# Email Open Rate Calculator

- **URL:** https://codeasystem.com/calculators/marketing/email-open-rate-calculator/
- **Category:** marketing
- **Description:** Measure email open rate, click rate and click-to-open rate from delivered counts, opens and clicks.
- **Primary output:** Open rate: 22.5%

## Inputs
- Emails delivered (name: `delivered`, type: number, example: 2000)
- Unique opens (name: `opens`, type: number, example: 450)
- Unique clicks (name: `clicks`, type: number, example: 90)

## Outputs
- Open rate: 22.5%
- Click rate (of delivered): 4.5%
- Click-to-open rate: 20%
- Non-openers: 1,550

## Formula / methodology
```
Open rate = opens ÷ delivered
Click rate = clicks ÷ delivered     Click-to-open rate = clicks ÷ opens
```

Three complementary views: open rate measures subject-line pull against everything delivered; click rate measures overall action against delivery; click-to-open isolates content effectiveness among people who actually looked.

## Assumptions & limitations
- Unique per-person counts, not raw total opens and clicks.
- Delivered excludes bounces but includes privacy-inflated opens.
- Apple Mail privacy prefetching can inflate open figures materially.

## How to use
1. **Start from delivered, not sent**; Bounced addresses never saw anything, so honest rates use delivered as the denominator.
2. **Use unique counts**; One person opening five times counts once here; most platforms report both; pick uniques.
3. **Read all three together**; Strong opens with weak CTOR means subjects oversell the content; weak opens shift attention to deliverability and timing first.

## Example
Of 2,000 delivered emails, 450 opens make a 22.5% open rate; 90 clicks yield a 4.5% click rate and a 20% click-to-open rate among openers.

Result for these inputs:

```
Open rate: 22.5%
```

## About this calculator
### The Apple Mail open problem

Since Mail Privacy Protection, Apple prefetches images for users who never looked, inflating opens. Treat open rate as directional and weight click-based numbers; which require genuine intent; far more heavily.

### CTOR separates subject from story

When open rate holds but click-to-open falls, recipients were hooked by the subject then let down inside. The fix is content relevance, not another subject-line experiment.

### List hygiene beats cleverness

Engagement decays as lists age. Regularly sunsetting non-openers lifts every metric here, protects sender reputation, and paradoxically raises absolute revenue per send.

## FAQs
### What is a good open rate?

Roughly 17–28% covers typical cross-industry medians, though it varies by list quality and audience. Trend against your own sends; Apple inflation makes cross-company comparisons unreliable now.

### Why do opens exceed clicks so dramatically?

Opening takes curiosity; clicking takes motive. Click-to-open rates of 10–20% are normal, and 20%+ signals genuinely aligned message-market fit.

### Should I A/B test subject lines?

Yes; they remain the largest single lever on opens. Just confirm any winner also sustains clicks, since curiosity-gap subjects often win opens and lose downstream engagement.

## Related calculators
- [Conversion Rate Calculator](https://codeasystem.com/calculators/marketing/conversion-rate-calculator/)
- [CTR Calculator](https://codeasystem.com/calculators/marketing/ctr-calculator/)

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Last updated: 2026-08-23 · Version: 1.0.0 · [HTML version](https://codeasystem.com/calculators/marketing/email-open-rate-calculator/)