Email deliverability: 12-point fix for dying sender reputation

Deliverabilitydrift is silent and deadly. By the time you notice, you're already in spam. Here is the recovery plan.

1. Set up SPF, DKIM, DMARC

All three are table stakes now. Check with MXToolbox. Missing DMARC = guaranteed spam folder with Gmail and Yahoo post-Feb 2024.

2. Use dedicated sending domain

Send from a subdomain (e.g., email.growwithba.com) not your main domain. Protects main domain reputation.

3. Warm up new domains gradually

Start at 50 sends per day, double weekly. Full volume only after 4-6 weeks. Jumping straight to 10K = spam folder.

4. Remove inactive subscribers

Anyone who hasn't opened in 90+ days = deliverabilitypoison. Run re-engagement sequence, then suppress.

5. Double opt-in

Increases list quality 30-50%. Lower volume, higher engagement.

6. Send consistent volume

Spiky sending (0 for weeks, then 100K at once) flags spam filters. Keep daily volume within 2x of average. (See Klaviyo email marketing guidefor the official documentation.)

7. Monitor bounce rate

Over 2% bounce rate= reputation damage. Clean list with BriteVerify or ZeroBounce before sending.

8. Watch complaint rate

Over 0.1% complaint rate (1 per 1000) = blacklisted. Make unsubscribe obvious. Reduce send frequency if creeping up.

9. Segment by engagement

Send more to 30-day openers, less to 90-day non-openers. Protects sender reputation.

10. Avoid spam triggers in content

ALL CAPS, excessive punctuation, "FREE!!!", image-only emails = spam signals. Balance text and images.

11. Check postmaster tools

Google Postmaster Tools + Microsoft SNDS give free insight into your sender reputation. Related: cro.

12. Pay attention to deliverability metrics (not open rate)

Post-MPP, open rateis unreliable. Focus on: inbox placement rate, click rate, and list growth.

Frequently asked questions

Is this approach right for early-stage companies?

Most frameworks in this space assume a certain level of operational maturity, dedicated team members, established measurement infrastructure, some history of experimentation to build on. Pre-seed and seed-stage companies often lack these prerequisites and need a lighter-weight adaptation. For brands doing under $3M in annual revenue, focus on three or four of the principles that matter most for your specific business model rather than trying to implement the full framework at once. Rigor matters more than coverage at this stage.

How does this work for B2B versus B2C businesses?

The underlying principles around email deliverabilityfix apply across both contexts, but execution differs meaningfully. B2B email typically has longer sales cycles, multiple stakeholders per deal, and consideration periods measured in months rather than minutes. Measurement frameworks need longer windows. Attributionbecomes more complex. The same core strategic logic applies, but the tactical implementation looks different. We've worked extensively in both contexts and can flex the approach accordingly.

What changes when we integrate this with existing systems?

Every implementation requires integration work, systems don't exist in isolation. Analytics platforms, CRM, email systems, ad accounts, BI tooling all need to talk to each other for this to work at scale. Plan for 2-4 weeks of integration work at the start of any implementation. Shortcutting this phase creates data quality issues that compound and undermine the entire program over 6-12 months. We've seen teams skip integration work to move faster, only to spend 6 months later reconciling measurement discrepancies that could have been prevented upfront.

When should we reconsider the approach?

Every 6 months, run a structured review against the principles outlined here. Ask whether the market has shifted meaningfully, whether your business model has evolved, whether competitive dynamics have changed. Frameworks should evolve with context. A rigid commitment to any specific approach, including ours, eventually becomes the problem rather than the solution. The teams that outperform long-term are the ones that update their operating model based on evidence, not the ones that defend past decisions.