performance-analysis

name	performance-analysis
description	Analyze outbound campaign performance across every meaningful metric. Diagnose what's working, what's broken, and exactly where to optimize for higher conversion.

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	< 3%	> 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%	< 85%	Domain/IP reputation. May need warmup or domain rotation.
Unsubscribe rate	< 0.5%	> 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 < 85%?
├── YES → Check domain reputation (Google Postmaster, MXToolbox)
│         → Reduce daily send volume
│         → Rotate sending domains
│         → Review email content for spam triggers
└── NO ↓

Spam complaints > 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%	< 40%	Subject line + deliverability + send timing
Open rate by step	Declining 5-10% per step	Drops > 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%	< 5%	Copy relevance + offer strength + list quality
Reply rate by step	Step 1: highest, declining	Step 1 < 3%	Opening email isn't earning replies
Reply timing	Most replies within 24h	Delayed replies (3+ days)	Email is interesting but not urgent
Auto-reply rate	Track separately	> 10%	Many OOO or bounced-to-assistant

Reply Rate Diagnostic

Reply rate < 5% overall?
├── Open 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%	< 1%	True message-market fit
Negative reply rate	< 3%	> 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 (< 1 hour)	"Sure, let's chat next week"
Positive: Interest	Interested but no commitment yet	Reply with value, ask for meeting	"Tell me more about this"
Positive: Referral	Directed you to someone else	Contact the referral, thank the original	"Talk to Sarah, she handles this"
Neutral: Not Now	Timing issue, not a rejection	Add to nurture, follow up in 30-60 days	"Not a priority right now"
Neutral: OOO	Out of office auto-reply	Re-send after they return	"I'm out until March 1"
Negative: Not Interested	Polite rejection	Respect it. Remove from sequence.	"Thanks, but we're all set"
Negative: Angry	Hostile response	Remove immediately. Review targeting.	"Stop emailing me"
Negative: Unsubscribe	Requests removal	Remove immediately. Legal requirement.	"Please remove me from your list"

The ratio that matters most:

Positive Reply Rate = (Positive replies ÷ Total emails sent) × 100

This single metric is the truest measure of campaign effectiveness. It strips out noise (opens, negative replies) and measures real demand generation.

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Layer 5: Conversion Metrics

Metric	Target	Red Flag	What It Tells You
Reply-to-meeting rate	40-60%	< 25%	Reply handling quality + qualification
Meeting show rate	80-90%	< 70%	Confirmation process + prospect quality
Meeting-to-opportunity rate	30-50%	< 20%	Discovery call quality + true fit
Cost per meeting	Varies by ACV	Rising over time	Campaign efficiency trending

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Layer 6: Revenue Metrics

Metric	Target	What It Tells You
Pipeline generated	Track per campaign	Total $ value of opportunities created
Revenue closed	Track per campaign	Actual revenue attributable to outbound
Cost per opportunity	Varies by ACV	Efficiency of the outbound motion
CAC (Customer Acquisition Cost)	< 1/3 of first-year ACV	Sustainability of the channel
Time to close	Track by campaign/segment	Which campaigns produce faster deals

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The Performance Analysis Report

Campaign Summary Card

CAMPAIGN: {{campaign_name}}
Period: {{start_date}} — {{end_date}}
Total sends: {{total_sends}}

DELIVERABILITY
  Bounce rate: __% (target: <3%)
  Spam complaints: __ (target: 0)

ENGAGEMENT
  Open rate: __% (target: 60-80%)

RESPONSE
  Total reply rate: __% (target: 8-15%)
  Positive reply rate: __% (target: 2-8%)
  Negative reply rate: __%

CONVERSION
  Meetings booked: __
  Reply-to-meeting rate: __%
  Cost per meeting: $__

REVENUE
  Pipeline generated: $__
  Revenue closed: $__
  ROI: __x

Variant Comparison Table

| Metric | Variant A | Variant B | Variant C | Winner |
|--------|-----------|-----------|-----------|--------|
| Sends | __ | __ | __ | — |
| Open rate | __% | __% | __% | __ |
| Reply rate | __% | __% | __% | __ |
| Positive reply rate | __% | __% | __% | __ |
| Meetings | __ | __ | __ | __ |

Step Performance Breakdown

| Step | Sends | Opens | Open Rate | Replies | Reply Rate | Positive | Positive Rate |
|------|-------|-------|-----------|---------|------------|----------|---------------|
| 1 | __ | __ | __% | __ | __% | __ | __% |
| 2 | __ | __ | __% | __ | __% | __ | __% |
| 3 | __ | __ | __% | __ | __% | __ | __% |
| 4 | __ | __ | __% | __ | __% | __ | __% |

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Decision Framework: Scale, Optimize, or Kill

Scenario	Diagnosis	Action
Positive reply rate > 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.