Marketing Campaign Optimizer

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Overview

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What the Agent Needs to Accomplish

• Analyze campaign performance across channels
• Identify high-value customer segments
• Calculate ROI and conversion metrics
• Optimize marketing spend allocation
• Track campaign effectiveness over time
• Recommend campaign adjustments

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How Pylar Helps

• Unified Campaign View: Combining campaign data, customer segments, and conversion metrics
• Real-time Analysis: Querying current campaign performance
• Multi-Channel Integration: Joining data from multiple marketing channels
• ROI Calculation: Automated ROI and conversion rate calculations
• Segment Analysis: Identifying profitable customer segments

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Without Pylar vs With Pylar

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Without Pylar

• ❌ Multiple marketing platforms (Google Ads, Facebook, email, etc.)
• ❌ Complex API integrations for each channel
• ❌ Manual campaign analysis
• ❌ Difficult to correlate campaigns with conversions
• ❌ Time-consuming ROI calculations
• ❌ Limited real-time insights

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With Pylar

• ✅ Single endpoint for all campaign data
• ✅ Real-time campaign analysis
• ✅ Automated ROI calculations
• ✅ Unified conversion tracking
• ✅ Easy campaign optimization

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Step-by-Step Implementation

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Step 1: Connect Data Sources

1. Connect Marketing Platforms (Google Ads, Facebook Ads, LinkedIn Ads)
2. Connect Email Platform (Email campaigns, open rates)
3. Connect Analytics (Website traffic, conversions)
4. Connect CRM (Customer segments, conversion data)

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Step 2: Create Campaign Views

CREATE VIEW campaign_performance AS
SELECT 
  c.campaign_id,
  c.campaign_name,
  c.channel,
  c.start_date,
  c.end_date,
  c.spend,
  c.impressions,
  c.clicks,
  c.conversions,
  -- Metrics
  (c.clicks / NULLIF(c.impressions, 0)) * 100 as ctr,
  (c.conversions / NULLIF(c.clicks, 0)) * 100 as conversion_rate,
  c.revenue,
  (c.revenue - c.spend) as profit,
  ((c.revenue - c.spend) / NULLIF(c.spend, 0)) * 100 as roi_percent
FROM marketing.campaigns c;

CREATE VIEW segment_performance AS
SELECT 
  s.segment_name,
  s.channel,
  COUNT(DISTINCT c.customer_id) as customers,
  SUM(c.spend) as total_spend,
  SUM(c.revenue) as total_revenue,
  AVG(c.conversion_rate) as avg_conversion_rate,
  AVG(c.roi_percent) as avg_roi
FROM marketing.segments s
JOIN marketing.campaigns c ON s.campaign_id = c.campaign_id
GROUP BY s.segment_name, s.channel;

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Step 3: Create MCP Tools

• analyze_campaign_performance(campaign_id: string, start_date: date, end_date: date)

• identify_high_value_segments(min_roi: number, channel: string)

• optimize_marketing_spend(budget: number, channels: array)

• analyze_campaign_roi(period: string, channel: string)

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Example Agent Interactions

1. LinkedIn B2B Campaign: 285% ROI, $50K revenue from$13K spend
2. Email Product Launch: 240% ROI, $72K revenue from$30K spend
3. Google Search - Enterprise: 210% ROI, $105K revenue from$50K spend

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Outcomes

• ROI Improvement: 35% increase in average ROI
• Spend Efficiency: 25% better budget allocation
• Conversion Rate: 20% improvement in conversion rates
• Campaign Performance: 40% reduction in underperforming campaigns

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Next Steps

• Content Performance Analyzer Example
• A/B Testing Assistant Example
• Marketing Attribution Analyzer Example