How to weigh engagement vs risk in decision logic?

In a perfect world, every address on your list would be both technically valid and actively engaged. In reality, you have addresses where these two signals point in different directions: an address might be risky but recently engaged, or valid but completely silent. The decision of what to do with them requires a risk hierarchy, not a simple rule.

When risk overrides engagement (no exceptions):

• Confirmed spam traps. It doesn't matter if the address opened your email last week. A spam trap is a spam trap. Suppress it immediately.
• Addresses on abuse networks or confirmed complaint databases. Same rule applies.
• Hard bounces. The address is gone. Engagement history is irrelevant when the mailbox doesn't exist.

This is the category where engagement data can mislead you. A spam trap that "opened" your last campaign (because some trap operators do monitor what arrives) doesn't become a safe address because of that signal.

When engagement can override risk:

• Catch-all domains: The validation result is inconclusive because the server accepts everything. But if this address has opened and clicked across multiple campaigns, you have strong real-world evidence that the mailbox is valid and the person is engaged. Keep sending.
• Old addresses with stale validation: Validation was run a year ago and the address came back risky due to domain issues. But since then the domain has resolved and the person has clicked. The behavior is more current than the validation result.
• Unknown addresses from borderline sources: If the address came from a co-registration (medium risk) but has shown strong engagement over three campaigns, that engagement signal is meaningful context. Monitor rather than suppress.

The practical decision framework:

• Toxic risk category: suppress, no engagement exception
• Structural risk (catch-all, unknown): check engagement. If positive, keep or monitor
• Source risk (borderline acquisition): watch engagement closely; one campaign of silence tips toward monitor, three toward suppress

If you're building this logic into your own suppression system, the signal hierarchy is: risk classification first, then engagement trend, then source quality. All three together give you a more accurate picture than any one alone. Defining your policy thresholds in advance makes these decisions faster and more consistent at scale.