The Challenge
Business Problem
Marketing teams send campaigns but lack time to deeply analyze results. They miss patterns in open rates, click behavior, and unsubscribe triggers that could dramatically improve performance.
The Approach
Solution Overview
Connect SendGrid MCP Server with Google Analytics and Slack to automatically analyze campaign performance, identify winning segments, and recommend next actions.
Step-by-Step
Implementation Steps
1
Pull Campaign Data
Fetch campaign metrics from SendGrid including opens, clicks, bounces, and unsubscribes.
2
Segment Analysis
Break down performance by audience segment, send time, subject line, and content type.
3
Generate Insights
Identify statistically significant patterns in high-performing campaigns.
async function analyzeCampaign(campaignId) {
const stats = await sendgrid.getCampaignStats({ campaign_id: campaignId });
const insights = {
openRate: stats.opens / stats.delivered,
clickRate: stats.clicks / stats.opens,
bestSegment: findBestSegment(stats.segments),
recommendation: generateRecommendation(stats)
};
await slack.sendMessage({ channel: '#marketing', text: formatInsights(insights) });
}4
A/B Test Recommendations
Suggest subject lines, send times, and content variants based on historical performance.
Code
Code Examples
typescript
Segment Analyzer
function findBestSegment(segments) {
return segments.sort((a, b) => (b.clicks / b.opens) - (a.clicks / a.opens))[0];
}Overview
ComplexityEasy
Estimated Time~6 hours
Tools Used
SendGrid MCP ServerGoogle Analytics MCP ServerSlack MCP Server
Industry
MarketingSaaSE-commerce
ROI Metrics
Time Saved8 hours/week
Cost Reduction25% improvement in email ROI
Efficiency GainData-driven campaign decisions