plugin: instantly updated: 2026-01-20

Campaign Metrics

Name: campaign-metrics
Rating: 92
Author: MadAppGang

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

code

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)

code

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

Component Calculations:

code

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