Sequence Performance
Goes beyond vanity metrics. Most campaign reports tell you open rate and reply rate. This skill reads the actual emails you sent, reads every reply you received, classifies the responses, evaluates your copy, evaluates your lead quality, and tells you specifically what's working, what's not, and what to do about it.
Three layers of analysis:
- Quantitative: The numbers — sends, opens, replies, bounces, conversions, by touch and by variant
- Qualitative (Copy): Are the subject lines, email bodies, CTAs, and personalization actually good?
- Qualitative (Replies): What are people actually saying? What objections keep coming up?
When to Use
Use this skill when:
- User says "how's my campaign doing", "sequence performance", "campaign review", "email analytics"
- User says "analyze my outreach", "why isn't my campaign working", "review my email results"
- A campaign has been running for 7+ days and has meaningful data
Phase 0: Intake
Outreach Tool
- What outreach tool do you use? (Smartlead / Instantly / Outreach.io / Lemlist / Apollo / Other)
- How do we access campaign data? (MCP tools / API / CSV export / paste metrics)
Campaign Selection
- Which campaign? (name or ID)
- Date range? (or "all data")
Your Company Context (for copy evaluation)
- What does your company do? (one-liner)
- Who is your ICP? (titles, industries, company size)
- What problem do you solve?
- What's your CTA goal? (book meeting, get reply, drive to page)
Benchmark Context
- Is this cold outreach or warm/nurture?
- What segment are you selling to? (SMB, mid-market, enterprise)
Step 1: Pull Campaign Data
Pull three categories of data from the user's outreach tool:
A) Campaign Metrics
| Data Point |
What We Need |
| Total emails sent |
By touch (Touch 1, Touch 2, Touch 3, etc.) |
| Total unique recipients |
Deduplicated count |
| Opens |
By touch, unique opens vs. total opens |
| Replies |
By touch, total reply count |
| Bounces |
Hard bounces + soft bounces |
| Unsubscribes |
Count |
| Clicks |
If link tracking is on |
| Positive replies |
If categorized in the tool |
| Meetings booked |
If tracked |
How to pull by tool:
| Tool |
Method |
| Smartlead (MCP) |
mcp__smartlead__get_campaign_stats, mcp__smartlead__get_campaign_sequence_analytics, mcp__smartlead__get_campaign_variant_statistics |
| Instantly / Outreach / Lemlist / Apollo |
Ask user for CSV export or paste metrics |
| Other |
User provides CSV with columns: email, status, opened, replied, bounced |
B) Email Copy (Sequence Content)
Pull the actual templates for every touch:
| Tool |
Method |
| Smartlead (MCP) |
mcp__smartlead__get_campaign_sequences |
| Others |
User pastes the copy or provides CSV export |
C) Reply Content
Pull the actual text of every reply:
| Tool |
Method |
| Smartlead (MCP) |
mcp__smartlead__get_campaign_leads_history, mcp__smartlead__fetch_master_inbox_replies |
| Others |
User provides reply dump or CSV export |
Human Checkpoint
Campaign: [name]
Status: [active/paused/completed]
Sent: X emails to Y recipients
Replies: Z (full text pulled for analysis)
Touches: N touches, M variants
Data looks complete? (Y/n)
Step 2: Quantitative Analysis
Benchmarks
| Metric |
Cold (SMB) |
Cold (Mid-Market) |
Cold (Enterprise) |
Warm/Nurture |
| Open rate |
40-60% |
30-50% |
25-40% |
50-70% |
| Reply rate |
3-8% |
2-5% |
1-3% |
10-20% |
| Positive reply rate |
1-3% |
0.5-2% |
0.3-1% |
5-10% |
| Bounce rate |
<3% |
<3% |
<2% |
<1% |
| Unsubscribe rate |
<1% |
<1% |
<0.5% |
<0.5% |
Calculate
Overall metrics: open rate, reply rate, positive reply rate, bounce rate, unsubscribe rate, deliverability rate. Compare each to the benchmark.
Per-touch breakdown:
- Touch-level open/reply rates
- Marginal reply rate (replies from THIS touch / people who received this touch but hadn't replied yet)
- Touch contribution (what % of total replies came from each touch)
Variant analysis (if A/B testing):
- Open rate and reply rate per variant
- Statistical confidence: <50 sends = "insufficient data", 50-100 = "directional", 100-250 = "likely winner", 250+ = "statistically significant"
- Winner recommendation: scale, keep testing, or kill
Step 3: Reply Analysis
Read every reply, classify it, and extract patterns.
