There’s a specific kind of frustration that comes from watching your email list grow while engagement stalls. You’re doing the right things on paper—audience growth, consistent sends, subject line testing—but the results don’t line up.

For this B2B financial services firm, the concern was more specific: they suspected their emails weren’t reliably reaching inboxes. Their subscriber base had grown from 665 to more than 1,500 contacts, yet open rates were trending down. At the same time, they were paying for marketing contacts who either never received emails or shouldn’t have been included in sends at all.

The pattern pointed to infrastructure problems, not content problems.

The Challenge

On the surface, the newsletter program looked healthy. In practice, engagement was erratic. Open rates swung between 8% and 25% with no consistent relationship to content quality or timing.

Early conversations surfaced several red flags:

• Active marketing contacts weren’t receiving emails
• Suppression logic was unclear and inconsistently applied
• Domain-based exclusions didn’t seem to work as expected
• Marketing contact spend didn’t reflect actual send behavior

The business impact was twofold: unreliable engagement data and unnecessary platform costs. They needed a technical audit of the system underneath the program, not another round of creative optimization.

The Approach

We started with infrastructure. When engagement issues show up across multiple sends and content types, delivery and logic are the first things to validate.

The audit focused on four areas where email programs often fail quietly: authentication, suppression architecture, domain filtering, and marketing contact allocation.

Email Authentication

We reviewed their DMARC, SPF, and DKIM records first. These were configured correctly, which ruled out outright authentication failure but gave us a verified baseline. We documented the setup for future reference and moved deeper into list logic.

Suppression Architecture

This was the first real failure point.

The client had built suppression lists to exclude certain organizations—partners who shouldn’t receive promotional emails. The issue wasn’t intent; it was structure. Suppression logic was fragmented across multiple lists, which meant a contact could be suppressed in one context and included in another.

Some contacts marked as marketing contacts were also permanently suppressed. They were never going to receive emails but still counted toward contact limits.

We mapped the full suppression setup and rebuilt it around centralized logic that applied consistently across all sends.

Domain Filtering

We found a syntax error that explained much of the confusion.

Their lists filtered for domains using values like ‘@xyz.com.’ In HubSpot, domain filters should only use ‘xyz.com’—including the @ symbol breaks the matching. As a result, contacts from excluded organizations were still receiving emails.

We corrected domain filtering across all active lists and validated exclusions through test sends.

Marketing Contact Allocation

Once suppression and filtering were fixed, we addressed contact status.

Contacts who should never receive marketing emails were still flagged as marketing contacts. We identified which records should be downgraded or removed entirely and aligned contact status with actual send eligibility. This eliminated ongoing spend tied to unusable contacts.

Engagement Metrics

Finally, we reset how success was measured.

Open rates were treated as directional, not definitive. With privacy changes and inbox prefetching, they’re noisy at best. We shifted primary reporting to click-through rates, which reflect real engagement, and documented how to interpret both metrics going forward.

The Deliverables

The audit resulted in practical, system-level improvements:

• Corrected domain filtering syntax across all active lists
• Centralized suppression logic applied consistently across sends
• Documented DMARC, SPF, and DKIM configuration for future troubleshooting
• Marketing contact audit with clear recommendations for removal or reclassification
• Engagement dashboard prioritizing click-through rates
• A testing framework for subject lines, layout, and content—now backed by reliable delivery

This wasn’t cleanup for its own sake. It was about making the system behave predictably.

The Outcome

Once the foundation was fixed, performance stabilized quickly.

• Open rates increased 69%, from a 13.8% average to 23.34% on the first post-fix send.
• Subscriber count grew 135%, from 665 to 1,564, without degrading deliverability.
• Click-through rate (CTR) consistently ranged between approximately 3% and 8%, increasing as the audience expanded. Variations over time reflected growth in total recipients rather than declining engagement.
• Marketing contact spend dropped by eliminating contacts that never received emails.

Just as important, the team could finally test with confidence. With delivery issues resolved, A/B tests produced meaningful signals instead of noise.

What This Means for Email Programs at Scale

Most engagement problems aren’t creative problems. Before changing templates or rewriting subject lines, validate that your emails are reaching the right people in the first place.

Suppression logic, domain filters, and contact allocation aren’t visible, but they shape everything downstream. As lists grow, these issues compound quietly until performance feels inexplicably broken.

If your list is growing and engagement isn’t—or results feel inconsistent without a clear reason—start with infrastructure. Fixing that changes what’s possible everywhere else.

Dealing with email deliverability issues that don’t respond to surface-level fixes?

Hypha focuses on the technical work that makes performance measurable again. Let’s talk about what’s actually happening inside your email program. Reach out to a Hypha expert, today.