- Treat opens as a rough signal, not proof of reading.
- Filter automated clicks before you report to sponsors or judge an issue.
- Use first-party click tracking so you can see timing and patterns.
- Weight replies, real clicks and conversions above opens.
Where fake engagement comes from
- Privacy features that preload images. Some mail apps load every image when the email arrives, which records an open whether or not anyone read it.
- Corporate security scanners. Business email systems often open messages and visit every link to check for threats before a person sees them. Each visit looks like a click.
- Link previews and bots. Messaging apps, browser extensions and crawlers can fetch links too.
Illustrative example. Figures are fictional.
1. Own your click tracking
Route newsletter links through your own redirect, so every click is logged with its timing, the link and the recipient. Platform dashboards rarely let you see the raw patterns you need to filter.
2. Score clicks by behavior
Scanners behave differently from people. They click within seconds of delivery, often hit every link in the email at once, and arrive in bursts from the same network. People click later, choose a link or two, and spread out over hours.
3. Report filtered numbers, and say so
Report engagement after removing automated activity, and tell sponsors that you do. Lower but honest numbers build more trust than inflated ones that never turn into results.
4. Look for signals scanners cannot fake
Replies, survey answers, purchases, signups from a sponsor's landing page and repeat clicks over several issues are much harder for software to imitate.
What most guides miss
Lessons from systems we have built and run, not the usual checklist.
The inflation is worst where sponsors pay most
B2B newsletters reach corporate inboxes, which are exactly where security scanners run. A business audience can show click rates several times higher than real reading, which means a sponsor sees great numbers and weak results.
Filters can be too aggressive
A filter that removes too much will hide real readers and, if it feeds list cleaning, delete them. Review what a new rule removes before trusting it, and keep a way to restore people.
Your event pipeline can drop data
When you collect events yourself, a large send arrives as a burst. Make sure your system stores every event under that load, or your filtered numbers will be wrong in ways that look plausible.
Opens still have a use
Opens are unreliable for judging a single issue, but trends over time and comparisons between segments are still useful.
How we do it
We build first-party click tracking, behavior-based filtering and reporting that separates real readers from automated activity as part of our growth systems. Related: the deliverability checklist.