Reply Categories
| Category |
Definition |
| Positive interest |
Wants to learn more, open to a conversation |
| Meeting request |
Explicitly asks to meet or provides availability |
| Warm / Curious |
Interested but non-committal, asks questions |
| Objection — Timing |
Not now, but potentially later |
| Objection — Budget |
Can't afford or not a priority |
| Objection — Competitor |
Already using a competing solution |
| Objection — Relevance |
Doesn't see the fit |
| Objection — Authority |
Not the right person |
| Not interested |
Flat no |
| Auto-reply / OOO |
Automated response |
| Referral |
Redirects to someone else |
| Question |
Asks about product/offering |
Objection Patterns
- Which objection appears most? (reveals systemic issues)
- Do objections cluster at Touch 1 (bad targeting) vs. Touch 3 (fatigue)?
- Which are handleable (timing, authority) vs. terminal (relevance)?
- What exact language do people use?
Positive Signal Patterns
- Which touch/variant generated positive replies?
- What do positive responders have in common? (title, industry, company size)
- What questions do warm leads ask? (reveals what's missing from the email)
Reply Quality Score
| Score |
Criteria |
| Strong |
>50% positive/warm. Objections are handleable. |
| Mixed |
30-50% positive. Mix of handleable and terminal. |
| Weak |
<30% positive. Dominated by "not interested" and "not relevant." |
| Toxic |
High unsubscribe + angry replies. Something is fundamentally wrong. |
Step 4: Copy Quality Assessment
Evaluate the actual email copy against best practices and reply data.
Subject Lines
| Criterion |
Red Flags |
| Length |
>60 chars gets truncated on mobile |
| Specificity |
Generic "Quick question" or "Checking in" |
| Spam triggers |
"Free", "Limited time", ALL CAPS |
| Open rate correlation |
Low open rate = subject line problem |
Email Body
| Criterion |
Red Flags |
| Hook (first line) |
"I'm reaching out because..." or "We are a company that..." |
| Length |
Over 150 words |
| Value prop clarity |
Jargon, vague language, buzzwords |
| Proof points |
No proof = no credibility |
| Personalization |
Only {first_name} merge field |
| CTA |
Multiple CTAs, high-friction asks, or no CTA |
| Filler language |
"Hope this finds you well", "just checking in" |
| Sequence progression |
Touch 2 is just a "bump" of Touch 1 |
Grades
Grade each touch A through F on: hook quality, value prop clarity, proof usage, personalization level, CTA quality.
Step 5: Lead Quality Assessment
Evaluate whether we're sending to the right people.
Targeting Check
- Do lead titles match ICP buyer/champion/user personas?
- Are leads in target industries?
- Right seniority level for the ask?
- Company size in target range?
Signal Quality (from replies)
| Pattern |
What It Tells You |
| High "not relevant" replies |
Sending to people who don't have the problem |
| High "wrong person" replies |
Right companies, wrong roles |
| High "already have a solution" |
Right problem, late to the party |
| High "timing" objections |
Right people, right problem, wrong moment — not a targeting issue |
| Low reply + high open rate |
People open but don't find it relevant — copy/targeting mismatch |
| High bounce rate |
List quality issue — bad emails, old data |
Step 6: Generate Report
Report Structure
# Sequence Performance Review: [Campaign Name]
**Period:** [date range] | **Status:** [active/paused/completed]
---
## Executive Summary
**Overall verdict:** [One sentence]
| Dimension | Grade | Assessment |
|-----------|-------|-----------|
| Metrics | [A-F] | [one-liner] |
| Copy Quality | [A-F] | [one-liner] |
| Lead Quality | [A-F] | [one-liner] |
| Reply Quality | [Strong/Mixed/Weak/Toxic] | [one-liner] |
### What's Working (Double Down)
- [Specific thing with data]
### What's Not Working (Fix or Kill)
- [Specific thing with data]
### Top 3 Actions
1. [Highest-impact action]
2. [Second]
3. [Third]
---
## Detailed Metrics
### Overall Performance
| Metric | Actual | Benchmark | Status |
|--------|--------|-----------|--------|
| Open rate | X% | Y% | [above/below] |
| Reply rate | X% | Y% | [above/below] |
| Bounce rate | X% | <3% | [flag] |
| ... | ... | ... | ... |
### Performance by Touch
| Touch | Sent | Open Rate | Reply Rate | Marginal Reply Rate | % of Total Replies |
|-------|------|-----------|------------|--------------------|--------------------|
