div class="metric fade-in">{roi_improvement:.0f}% ROI Improvement</div>
<div class="sub-metric fade-in" style="animation-delay: 0.3s">
${annual_benefit:,.0f} Annual Benefit
</div>
</div>
</div>
<!-- Slide 2: Current State -->
<div class="slide">
<h2>Current Campaign Performance</h2>
<div class="grid">
<div class="card fade-in">
<h3>Monthly Spend</h3>
<div class="metric">${current_spend:,.0f}</div>
<div class="sub-metric">Across 5 campaigns</div>
</div>
<div class="card fade-in" style="animation-delay: 0.2s">
<h3>Average ROI</h3>
<div class="metric">{current_roi:.1f}%</div>
<div class="sub-metric">Below industry benchmark</div>
</div>
<div class="card fade-in" style="animation-delay: 0.4s">
<h3>Underperforming</h3>
<div class="metric">2</div>
<div class="sub-metric">Campaigns need optimization</div>
</div>
<div class="card fade-in" style="animation-delay: 0.6s">
<h3>Opportunity</h3>
<div class="metric">${waste:,.0f}</div>
<div class="sub-metric">Monthly wasted spend</div>
</div>
</div>
</div>
<!-- Slide 3: AI Recommendations -->
<div class="slide">
<h2>AI-Powered Optimization Strategy</h2>
<div style="margin: 40px 0;">
<h3>🎯 DoorDash Search Campaign</h3>
<ul style="font-size: 24px; line-height: 1.8;">
<li class="fade-in">Implement dayparting: <span class="highlight">+25% conversions</span></li>
<li class="fade-in" style="animation-delay: 0.2s">Refine keywords: <span class="highlight">-$2,000/month waste</span></li>
<li class="fade-in" style="animation-delay: 0.4s">Update ad copy: <span class="highlight">+15% CTR</span></li>
</ul>
<h3 style="margin-top: 40px;">🚨 Video Campaign (Critical)</h3>
<ul style="font-size: 24px; line-height: 1.8;">
<li class="fade-in" style="animation-delay: 0.6s">Pause & reallocate: <span class="highlight">+$21,000 monthly gain</span></li>
<li class="fade-in" style="animation-delay: 0.8s">Redesign creative: <span class="highlight">3x engagement</span></li>
</ul>
</div>
<div class="progress-bar">
<div class="progress" style="width: 88%;"></div>
</div>
<div class="sub-metric">Average Confidence Score: 88%</div>
</div>
<!-- Slide 4: Projected Impact -->
<div class="slide">
<h2>Projected Business Impact</h2>
<div class="grid">
<div style="flex: 1;">
<h3>Revenue Growth</h3>
<div class="metric fade-in">${monthly_revenue_increase:,.0f}</div>
<div class="sub-metric">Additional monthly revenue</div>
<h3 style="margin-top: 40px;">Cost Reduction</h3>
<div class="metric fade-in" style="animation-delay: 0.3s">${monthly_cost_savings:,.0f}</div>
<div class="sub-metric">Monthly savings from optimization</div>
</div>
<div style="flex: 1; display: flex; align-items: center; justify-content: center;">
<div style="text-align: center;">
<div style="font-size: 28px; margin-bottom: 20px;">Annual Net Benefit</div>
<div class="metric" style="font-size: 80px; color: #00ff00;">
${annual_net_benefit:,.0f}
</div>
<div class="sub-metric" style="font-size: 28px; margin-top: 20px;">
ROI Improvement: <span class="highlight">{roi_improvement:.1f}%</span>
</div>
</div>
</div>
</div>
</div>
<!-- Slide 5: Time Savings -->
<div class="slide">
<h2>Operational Efficiency Gains</h2>
<div class="savings-grid">
<div class="savings-card fade-in">
<div class="icon">⏱️</div>
<div class="metric" style="font-size: 48px;">{weekly_hours:.0f}</div>
<div class="sub-metric">Hours saved weekly</div>
</div>
<div class="savings-card fade-in" style="animation-delay: 0.2s">
<div class="icon">💰</div>
<div class="metric" style="font-size: 48px;">${annual_labor_saved:,.0f}</div>
<div class="sub-metric">Annual labor savings</div>
</div>
<div class="savings-card fade-in" style="animation-delay: 0.4s">
<div class="icon">👥</div>
<div class="metric" style="font-size: 48px;">{fte:.1f}</div>
<div class="sub-metric">FTE equivalent</div>
</div>
</div>
<div style="margin-top: 40px;">
<h3>Task Automation Breakdown</h3>
<div style="font-size: 20px; line-height: 1.8;">
<div class="fade-in" style="animation-delay: 0.6s">
📊 Campaign Analysis: <span class="highlight">8h → 2min</span> (99.6% reduction)
</div>
<div class="fade-in" style="animation-delay: 0.7s">
💰 Budget Optimization: <span class="highlight">6h → 1min</span> (99.7% reduction)
</div>
<div class="fade-in" style="animation-delay: 0.8s">
📈 Report Generation: <span class="highlight">10h → 3min</span> (99.5% reduction)
</div>
</div>
</div>
</div>
<!-- Slide 6: ROI Summary -->
<div class="slide">
<h2>Return on Investment</h2>
<div style="text-align: center; margin: 60px 0;">
<div class="metric" style="font-size: 120px; margin-bottom: 40px;">
{automation_roi:.0f}%
</div>
<div class="sub-metric" style="font-size: 32px;">First Year ROI</div>
