Performance Analysis

Campaign Performance Analysis

When to Use

• Reviewing campaign results after a send cycle completes
• Diagnosing why a campaign is underperforming
• Comparing campaign variants to identify winners
• Building performance reports for clients or leadership
• Making data-driven decisions about what to scale, pause, or kill

Framework

The Campaign Metrics Stack

Measure campaigns in layers. Each layer tells you something different about what's working and what isn't.

Layer 1: Deliverability     → Did the email reach the inbox?
Layer 2: Engagement         → Did they open and read it?
Layer 3: Response           → Did they reply?
Layer 4: Quality            → Was the reply positive?
Layer 5: Conversion         → Did the reply turn into a meeting?
Layer 6: Revenue            → Did the meeting turn into revenue?

Critical insight: Most teams obsess over Layer 2-3 (opens and replies) while ignoring Layer 1 (deliverability) and Layer 4-6 (quality and revenue). The full stack matters.

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Layer 1: Deliverability Metrics

| Metric | Target | Red Flag | What It Tells You | |--------|--------|----------|-------------------| | Bounce rate | 5% | List quality. High bounces = bad data or unverified emails. | | Spam complaint rate | 0% | > 0.1% | Content or targeting issue. Immediate pause needed. | | Inbox placement rate | > 95% | 1% | Targeting accuracy. Wrong people or too many touches. |

If deliverability metrics are off, STOP. Do not optimize copy, subject lines, or targeting until deliverability is fixed. You're optimizing something that never reaches the prospect.

Deliverability Diagnostic

Bounce rate > 5%?
├── YES → Verify email list. Switch to verified-only sends.
└── NO ↓

Inbox placement  0?
├── YES → Review targeting. Are you emailing the right people?
│         → Check for spam trigger words in subject/body
│         → Ensure unsubscribe link is visible
└── NO → Deliverability is healthy. Move to Layer 2.

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Layer 2: Engagement Metrics

| Metric | Target | Red Flag | What It Tells You | |--------|--------|----------|-------------------| | Open rate | 60-80% | 20% per step | Sequence fatigue or deliverability degradation | | Unique opens | Track vs. total opens | Low unique/high total | Same people reopening, not new engagement |

Note on open tracking: Open tracking uses invisible pixels that can hurt deliverability. If you're tracking opens, use it for diagnostic purposes but consider turning it off for production campaigns. Low open rate with high reply rate = your emails are landing but the pixel isn't loading (common with Outlook).

Subject Line Analysis

| Subject Line | Open Rate | Sample Size | Verdict | |-------------|-----------|-------------|---------| | Variant A | __% | __ sends | Winner / Loser / Inconclusive | | Variant B | __% | __ sends | Winner / Loser / Inconclusive | | Variant C | __% | __ sends | Winner / Loser / Inconclusive |

Minimum sample size: 200 sends per variant before drawing conclusions. Below 200, the variance is too high to trust.

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Layer 3: Response Metrics

| Metric | Target | Red Flag | What It Tells You | |--------|--------|----------|-------------------| | Total reply rate | 8-15% | 10% | Many OOO or bounced-to-assistant |

Reply Rate Diagnostic

Reply rate  60%?
│   ├── YES → Copy problem. Emails are being read but not compelling.
│   │         → Test new body copy variants
│   │         → Test new CTAs
│   │         → Review personalization quality
│   └── NO  → Subject line or deliverability problem.
│             → Fix opens first, then reassess replies.
│
Reply rate > 5% but meetings are low?
├── Most replies are negative ("not interested", "remove me")?
│   ├── YES → Targeting problem. You're reaching the wrong people.
│   │         → Review ICP and list quality
│   └── NO  → Qualification problem. Interested leads aren't converting.
│             → Review your meeting booking process
│             → Improve reply handling speed

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Layer 4: Quality Metrics (Most Important)

| Metric | Target | Red Flag | What It Tells You | |--------|--------|----------|-------------------| | Positive reply rate | 2-8% | 5% | Targeting accuracy | | Referral replies | Track separately | — | Valuable — contact the referral | | "Not now" replies | Track separately | — | Future pipeline. Add to nurture. |

Reply Classification Framework

Every reply should be classified:

| Category | Definition | Action | Example | |----------|-----------|--------|---------| | Positive: Meeting | Agreed to a call/meeting | Book immediately ( 5% | Campaign is working | Scale: increase volume, clone for new segments | | Positive reply rate 2-5% | Campaign has potential | Optimize: test new variants, improve personalization | | Positive reply rate 1-2% | Campaign is marginal | Diagnose: is it copy, targeting, or timing? Fix one variable | | Positive reply rate < 1% | Campaign isn't working | Kill: stop sending. Redesign from scratch or abandon the angle |

Templates

Weekly Campaign Report Template

# Weekly Campaign Report
# Period: {{week}}

## Summary
- Active campaigns: __
- Total sends this week: __
- Avg positive reply rate: __%
- Meetings booked: __

## Top Performing Campaign
{{campaign_name}} — {{positive_reply_rate}}% positive reply rate

## Underperforming (Action Needed)
{{campaign_name}} — {{issue}} → {{recommended_action}}

## Key Decisions
- Scale: {{campaign_to_scale}}
- Optimize: {{campaign_to_optimize}}
- Kill: {{campaign_to_kill}}

## Next Week Plan
- {{action_1}}
- {{action_2}}

Tips

• Positive reply rate is the only metric that matters for campaign-level decisions. Everything else (opens, total replies) is diagnostic — useful for understanding WHY, but not for deciding WHAT to do.
• Always compare apples to apples. A campaign targeting VPs at enterprise companies will have different benchmarks than one targeting founders at SMBs. Segment your analysis.
• The most common analysis mistake: drawing conclusions from too-small samples. 50 sends with a 10% reply rate is not a winning campaign — it's noise. Wait for 200+ sends per variant.
• Track metrics over time, not just snapshots. A campaign with a 5% reply rate in week 1 and 2% in week 4 is degrading — the list might be exhausted or deliverability is dropping.
• Don't average across campaigns. One campaign with a 15% positive reply rate and one with 0.5% averages to 7.75% — but that hides the fact that one is amazing and one is terrible.

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Progressive disclosure: load platform-specific analytics integrations and automated reporting configs only when analyzing data from a specific sending platform.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: kenny589
• Source: kenny589/gtm-flywheel
• License: MIT

Install and usage instructions live in the source repository linked above.