| 1 | X | Y% | Z% | Z% | W% |
### Variant Performance (if A/B testing)
| Touch | Variant | Subject | Sent | Open Rate | Reply Rate | Confidence | Action |
|-------|---------|---------|------|-----------|------------|------------|--------|
---
## Reply Deep Dive
### Reply Classification
| Category | Count | % of Replies |
|----------|-------|-------------|
### Top Objections
| Objection | Count | Handleable? | Suggested Response |
|-----------|-------|------------|-------------------|
### Notable Replies
[5-10 most instructive replies with quotes]
---
## Copy Assessment
[Subject line verdicts, body grades, sequence architecture assessment]
---
## Lead Quality
[Targeting assessment, actual vs intended ICP]
---
## Recommendations (Prioritized)
### High Priority (Do This Week)
1. **[Action]** — [data point] → [expected impact]
### Medium Priority (Do This Month)
2. **[Action]** — [data point] → [expected impact]
### Kill List
- [Anything that should be stopped]
Recommendation Logic
| Finding |
Recommendation |
| Open rate below benchmark |
Subject line rewrite — suggest 3 alternatives |
| Reply rate below + open rate fine |
Body copy issue — focus on hook, proof, CTA |
| Both below benchmark |
Full sequence rewrite |
| High "not relevant" objections |
Targeting issue — tighten ICP filters |
| High "wrong person" referrals |
Title targeting issue — shift to referred titles |
| High "already have solution" |
Add competitive differentiation to copy |
| High "timing" objections |
Not a problem — set up 90-day re-engagement |
| One variant clearly winning |
Scale winner, test new idea in losing slot |
| Touch 2/3 near-zero marginal replies |
Cut sequence short or rewrite with new angles |
| High bounce rate |
List hygiene — verify emails, check data source |
| Deliverability <95% |
Infrastructure — check SPF/DKIM/DMARC, reduce volume |
Human Checkpoint
Present the executive summary, then ask:
Full detailed report available. Want to see the full breakdown, or act on a specific recommendation?
Adapting to Data Availability
| Missing Data |
What Gets Skipped |
Still Useful? |
| Reply text |
Reply classification + objection patterns |
Partially — metrics + copy still run |
| Variant data |
Variant analysis |
Yes — single-variant analysis still runs |
| Lead demographics |
Targeting assessment |
Yes — infers from reply patterns |
| Open tracking |
Open rate analysis |
Partially — reply rate + copy still run |
Minimum viable data: Emails sent + reply count + email copy text.
Cost
Free. Pure reasoning + data from user's outreach tool.
Tips
- Run at Day 7 and Day 14. Day 7 catches deliverability and subject line problems. Day 14 gives enough replies for objection analysis.
- Reply analysis is where the gold is. Metrics tell you WHAT. Replies tell you WHY.
- High open + low reply = copy problem. The subject gets them to open but the email doesn't deliver.
- Low open + decent reply rate = subject line problem. The email works, people just aren't seeing it.
- "Not relevant" is the most important objection. If >20% say "this isn't for me," it's targeting, not copy.
- Don't kill a variant too early. Need 100+ sends per variant for directional data.
- Touch 2/3 should contribute 30-40% of replies. If Touch 1 is 90%+, your follow-ups aren't adding value.
1---2name: sequence-performance3description: Email campaign/sequence performance review composite. Pulls campaign data (sends, opens, replies, bounces), reads actual email copy and subject lines, analyzes reply content (objections, positive interest, questions), and produces a diagnostic report covering quantitative metrics, copy quality, lead quality, and actionable recommendations. Tool-agnostic — works with Smartlead (MCP), Instantly, Outreach, Lemlist, Apollo, or CSV data.4---5
6# Sequence Performance
7
8Goes beyond vanity metrics. Most campaign reports tell you open rate and reply rate. This skill reads the actual emails you sent, reads every reply you received, classifies the responses, evaluates your copy, evaluates your lead quality, and tells you specifically what's working, what's not, and what to do about it.
9
10**Three layers of analysis:**
111. **Quantitative:** The numbers — sends, opens, replies, bounces, conversions, by touch and by variant
122. **Qualitative (Copy):** Are the subject lines, email bodies, CTAs, and personalization actually good?