<div class="grid" style="margin-top: 60px; max-width: 800px; margin-left: auto; margin-right: auto;">
<div class="card">
<h3>Investment</h3>
<div style="font-size: 36px;">$50,000</div>
<div class="sub-metric">Annual platform cost</div>
</div>
<div class="card">
<h3>Payback Period</h3>
<div style="font-size: 36px;">{payback:.1f} months</div>
<div class="sub-metric">Break-even timeline</div>
</div>
</div>
</div>
</div>
<!-- Slide 7: Next Steps -->
<div class="slide">
<h2>Implementation Roadmap</h2>
<div style="font-size: 28px; line-height: 2; margin: 40px 0;">
<div class="fade-in">
<span class="highlight">Week 1-2:</span> Platform setup and integration
</div>
<div class="fade-in" style="animation-delay: 0.2s">
<span class="highlight">Week 3-4:</span> Historical data analysis and baseline
</div>
<div class="fade-in" style="animation-delay: 0.4s">
<span class="highlight">Month 2:</span> Implement first optimizations
</div>
<div class="fade-in" style="animation-delay: 0.6s">
<span class="highlight">Month 3:</span> Scale to all campaigns
</div>
<div class="fade-in" style="animation-delay: 0.8s">
<span class="highlight">Ongoing:</span> Continuous optimization and reporting
</div>
</div>
<div style="text-align: center; margin-top: 60px;">
<button onclick="window.location.href='mailto:demo@marketing-automation.ai'"
style="font-size: 24px; padding: 20px 40px;">
Schedule Deep Dive Discussion
</button>
</div>
</div>
<!-- Navigation -->
<div class="controls">
<button onclick="previousSlide()">Previous</button>
<button onclick="nextSlide()">Next</button>
<button onclick="autoPlay()">Auto Play</button>
</div>
<script>
let currentSlide = 0;
const slides = document.querySelectorAll('.slide');
let autoPlayInterval = null;
function showSlide(index) {{
slides.forEach(slide => slide.classList.remove('active'));
slides[index].classList.add('active');
// Reset animations
const fadeElements = slides[index].querySelectorAll('.fade-in');
fadeElements.forEach(el => {{
el.style.animation = 'none';
el.offsetHeight; // Trigger reflow
el.style.animation = null;
}});
}}
function nextSlide() {{
currentSlide = (currentSlide + 1) % slides.length;
showSlide(currentSlide);
}}
function previousSlide() {{
currentSlide = (currentSlide - 1 + slides.length) % slides.length;
showSlide(currentSlide);
}}
function autoPlay() {{
if (autoPlayInterval) {{
clearInterval(autoPlayInterval);
autoPlayInterval = null;
}} else {{
autoPlayInterval = setInterval(nextSlide, 8000);
}}
}}
// Keyboard navigation
document.addEventListener('keydown', (e) => {{
if (e.key === 'ArrowRight') nextSlide();
if (e.key === 'ArrowLeft') previousSlide();
if (e.key === ' ') autoPlay();
}});
</script>
</body>
</html>
"""
# Format with actual values
html_content = html_content.format(
roi_improvement=self.results['projections']['roi_improvement'],
annual_benefit=self.results['projections']['annual_net_benefit'] +
self.results['savings']['annual_cost_saved'],
current_spend=self.results['current_performance']['total_spend'],
current_roi=self.results['current_performance']['average_roi'],
waste=2000, # Estimated monthly waste
monthly_revenue_increase=self.results['projections']['monthly_revenue_increase'],
monthly_cost_savings=self.results['projections']['monthly_cost_savings'],
annual_net_benefit=self.results['projections']['annual_net_benefit'],
weekly_hours=self.results['savings']['weekly_hours_saved'],
annual_labor_saved=self.results['savings']['annual_cost_saved'],
fte=self.results['savings']['fte_equivalent'],
automation_roi=self.results['savings']['automation_roi'],
payback=50000/(self.results['projections']['annual_net_benefit'] +
self.results['savings']['annual_cost_saved'])*12
)
# Save presentation
with open('doordash_demo_deck.html', 'w') as f:
f.write(html_content)
# Main execution
async def main():
"""Run the demo"""
demo = MarketingAutomationDemo()
results = await demo.run_demo()
print("\n" + "="*80)
print("✅ Demo Complete!")
print("="*80)
print("\nKey Takeaways:")
print(f"• ROI Improvement: {results['projections']['roi_improvement']:.1f}%")
print(f"• Annual Benefit: ${results['projections']['annual_net_benefit'] + results['savings']['annual_cost_saved']:,.2f}")
print(f"• Time Saved: {results['savings']['weekly_hours_saved']:.1f} hours/week")
print(f"• Automation ROI: {results['savings']['automation_roi']:.0f}%")
# Save results to JSON for further analysis
with open('demo_results.json', 'w') as f:
json.dump(results, f, indent=2)
print("\n📄 Results saved to: demo_results.json")
print("🎯 Presentation deck: doordash_demo_deck.html")
if __name__ == "__main__":
asyncio.run(main())
