Do “spammy” words affect cold deliverability?

The impact of specific words on deliverability is often overstated and misunderstood.

Modern reality:

• Spam filters use machine learning, not simple word lists
• Context matters more than individual terms
• Sender reputation outweighs content factors
• Engagement signals drive filtering decisions

What actually triggers filters:

• Patterns across many messages (same content, same sender, low engagement)
• Technical issues (authentication failures, poor infrastructure)
• Behavioral signals (high complaints, low opens)
• Sending to invalid or trap addresses

Words that can indicate problems:

• Financial promises (guaranteed, free money)
• Urgent manipulation (act now, limited time)
• Deceptive framing (re: when not a reply, fwd: when not forwarded)
• These matter more in context than in isolation

Better focus areas:

• Maintain good sender reputation
• Send to people who want your email
• Write naturally, not around assumed trigger words
• Monitor deliverability metrics, not word lists
• Write good emails for humans. Filters follow engagement, not vocabulary lists.