133. **Qualitative (Replies):** What are people actually saying? What objections keep coming up?
14
15## When to Use
16
17Use this skill when:
18- User says "how's my campaign doing", "sequence performance", "campaign review", "email analytics"
19- User says "analyze my outreach", "why isn't my campaign working", "review my email results"
20- A campaign has been running for 7+ days and has meaningful data
21
22## Phase 0: Intake
23
24### Outreach Tool
251. What outreach tool do you use? (Smartlead / Instantly / Outreach.io / Lemlist / Apollo / Other)
262. How do we access campaign data? (MCP tools / API / CSV export / paste metrics)
27
28### Campaign Selection
293. Which campaign? (name or ID)
304. Date range? (or "all data")
31
32### Your Company Context (for copy evaluation)
335. What does your company do? (one-liner)
346. Who is your ICP? (titles, industries, company size)
357. What problem do you solve?
368. What's your CTA goal? (book meeting, get reply, drive to page)
37
38### Benchmark Context
399. Is this cold outreach or warm/nurture?
4010. What segment are you selling to? (SMB, mid-market, enterprise)
41
42## Step 1: Pull Campaign Data
43
44Pull three categories of data from the user's outreach tool:
45
46### A) Campaign Metrics
47
48| Data Point | What We Need |
49|-----------|-------------|
50| Total emails sent | By touch (Touch 1, Touch 2, Touch 3, etc.) |
51| Total unique recipients | Deduplicated count |
52| Opens | By touch, unique opens vs. total opens |
53| Replies | By touch, total reply count |
54| Bounces | Hard bounces + soft bounces |
55| Unsubscribes | Count |
56| Clicks | If link tracking is on |
57| Positive replies | If categorized in the tool |
58| Meetings booked | If tracked |
59
60**How to pull by tool:**
61
62| Tool | Method |
63|------|--------|
64| **Smartlead** (MCP) | `mcp__smartlead__get_campaign_stats`, `mcp__smartlead__get_campaign_sequence_analytics`, `mcp__smartlead__get_campaign_variant_statistics` |
65| **Instantly / Outreach / Lemlist / Apollo** | Ask user for CSV export or paste metrics |
66| **Other** | User provides CSV with columns: email, status, opened, replied, bounced |
67
68### B) Email Copy (Sequence Content)
69
70Pull the actual templates for every touch:
71
72| Tool | Method |
73|------|--------|
74| **Smartlead** (MCP) | `mcp__smartlead__get_campaign_sequences` |
75| **Others** | User pastes the copy or provides CSV export |
76
77### C) Reply Content
78
79Pull the actual text of every reply:
80
81| Tool | Method |
82|------|--------|
83| **Smartlead** (MCP) | `mcp__smartlead__get_campaign_leads_history`, `mcp__smartlead__fetch_master_inbox_replies` |
84| **Others** | User provides reply dump or CSV export |
85
86### Human Checkpoint
87
88```
89Campaign: [name]
90Status: [active/paused/completed]
91Sent: X emails to Y recipients
92Replies: Z (full text pulled for analysis)
93Touches: N touches, M variants
94
95Data looks complete? (Y/n)
96```
97
98## Step 2: Quantitative Analysis
99
100### Benchmarks
101
102| Metric | Cold (SMB) | Cold (Mid-Market) | Cold (Enterprise) | Warm/Nurture |
103|--------|-----------|-------------------|-------------------|-------------|
104| Open rate | 40-60% | 30-50% | 25-40% | 50-70% |
105| Reply rate | 3-8% | 2-5% | 1-3% | 10-20% |
106| Positive reply rate | 1-3% | 0.5-2% | 0.3-1% | 5-10% |
107| Bounce rate | <3% | <3% | <2% | <1% |
108| Unsubscribe rate | <1% | <1% | <0.5% | <0.5% |
109
110### Calculate
111
112**Overall metrics:** open rate, reply rate, positive reply rate, bounce rate, unsubscribe rate, deliverability rate. Compare each to the benchmark.
113
114**Per-touch breakdown:**
115- Touch-level open/reply rates
116- Marginal reply rate (replies from THIS touch / people who received this touch but hadn't replied yet)
117- Touch contribution (what % of total replies came from each touch)
118
119**Variant analysis (if A/B testing):**
120- Open rate and reply rate per variant
121- Statistical confidence: <50 sends = "insufficient data", 50-100 = "directional", 100-250 = "likely winner", 250+ = "statistically significant"
122- Winner recommendation: scale, keep testing, or kill
123
124## Step 3: Reply Analysis
125
126Read every reply, classify it, and extract patterns.
