Deliverability analytics
Deliverability analytics tell you what happened to the email that you sent. You select metrics and a time window. Lettermint returns the totals, and can also return a time series and a breakdown by provider, domain, tag, or SMTP reply.
Deliverability analytics are available on the Pro plan.
Questions that analytics answer
- Which mailbox provider defers or refuses your email?
- Did the bounce rate change after your last release?
- Which replies from receiving servers cause the most bounces?
- How long does delivery take for most recipients, and for the slowest 1 percent?
- Do people open your email, or do machines?
- Which campaign tag has the most complaints?
Ways to use analytics
| Method | Use it to | Status |
|---|---|---|
| API | Build reports, alerts, and dashboards in your own systems | Available |
| MCP server | Ask an AI assistant a question in plain language | Available |
| Dashboard | See charts in the Lettermint dashboard | Not available yet |
The API and the MCP server run the same query on the same data. They return the same numbers.
How Lettermint counts
These rules explain most of the numbers that you see.
The unit is a recipient
One email to three addresses is three recipients. Each recipient has its own delivery result, so Lettermint counts recipients. The metric messages is the exception. It counts emails.
An event counts at the time that it happened
Lettermint does not count an event at the time that you sent the email. An email with this history adds to three different hours:
| Time | Event | Metric that increases |
|---|---|---|
| 09:58 | Lettermint accepts the email | accepted in the 09:00 bucket |
| 10:02 | The receiving server accepts the email | delivered in the 10:00 bucket |
| 14:30 | The recipient opens the email | human_opens in the 14:00 bucket |
This method shows you when something happened. A provider that starts to defer your email at 10:00 shows up in the 10:00 bucket, even for email that you sent the day before.
It has one side effect. In a short window, the opens can belong to email that was delivered before the window. A rate can then be higher than 1.
The buckets of a time series add up to the summary
Each event is in one bucket only. The sum of a count over all buckets is equal to the count in the summary. This applies to counts, not to rates or percentiles.
A recipient opens one time
human_opens counts a recipient one time, when the first open happens. The recipient stays counted in that bucket, and later opens do not count again. To count each open, use human_opens_events.
Test email and Sandbox email are not counted
Email to the test addresses at @lettermint.dev is not in analytics. Email from a Sandbox project is not in analytics.
Analytics are not real time
A new event appears in analytics after a short delay. Each response includes meta.last_ingested_at, the time of the newest data that the query read.
What analytics do not tell you
Inbox placement. delivered means that the receiving server accepted the email. The server can still put the email in the spam folder.
The history of one recipient. Analytics do not store recipient addresses. To find one email, use Email activity.
Inbound email. Analytics cover the email that you send.
Access
| Method | You need |
|---|---|
| API | A Team API token with the read:analytics ability |
| MCP server | A role with the View analytics permission, in a team that allows MCP access |
Two more rules apply:
- A team member sees the analytics of the projects in their project access only. A Team API token sees all projects of the team.
- The dimensions
from_addressandsubjecthold personal data. The token also needsread:messages. A team member also needs View messages.
How long Lettermint keeps analytics
A query can cover up to 90 days. The data that is available depends on the retention period. See Data retention.
Each response includes meta.available_since. Lettermint has no analytics before this time.
Next steps
Query analytics with the API
Send your first query and read the response.
Ask an AI assistant
Use the MCP server to query analytics in plain language.
Metrics
Read the definition of each metric and the formula of each rate.
Examples
Copy complete queries for common questions.