SmartLead Campaign Performance Tracker

Task

Pull performance data across all active SmartLead campaigns using @SmartLead/List All CampaignsName it "SmartLead/List All Campaigns" and call it with @SmartLead/List All Campaigns, then analyze each one with @SmartLead/Get Campaign Top-Level Analytics and @SmartLead/Get Campaign Analytics by Date RangeName it "SmartLead/Get Campaign Analytics by Date Range" and call it with @SmartLead/Get Campaign Analytics by Date Range. For campaigns with concerning metrics, drill into lead-level data with @SmartLead/Get Campaign StatisticsName it "SmartLead/Get Campaign Statistics" and call it with @SmartLead/Get Campaign Statistics. Export a summary report to @Google Sheets/Update SpreadsheetName it "Google Sheets/Update Spreadsheet" and call it with @Google Sheets/Update Spreadsheet.

Example: Show me how all my SmartLead campaigns performed last month, highlight which sequences are winning, and put the report in my Google Sheet.

Input

The user will provide a date range and optionally specific campaigns to focus on.

Example: "How did my campaigns perform in January?" or "Compare my Q4 outbound campaigns and export results to Google Sheets"

Context

Metrics to Analyze

For each campaign, pull:

• Total sent, opened, clicked, replied counts
• Open rate, click rate, reply rate (calculated)
• Bounce rate and unsubscribe rate
• Unique opens vs. total opens (engagement depth)
• Lead progress: not started, in progress, completed, stopped

Benchmarking Thresholds

Use these cold email benchmarks to grade performance:

• Open rate: >50% = Strong, 30-50% = Average, <30% = Needs work
• Reply rate: >5% = Strong, 2-5% = Average, <2% = Needs work
• Bounce rate: <2% = Healthy, 2-5% = Warning, >5% = Problem
• Unsubscribe rate: <1% = Healthy, 1-3% = Warning, >3% = Problem

Analysis Strategy

1. List all campaigns and filter to active or recently completed ones
2. Pull top-level analytics for a quick performance snapshot
3. Use date range analytics to spot trends over weeks
4. For underperforming campaigns, get lead-level statistics to find patterns
5. Identify which sequence numbers (email 1, 2, 3) drive the most replies
6. Compare A/B variants if multiple exist

What to Flag

• Campaigns with reply rates below 2%
• High bounce rates indicating list quality issues
• Sequences where engagement drops sharply after email 1
• Campaigns with high opens but low replies (messaging problem)
• Campaigns where most leads are "stopped" or "blocked"

Output

Campaign Performance Overview: | Campaign | Status | Sent | Open Rate | Reply Rate | Bounce Rate | Grade | |----------|--------|------|-----------|------------|-------------|-------| | [Name] | Active | [N] | [X%] | [X%] | [X%] | A/B/C |

Top Performing Campaign: [Name] — [Why it's winning]

Underperforming Campaigns:

• [Name]: [Specific issue and recommendation]

Sequence Performance: | Campaign | Seq 1 Reply % | Seq 2 Reply % | Seq 3 Reply % | Best Performer | |----------|--------------|--------------|--------------|----------------| | [Name] | [X%] | [X%] | [X%] | Seq [N] |

Recommendations:

1. [Specific, actionable recommendation based on data]
2. [Specific, actionable recommendation based on data]
3. [Specific, actionable recommendation based on data]

Google Sheet Updated: [Link or confirmation that the report was exported]