127
128### Reply Categories
129
130| Category | Definition |
131|----------|-----------|
132| **Positive interest** | Wants to learn more, open to a conversation |
133| **Meeting request** | Explicitly asks to meet or provides availability |
134| **Warm / Curious** | Interested but non-committal, asks questions |
135| **Objection — Timing** | Not now, but potentially later |
136| **Objection — Budget** | Can't afford or not a priority |
137| **Objection — Competitor** | Already using a competing solution |
138| **Objection — Relevance** | Doesn't see the fit |
139| **Objection — Authority** | Not the right person |
140| **Not interested** | Flat no |
141| **Auto-reply / OOO** | Automated response |
142| **Referral** | Redirects to someone else |
143| **Question** | Asks about product/offering |
144
145### Objection Patterns
146
147- Which objection appears most? (reveals systemic issues)
148- Do objections cluster at Touch 1 (bad targeting) vs. Touch 3 (fatigue)?
149- Which are handleable (timing, authority) vs. terminal (relevance)?
150- What exact language do people use?
151
152### Positive Signal Patterns
153
154- Which touch/variant generated positive replies?
155- What do positive responders have in common? (title, industry, company size)
156- What questions do warm leads ask? (reveals what's missing from the email)
157
158### Reply Quality Score
159
160| Score | Criteria |
161|-------|---------|
162| **Strong** | >50% positive/warm. Objections are handleable. |
163| **Mixed** | 30-50% positive. Mix of handleable and terminal. |
164| **Weak** | <30% positive. Dominated by "not interested" and "not relevant." |
165| **Toxic** | High unsubscribe + angry replies. Something is fundamentally wrong. |
166
167## Step 4: Copy Quality Assessment
168
169Evaluate the actual email copy against best practices and reply data.
170
171### Subject Lines
172
173| Criterion | Red Flags |
174|-----------|-----------|
175| Length | >60 chars gets truncated on mobile |
176| Specificity | Generic "Quick question" or "Checking in" |
177| Spam triggers | "Free", "Limited time", ALL CAPS |
178| Open rate correlation | Low open rate = subject line problem |
179
180### Email Body
181
182| Criterion | Red Flags |
183|-----------|-----------|
184| Hook (first line) | "I'm reaching out because..." or "We are a company that..." |
185| Length | Over 150 words |
186| Value prop clarity | Jargon, vague language, buzzwords |
187| Proof points | No proof = no credibility |
188| Personalization | Only `{first_name}` merge field |
189| CTA | Multiple CTAs, high-friction asks, or no CTA |
190| Filler language | "Hope this finds you well", "just checking in" |
191| Sequence progression | Touch 2 is just a "bump" of Touch 1 |
192
193### Grades
194
195Grade each touch A through F on: hook quality, value prop clarity, proof usage, personalization level, CTA quality.
196
197## Step 5: Lead Quality Assessment
198
199Evaluate whether we're sending to the right people.
200
201### Targeting Check
202
203- Do lead titles match ICP buyer/champion/user personas?
204- Are leads in target industries?
205- Right seniority level for the ask?
206- Company size in target range?
