Subscribe to our newsletter
We see the same category of problems repeatedly, but in different combinations and with different severity. These aren’t surface-level issues. They’re systemic problems that tools miss and that responsible operators often don’t see until reputation starts degrading visibly.
Authentication Misalignment
This is more common than it should be. A company configures SPF, DKIM, and DMARC correctly according to their ESP’s documentation, but doesn’t account for the actual flow of their mail. They might be sending email through multiple ESPs without realizing it, or they changed email providers six months ago and never cleaned up old DNS records, or they’re sending from a domain but not aligned the DKIM to that domain.
The result: authentication technically works, but isn’t as strong as it should be. Mail that should be passing DKIM alignment fails occasionally. SPF includes too many providers. DMARC policy is set to monitoring when it should be enforcing.
We also see authentication gaps in more complex infrastructure. A company might have correct DMARC alignment on their marketing domain, but not on the subdomain they use for transactional email. They might have proper authentication on cold email sending, but not on their webhook-based transactional infrastructure.
DNS and Infrastructure Gaps
Your DNS tells a story about your mail infrastructure. Sometimes that story is incomplete. Missing reverse DNS (PTR records). IPs that don’t match the domains they claim to represent. Incomplete or outdated SPF records that list providers you haven’t used in years. These gaps matter less for technical correctness and more for reputation signals that mailbox providers use to assess trustworthiness.
We’ve also seen cases where companies have infrastructure gaps they weren’t aware of: they think they’re sending from one IP but their ESP is distributing across multiple IPs without proper reputation separation. They think their IP is dedicated but it’s shared with other senders. They have multiple sending IPs but only one is warmed.
Volume and Cadence Misalignment
Mailbox providers care deeply about consistency. When you change your sending volume dramatically, or shift your sending time, or change your target audience geography, those changes get noticed. They trigger higher scrutiny of your mail.
We see companies that ramped volume too aggressively relative to their domain’s sending history. They send 5,000 emails a week for six months, then try to jump to 50,000 a week. The mailbox provider sees this as unusual behavior and filters more of the mail until reputation stabilizes.
We see seasonal senders who restart sending after a long pause without accounting for how reputation degrades. A newsletter sender takes a three-month break, restarts in month four, and gets filtered more aggressively because the mailbox provider has forgotten them.
We see companies that shift their target audience without realizing the reputation impact. A B2B SaaS company starts targeting a new geography, and gets filtered more aggressively there because the mailbox provider doesn’t have established reputation for them in that region.
Complaint Risk and List Quality
Most companies monitor complaint rates, but few monitor complaint risk – the likelihood that unengaged subscribers will complain if you keep mailing them. A list might look fine by complaint metrics but be heading for a complaint spike if you keep mailing it without re-engagement efforts.
We assess list age, engagement rates, subscription method, and re-engagement patterns to identify list quality problems before they become visible as complaint spikes. We also look at whether complaint increases are being handled properly (removing complainers, analyzing complaint patterns, adjusting sending if needed).
Cold email is particularly prone to complaint risk. A sender might be getting a 0.5% complaint rate (which seems fine) while actually mailing 80% of people who are not engaging (which is a complaint spike waiting to happen).
Language Patterns and Content Issues
Modern spam filters use machine learning to detect patterns in content. They’re looking for things like: consistent use of high-pressure language, repeated selling patterns, headers that don’t match content, links that don’t match visible text.
We assess your content patterns for signals that modern filters watch for. Sometimes the problem is obvious (you’re using all-caps subject lines, or your copy has the feel of classic spam). Often it’s subtle (you’re using the same urgency pattern in every subject line, or your calls to action trigger filters in certain mailbox providers, or your links look suspicious to reputation algorithms).
These patterns compound across campaigns. A single email with slight red flags passes through. Fifty emails from the same sender all with the same pattern triggers filters.
System Interaction Problems
Sometimes the problem isn’t any single element, but how elements interact.
Your cold outreach has high complaint risk, which damages your domain reputation. That reputation damage affects your marketing email and transactional email. Your complaint rate is technically fine, but your unsubscribe rate is high, and high unsubscribe is an engagement signal that triggers filtering.
We look for these system-level interactions. A diagnostic often surfaces a primary problem (usually reputation or behavior related) that’s masking or compounding secondary problems. Fix the primary problem and the secondary problems sometimes resolve themselves.
We’d love to learn more about your business, email deliverability and outreach goals, and see if we might be able to help.
Whether you have questions about what we do, how Protocol works, or you’d just like to pick our brains on some of our best practices, we’d be happy to chat.
Schedule a call with our Revenue Director, Chrisley Ceme.
