Measuring Email Performance
Open, click, and revenue.
Measuring Email Performance is a free Digital Marketing Academy lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Digital Marketing Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Why Measurement Matters
You cannot improve what you do not measure. Email metrics tell you whether subscribers open, engage, and convert, and where flows leak value.
Vanity numbers like list size mean little. Focus on metrics tied to behavior and revenue to guide real decisions.
Open Rate
Open rate is the share of delivered emails that were opened. It signals subject-line strength and sender reputation.
Note that privacy features can inflate opens, so treat it as a directional signal rather than absolute truth.
Open Rate = opens / delivered
Example: 4,200 / 20,000 = 21%Click-Through Rate
Click-through rate (CTR) measures how many recipients clicked a link. It reflects how compelling your content and call to action are.
CTR is harder to game than opens, making it a more reliable engagement signal.
CTR = clicks / delivered
Example: 600 / 20,000 = 3%Click-to-Open Rate
Click-to-open rate (CTOR) isolates content quality by measuring clicks among those who actually opened.
A high open rate but low CTOR suggests the subject line worked but the email content or offer did not deliver.
CTOR = clicks / opens
Example: 600 / 4,200 = 14.3%Conversion Rate
Conversion rate is the ultimate metric: the share of recipients who completed the goal, such as a purchase or signup.
It connects email directly to business results. Two emails with equal clicks can have very different conversion rates.
Conversion Rate = conversions / delivered
Example: 120 / 20,000 = 0.6%Bounce Rate
Bounce rate is the share of emails that could not be delivered. Hard bounces are permanent (invalid address); soft bounces are temporary (full inbox).
High bounce rates damage sender reputation. Remove hard bounces immediately to protect deliverability.
Bounce Rate = bounces / sent
Hard bounce -> remove from list now
Soft bounce -> retry, remove after repeatsUnsubscribe and Complaints
Unsubscribe rate and spam-complaint rate are warning signals. A spike means your content, frequency, or targeting is off.
Keep complaints well below industry thresholds; mailbox providers penalize senders who generate too many.
Unsub Rate = unsubscribes / delivered
Complaint Rate = spam_reports / delivered
Target: complaints < 0.1%Revenue Metrics
For commerce, track revenue per email and revenue per recipient. These reveal which flows actually earn money, not just attention.
Automated flows often show far higher revenue per email than broadcasts, which justifies investing in them.
Revenue per Email = total revenue / emails sent
Example: 4,000 / 20,000 = 0.20 per emailA/B Testing
A/B testing compares two versions to learn what works. Change one variable at a time, subject line, CTA, or send time, so results are clear.
Run tests on a large enough sample and wait for statistical confidence before declaring a winner.
Test: subject line
A: "Your cart is waiting"
B: "Don't miss out, Maria"
Winner: higher open rate at 95% confidenceBenchmarks and Context
A 20% open rate is good in one industry and poor in another. Compare against your own past performance and your sector's benchmarks.
Trends over time matter more than any single send. Watch the direction your metrics are moving.
Turning Data Into Action
Metrics are useless without decisions. Low opens? Test subjects and clean your list. Low CTOR? Rework content and offer.
High unsubscribes? Reduce frequency or improve targeting. Each metric points to a specific lever you can pull.
Low open rate -> fix subject + list hygiene
Low CTOR -> fix content + CTA
Low conversion -> fix offer + landing page
High unsub -> reduce frequencyQuick Check
Check your understanding of email metrics.
Recap
Track opens, CTR, CTOR, conversion, bounce, unsubscribe, and revenue metrics to understand email performance from subject line to sale.
Use A/B tests, compare against benchmarks and your own trends, and turn each metric into a concrete action to keep improving.
Frequently asked questions
Is the “Measuring Email Performance” lesson free?
Yes — the full text of “Measuring Email Performance” is free to read here on the web, and the Digital Marketing Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Digital Marketing Academy course, upgrade to CoddyKit PRO.
What will I learn in “Measuring Email Performance”?
Open, click, and revenue. You practise Digital Marketing Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Digital Marketing Academy?
No prior experience is required. Digital Marketing Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Measuring Email Performance” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Digital Marketing Academy lesson?
Yes. Every Digital Marketing Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Why Automation
- Welcome Sequences
- Segmentation and Triggers
- Measuring Email Performance