Operations skill

Cold email campaign metrics reader

Share campaign or A/B numbers and the assistant checks the measurement first, then gives a verdict with a confidence level: winner, no difference yet, or invalid comparison.

What the skill checks

  • Uses emails sent as the denominator
  • Reads step-1 reply rate on a fixed list
  • Separates human replies from automatic replies
  • Counts opportunities per 1,000 leads contacted
  • Checks reply maturity, sample size and that arms differ in one thing
  • Confirms the sent body matches the variant before crediting copy

Use it when

  • Reading an A/B test between two copies or subject lines
  • Reply rate dropped and you need to know if it is real
  • Reporting campaign results to a client or a manager

Example

What you paste and what you get back

You
A: 1,200 sent, 14 replies, 2 interested. B: 1,150 sent, 9 replies, 3 interested. Which copy wins?
Assistant, with the skill
Reply rate: A 1.17%, B 0.78%.
Opportunities per 1,000 contacted: A 1.7, B 2.6.
Verdict: no difference yet. Confidence: low.
Why: 2 versus 3 opportunities is noise, and B has fewer replies but more interest.
Next: 3,000 more sends per arm, same list and start time.

Install Cold email campaign metrics reader

Claude Code

Terminal
mkdir -p ~/.claude/skills/campaign-metrics-reader
curl -fsSL https://outreach2day.com/skills/campaign-metrics-reader/SKILL.md -o ~/.claude/skills/campaign-metrics-reader/SKILL.md

Cursor and other coding agents

Terminal, in your project
mkdir -p .cursor/rules
curl -fsSL https://outreach2day.com/skills/campaign-metrics-reader/SKILL.md -o .cursor/rules/campaign-metrics-reader.mdc

Claude on the web or desktop: upload the ZIP. ChatGPT, Gemini, Grok and AGENTS.md: steps for every assistant.

Source

campaign-metrics-reader/SKILL.md

campaign-metrics-reader/SKILL.md
---
name: campaign-metrics-reader
description: Reads cold email campaign results without the usual mistakes - uses emails sent as the denominator, reads step-1 reply rate on a fixed list instead of a blended daily rate, separates human and automatic replies, counts opportunities per 1,000 leads contacted, waits for replies to arrive before comparing, checks that samples are large enough, compares arms that differ in one thing, and confirms the actual sent body before crediting a copy. Returns a readout with a verdict and a confidence level. Use when the user shares campaign stats, an A/B test, a sequencer export or a dashboard and asks what is working, which variant won or why results dropped.
---

# Campaign metrics reader

You turn cold email numbers into a verdict the user can act on, and you say how sure you are. Most wrong conclusions in cold email come from the wrong denominator, a mixed blend or too few sends; you check those first.

## Step 1. Collect

Ask for, per campaign or variant:

1. Emails sent (not leads uploaded), per step if possible.
2. Replies, split into human and automatic (out-of-office, auto-acknowledgements) if the tool separates them.
3. Opportunities: replies classified as interested, meeting request or referral.
4. Bounces.
5. Start date and time of each arm, list source, mailboxes used.
6. The actual subject and body that were sent (from the sent log, not the draft).

## Step 2. Check the measurement

Report each as `OK` or `PROBLEM`:

1. **Denominator**: rates use emails sent. Leads uploaded but not yet contacted inflate the base and deflate every rate.
2. **Step mix**: a daily blended reply rate mixes first emails and follow-ups, and new lists with old ones. When the mix shifts, the blend moves with no real change. Read step 1 on a fixed list family.
3. **Human vs automatic replies**: they are separate counts. Automatic replies say the email arrived; they are not interest.
4. **Maturity**: most replies to a send arrive within a few hours. Do not read an arm in its first hours, and compare only arms that started at the same time.
5. **Sample size**: with a few hundred sends, a difference of one or two replies is noise. Ask for a few thousand sends per arm before a verdict on reply rates; opportunities need more.
6. **One difference**: the arms differ in one thing (copy, or list, or mailboxes). If two things changed, the result cannot be credited to either.
7. **What was sent**: the sent body matches the variant name. Check at least 3 sent emails per arm for rendered variables and spintax.

## Step 3. Compute

- Reply rate = human replies / emails sent, per step.
- Opportunities per 1,000 leads contacted = opportunities / unique leads contacted x 1,000.
- Bounce rate = bounces / emails sent.
- For two arms, give the difference and a rough confidence: with small counts, say "not distinguishable".

Reply rate alone is vanity: an arm with more replies and fewer opportunities is worse.

## Step 4. Verdict

One of: `winner`, `no difference yet`, `invalid comparison`, `investigate`. Add what would change the verdict (for example "2,000 more sends per arm").

## Output format

1. Measurement checks with OK or PROBLEM.
2. A table per arm: sent, human replies, reply rate, opportunities, opportunities per 1,000, bounce rate.
3. Verdict, confidence (low, medium, high) and the reason in two sentences.
4. Next step.

## Rules

- Never declare a winner on a one or two event difference.
- If placement may have changed (bounces up, automatic replies down on all arms at once), say the drop may be delivery, not copy, and suggest a placement test.
- Do not mix campaigns from different lists into one "copy" comparison.

## Example

Input: "A: 1,200 sent, 14 replies, 2 interested. B: 1,150 sent, 9 replies, 3 interested. Which copy wins?"

Output (abridged): Reply rate A 1.17%, B 0.78%. Opportunities per 1,000: A 1.7, B 2.6. Verdict: no difference yet, low confidence: 2 versus 3 opportunities is noise, and B has fewer replies but more interest. Next: 3,000 more sends per arm, same start time and list.

Download SKILL.md · Download ZIP

Questions

What is a good reply rate for cold email?

It depends on list and offer too much for one number. Compare arms on the same list at the same time, and judge them by opportunities per 1,000 leads as well as reply rate.

How many emails do I need to send for an A/B test?

A few thousand per arm before trusting a reply-rate difference, more for opportunities. With a few hundred sends, one or two replies of difference is noise.

Why did my daily reply rate drop?

Often the mix changed: more follow-ups or a weaker new list in the blend. Read step 1 on one list family. If every arm drops at once and bounces rise, check delivery before the copy.

Should out-of-office replies count as replies?

No. Count human and automatic replies separately. Automatic replies show only that the email arrived.

Mailboxes, warmup and sending in one place

$2.50 a mailbox a month. DNS records are set for you, and every mailbox shows its warmup numbers from day one.

Deliverability call

Talk to our deliverability team

Book a call with the people who run our mailbox infrastructure. We look at your current setup and tell you what to change.

  • Review your domains, DNS records and current inbox placement
  • Size the setup: domains, mailboxes per domain and daily volume per mailbox
  • Plan warmup and the move from your current provider or sequencer

Free call

See open times in your time zone and book on this page.

Or open the booking page