We see the same category of problems repeatedly, but in different combinations and with different severity. These aren’t surface-level issues. They’re systemic problems that tools miss and that responsible operators often don’t see until reputation starts degrading visibly.
Authentication Misalignment
This is more common than it should be. A company configures SPF, DKIM, and DMARC correctly according to their ESP’s documentation, but doesn’t account for the actual flow of their mail. They might be sending email through multiple ESPs without realizing it, or they changed email providers six months ago and never cleaned up old DNS records, or they’re sending from a domain but not aligned the DKIM to that domain.
The result: authentication technically works, but isn’t as strong as it should be. Mail that should be passing DKIM alignment fails occasionally. SPF includes too many providers. DMARC policy is set to monitoring when it should be enforcing.
We also see authentication gaps in more complex infrastructure. A company might have correct DMARC alignment on their marketing domain, but not on the subdomain they use for transactional email. They might have proper authentication on cold email sending, but not on their webhook-based transactional infrastructure.
DNS and Infrastructure Gaps
Your DNS tells a story about your mail infrastructure. Sometimes that story is incomplete. Missing reverse DNS (PTR records). IPs that don’t match the domains they claim to represent. Incomplete or outdated SPF records that list providers you haven’t used in years. These gaps matter less for technical correctness and more for reputation signals that mailbox providers use to assess trustworthiness.
We’ve also seen cases where companies have infrastructure gaps they weren’t aware of: they think they’re sending from one IP but their ESP is distributing across multiple IPs without proper reputation separation. They think their IP is dedicated but it’s shared with other senders. They have multiple sending IPs but only one is warmed.
Volume and Cadence Misalignment
Mailbox providers care deeply about consistency. When you change your sending volume dramatically, or shift your sending time, or change your target audience geography, those changes get noticed. They trigger higher scrutiny of your mail.
We see companies that ramped volume too aggressively relative to their domain’s sending history. They send 5,000 emails a week for six months, then try to jump to 50,000 a week. The mailbox provider sees this as unusual behavior and filters more of the mail until reputation stabilizes.
We see seasonal senders who restart sending after a long pause without accounting for how reputation degrades. A newsletter sender takes a three-month break, restarts in month four, and gets filtered more aggressively because the mailbox provider has forgotten them.
We see companies that shift their target audience without realizing the reputation impact. A B2B SaaS company starts targeting a new geography, and gets filtered more aggressively there because the mailbox provider doesn’t have established reputation for them in that region.
Complaint Risk and List Quality
Most companies monitor complaint rates, but few monitor complaint risk – the likelihood that unengaged subscribers will complain if you keep mailing them. A list might look fine by complaint metrics but be heading for a complaint spike if you keep mailing it without re-engagement efforts.
We assess list age, engagement rates, subscription method, and re-engagement patterns to identify list quality problems before they become visible as complaint spikes. We also look at whether complaint increases are being handled properly (removing complainers, analyzing complaint patterns, adjusting sending if needed).
Cold email is particularly prone to complaint risk. A sender might be getting a 0.5% complaint rate (which seems fine) while actually mailing 80% of people who are not engaging (which is a complaint spike waiting to happen).
Language Patterns and Content Issues
Modern spam filters use machine learning to detect patterns in content. They’re looking for things like: consistent use of high-pressure language, repeated selling patterns, headers that don’t match content, links that don’t match visible text.
We assess your content patterns for signals that modern filters watch for. Sometimes the problem is obvious (you’re using all-caps subject lines, or your copy has the feel of classic spam). Often it’s subtle (you’re using the same urgency pattern in every subject line, or your calls to action trigger filters in certain mailbox providers, or your links look suspicious to reputation algorithms).
These patterns compound across campaigns. A single email with slight red flags passes through. Fifty emails from the same sender all with the same pattern triggers filters.
System Interaction Problems
Sometimes the problem isn’t any single element, but how elements interact.
Your cold outreach has high complaint risk, which damages your domain reputation. That reputation damage affects your marketing email and transactional email. Your complaint rate is technically fine, but your unsubscribe rate is high, and high unsubscribe is an engagement signal that triggers filtering.
We look for these system-level interactions. A diagnostic often surfaces a primary problem (usually reputation or behavior related) that’s masking or compounding secondary problems. Fix the primary problem and the secondary problems sometimes resolve themselves.
Our Revenue Director, Chrisley Ceme, is leading the Triggered Outbound program.Chrisley’s gone deep on this strategy and can walk you through:
- How Triggered Outbound fits with your outbound goals
- What triggers are available (and what’s possible within our platform)
- Pricing, onboarding, and getting started
