162 posts · page 3 of 18
Under 0.5% per campaign is healthy; consistently above 1% signals a real problem. This guide covers the correct formula, benchmark ranges by email type, why a near-zero rate is its own warning sign, a six-step diagnostic for spikes, and practical fixes that lower churn without hiding the unsubscribe link.
Email webhooks push delivery, bounce, click, and complaint events to your application in real time instead of making you poll an API. This guide covers the event types and how far to trust each one, payload structure, building an endpoint that acknowledges fast and processes async, signature verification, handling duplicates and out-of-order delivery, and automatic suppression.
An AI subject line generator is worth using for the same reason a thesaurus is: it gives you options you would not have reached. Here is how to get useful ones.
Most email A/B tests are not tests — they are noise read as signal. This guide covers writing a real hypothesis, choosing variables by impact, splitting the list correctly, the sample sizes needed to detect a given difference, why open rate is the wrong success metric, and how to build a testing program instead of a testing habit.
At high volume, your mail queue decides whether password resets arrive in seconds or minutes. Here is how to separate traffic classes, throttle per destination, build a retry ladder with jitter, enforce idempotency, and monitor the metrics that matter.
B2B email fails for different reasons than B2C email. Smaller lists, longer cycles, buying committees — and a reply is worth more than a click.
SMTP AUTH proves your client may send; SPF and DKIM prove your message is genuine. This guide compares PLAIN, LOGIN, CRAM-MD5, SCRAM, and XOAUTH2, walks the handshake step by step, maps ports to encryption modes, and decodes the errors you will actually hit.
The famous $36-to-$1 figure is a survey average, not your number. Here is how to calculate email ROI in a way that would survive a finance review.
How long to keep each type of subscriber data, from consent records and engagement history to suppression lists that should never be deleted. Includes a retention period table by data type, the delete vs anonymize vs suppress decision, and a six-step policy you can actually operate.
The month's most useful guides and one practical tip, on the first Tuesday. Nothing else.
