> ## Documentation Index
> Fetch the complete documentation index at: https://docs.letterbucket.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Post Analytics

> Understand how your emails and posts perform with detailed metrics

Every delivered post has a dedicated analytics view. Click on any delivered post in **Posts** and open the **Analytics** tab to see how it performed.

## Overview metrics

At the top of the analytics view you'll find the core stats:

| Metric        | What it means                                          |
| ------------- | ------------------------------------------------------ |
| **Sent to**   | Total number of subscribers the email was delivered to |
| **Open rate** | Percentage of recipients who opened the email          |
| **CTR**       | Percentage of recipients who clicked at least one link |

These are the same numbers shown on the post cards in your **Posts** list.

## Opens over time

A chart showing how opens accumulated after the email was sent — broken down by **hour** or **day**.

This tells you when your audience is most engaged. Most opens happen in the first few hours after sending. If you see a second spike, it may be from the web version being shared or discovered later.

## Link clicks

A breakdown of every link in your email, ranked by click count. For each link you can see:

* The URL
* Total number of clicks
* Click progression over time

Use this to understand which calls-to-action resonated most and which content drove the most engagement.

## Poll results

If your post included one or more polls, the **Polls** section shows:

* **Vote counts per option** — how many subscribers chose each answer
* **Total votes** across all polls in the post
* **Vote progression** — a timeline showing when votes came in, broken down hourly or daily

Click on an individual poll to see its detailed progression view.

<Info>
  Analytics data starts from the first tracked event after sending. Posts that were sent but never opened will show zero data.
</Info>

## Date range filtering

You can filter all analytics charts by date range to focus on a specific window after sending. This is useful for comparing early engagement vs. long-term reach.

<Tip>
  Compare open rate vs. CTR across your posts to find patterns. High open rate + low CTR may mean your subject line is strong but the content or CTA needs work. Low open rate + high CTR may mean only your most engaged readers are opening — which is actually a strong signal.
</Tip>