207
208### Signal Quality (from replies)
209
210| Pattern | What It Tells You |
211|---------|------------------|
212| High "not relevant" replies | Sending to people who don't have the problem |
213| High "wrong person" replies | Right companies, wrong roles |
214| High "already have a solution" | Right problem, late to the party |
215| High "timing" objections | Right people, right problem, wrong moment — not a targeting issue |
216| Low reply + high open rate | People open but don't find it relevant — copy/targeting mismatch |
217| High bounce rate | List quality issue — bad emails, old data |
218
219## Step 6: Generate Report
220
221### Report Structure
222
223```
224# Sequence Performance Review: [Campaign Name]
225**Period:** [date range] | **Status:** [active/paused/completed]
226
227---
228
229## Executive Summary
230
231**Overall verdict:** [One sentence]
232
233| Dimension | Grade | Assessment |
234|-----------|-------|-----------|
235| Metrics | [A-F] | [one-liner] |
236| Copy Quality | [A-F] | [one-liner] |
237| Lead Quality | [A-F] | [one-liner] |
238| Reply Quality | [Strong/Mixed/Weak/Toxic] | [one-liner] |
239
240### What's Working (Double Down)
241- [Specific thing with data]
242
243### What's Not Working (Fix or Kill)
244- [Specific thing with data]
245
246### Top 3 Actions
2471. [Highest-impact action]
2482. [Second]
2493. [Third]
250
251---
252
253## Detailed Metrics
254
255### Overall Performance
256| Metric | Actual | Benchmark | Status |
257|--------|--------|-----------|--------|
258| Open rate | X% | Y% | [above/below] |
259| Reply rate | X% | Y% | [above/below] |
260| Bounce rate | X% | <3% | [flag] |
261| ... | ... | ... | ... |
262
263### Performance by Touch
264| Touch | Sent | Open Rate | Reply Rate | Marginal Reply Rate | % of Total Replies |
265|-------|------|-----------|------------|--------------------|--------------------|
266| 1 | X | Y% | Z% | Z% | W% |
267
268### Variant Performance (if A/B testing)
269| Touch | Variant | Subject | Sent | Open Rate | Reply Rate | Confidence | Action |
270|-------|---------|---------|------|-----------|------------|------------|--------|
271
272---
273
274## Reply Deep Dive
275
276### Reply Classification
277| Category | Count | % of Replies |
278|----------|-------|-------------|
279
280### Top Objections
281| Objection | Count | Handleable? | Suggested Response |
282|-----------|-------|------------|-------------------|
283
284### Notable Replies
285[5-10 most instructive replies with quotes]
286
287---
288
289## Copy Assessment
290[Subject line verdicts, body grades, sequence architecture assessment]
291
292---
293
294## Lead Quality
295[Targeting assessment, actual vs intended ICP]
296
297---
298
299## Recommendations (Prioritized)
300
301### High Priority (Do This Week)
3021. **[Action]** — [data point] → [expected impact]
303
304### Medium Priority (Do This Month)
3052. **[Action]** — [data point] → [expected impact]
306
307### Kill List
308- [Anything that should be stopped]
309```
310
311### Recommendation Logic
312
313| Finding | Recommendation |
314|---------|---------------|
315| Open rate below benchmark | Subject line rewrite — suggest 3 alternatives |
316| Reply rate below + open rate fine | Body copy issue — focus on hook, proof, CTA |
317| Both below benchmark | Full sequence rewrite |
318| High "not relevant" objections | Targeting issue — tighten ICP filters |
319| High "wrong person" referrals | Title targeting issue — shift to referred titles |
320| High "already have solution" | Add competitive differentiation to copy |
321| High "timing" objections | Not a problem — set up 90-day re-engagement |
322| One variant clearly winning | Scale winner, test new idea in losing slot |
323| Touch 2/3 near-zero marginal replies | Cut sequence short or rewrite with new angles |
324| High bounce rate | List hygiene — verify emails, check data source |
325| Deliverability <95% | Infrastructure — check SPF/DKIM/DMARC, reduce volume |
326
327### Human Checkpoint
328
329Present the executive summary, then ask:
330
331```
332Full detailed report available. Want to see the full breakdown, or act on a specific recommendation?
333```
334
335## Adapting to Data Availability
336
337| Missing Data | What Gets Skipped | Still Useful? |
338|-------------|-------------------|--------------|
339| Reply text | Reply classification + objection patterns | Partially — metrics + copy still run |
340| Variant data | Variant analysis | Yes — single-variant analysis still runs |
341| Lead demographics | Targeting assessment | Yes — infers from reply patterns |
342| Open tracking | Open rate analysis | Partially — reply rate + copy still run |
343
344**Minimum viable data:** Emails sent + reply count + email copy text.
345
346## Cost
347
348Free. Pure reasoning + data from user's outreach tool.
349
350## Tips
351
352- **Run at Day 7 and Day 14.** Day 7 catches deliverability and subject line problems. Day 14 gives enough replies for objection analysis.
353- **Reply analysis is where the gold is.** Metrics tell you WHAT. Replies tell you WHY.
354- **High open + low reply = copy problem.** The subject gets them to open but the email doesn't deliver.
355- **Low open + decent reply rate = subject line problem.** The email works, people just aren't seeing it.
356- **"Not relevant" is the most important objection.** If >20% say "this isn't for me," it's targeting, not copy.
357- **Don't kill a variant too early.** Need 100+ sends per variant for directional data.
358- **Touch 2/3 should contribute 30-40% of replies.** If Touch 1 is 90%+, your follow-ups aren't adding value.
majiayu000