home / skills / madappgang / claude-code / campaign-metrics

This skill helps you optimize cold email campaigns by analyzing KPIs, benchmarks, and diagnostic patterns to improve engagement and deliverability.

npx playbooks add skill madappgang/claude-code --skill campaign-metrics

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md
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---
name: campaign-metrics
version: 1.0.0
description: Cold email campaign KPIs, benchmarks, and diagnostic patterns
---
plugin: instantly
updated: 2026-01-20

# Campaign Metrics

## Core KPIs

### Primary Metrics

| Metric | Formula | Benchmark (Cold Email) |
|--------|---------|------------------------|
| Open Rate | (Opened / Sent) * 100 | 40-50% (good), 25-40% (average) |
| Reply Rate | (Replied / Sent) * 100 | 5-10% (good), 2-5% (average) |
| Positive Reply Rate | (Positive / Replied) * 100 | 25-40% (good) |
| Bounce Rate | (Bounced / Sent) * 100 | <2% (healthy) |
| Unsubscribe Rate | (Unsubscribed / Sent) * 100 | <0.5% (healthy) |

### Secondary Metrics

| Metric | Formula | Use Case |
|--------|---------|----------|
| Emails per Lead | Total Sent / Unique Leads | Sequence effectiveness |
| Reply by Step | Replies per step / Sent per step | Identify best-performing emails |
| Time to Reply | Avg time between send and reply | Timing optimization |

## Benchmark Reference

### Industry Benchmarks by Vertical

| Vertical | Open Rate | Reply Rate | Notes |
|----------|-----------|------------|-------|
| SaaS | 45-55% | 5-12% | Higher engagement |
| Agency | 35-45% | 3-7% | Competitive space |
| E-commerce | 30-40% | 2-5% | Volume-focused |
| Financial Services | 25-35% | 2-4% | Compliance-heavy |

### Performance Tiers

```
EXCELLENT (Top 10%)
  Open Rate: >50%
  Reply Rate: >10%
  Bounce Rate: <1%

GOOD (Top 25%)
  Open Rate: 40-50%
  Reply Rate: 5-10%
  Bounce Rate: 1-2%

AVERAGE (Middle 50%)
  Open Rate: 25-40%
  Reply Rate: 2-5%
  Bounce Rate: 2-5%

POOR (Bottom 25%)
  Open Rate: 15-25%
  Reply Rate: 1-2%
  Bounce Rate: 5-10%

CRITICAL (Bottom 10%)
  Open Rate: <15%
  Reply Rate: <1%
  Bounce Rate: >10%
```

## Diagnostic Patterns

### Pattern Matrix

| Open Rate | Reply Rate | Diagnosis | Action |
|-----------|------------|-----------|--------|
| Low (<25%) | Any | Subject line issue | A/B test subjects |
| High (>40%) | Low (<2%) | Body copy issue | Rewrite email body |
| High | High | Winning combo | Scale and replicate |
| Declining | Stable | Fatigue setting in | Refresh creative |
| Any | Any + High Bounce | List quality issue | Verify emails |

### Time-Based Analysis

| Pattern | Meaning | Action |
|---------|---------|--------|
| Monday spike | Inbox cleared over weekend | Send Sun night or Mon early |
| Friday drop | Weekend mindset | Avoid Fri afternoon sends |
| Steady decline | Audience exhaustion | Rotate lists or refresh copy |
| Random spikes | External event correlation | Analyze and replicate |

## Score Calculation

### Campaign Health Score (0-100)

```
health_score = (
    open_score * 0.25 +
    reply_score * 0.35 +
    deliverability_score * 0.25 +
    trend_score * 0.15
)
```

**Component Calculations:**

```
open_score = normalize(open_rate, min=0, max=60)
  60%+ open = 100 points
  40% open = 67 points
  20% open = 33 points
  0% open = 0 points

reply_score = normalize(reply_rate, min=0, max=15)
  15%+ reply = 100 points
  10% reply = 67 points
  5% reply = 33 points
  0% reply = 0 points

deliverability_score = 100 - (bounce_rate * 10)
  0% bounce = 100 points
  5% bounce = 50 points
  10% bounce = 0 points

trend_score = based on week-over-week change
  +10% improvement = 100 points
  Stable = 50 points
  -10% decline = 0 points
```

### Score Interpretation

| Score | Rating | Action Required |
|-------|--------|-----------------|
| 90-100 | Excellent | Maintain, scale if possible |
| 75-89 | Good | Minor optimizations |
| 60-74 | Average | Address weak areas |
| 40-59 | Poor | Major revision needed |
| 0-39 | Critical | Pause and fix immediately |

Overview

This skill provides cold email campaign KPIs, benchmarks, and diagnostic patterns to evaluate and optimize deliverability and engagement. It translates raw sends into actionable insights, a campaign health score, and clear remediation steps. Use it to prioritize fixes and scale winning sequences.

How this skill works

The skill calculates primary metrics (open, reply, positive reply, bounce, unsubscribe) and secondary metrics (emails per lead, reply by step, time to reply). It compares results to industry and performance-tier benchmarks, runs diagnostic pattern checks, and produces a campaign health score based on weighted components (open, reply, deliverability, trend). It outputs targeted actions when performance deviates from expected ranges.

When to use it

  • Diagnosing a cold email sequence after the first few hundred sends
  • Prioritizing fixes when open or reply rates are below benchmarks
  • Validating list quality when bounce or unsubscribe rates spike
  • Deciding whether to scale a high-performing sequence
  • Optimizing send times and cadence based on temporal patterns

Best practices

  • Track both primary and secondary metrics to understand sequence-level performance
  • A/B test subject lines when open rates are low and body copy when replies lag
  • Keep bounce <2% and unsubscribe <0.5% to protect deliverability
  • Monitor week-over-week trends; treat steady declines as list or creative fatigue
  • Segment by vertical (SaaS, agency, e-commerce, financial) and compare against relevant benchmarks

Example use cases

  • A SaaS campaign with 48% open but 1.2% reply: rewrite body copy and CTA, then retest
  • An agency list with rising bounce from 1% to 4%: pause outreach, verify emails, and re-import clean contacts
  • Early-stage cold test: analyze reply-by-step to identify which sequence email drives most responses
  • Weekly scheduling optimization: move sends to Sunday night or Monday early when a Monday spike appears
  • Campaign scaling decision: replicate sequences classified as 'Excellent' or 'Good' by the health score

FAQ

What benchmarks should I use for reply rate?

Use 5-10% as a good benchmark for cold email; 2-5% is average. Adjust expectations by vertical: SaaS tends to be higher, financial services lower.

When should I pause a campaign?

Pause immediately if bounce rate exceeds ~10% or if the campaign health score falls into the Critical tier (0-39) while deliverability issues persist.