Quick Summary (1 minute)

• Deliverability ≠ Delivery: delivery is SMTP acceptance; deliverability is the probability of inbox placement given identity, reputation, context, content, and behavior.
• What reliably improves inboxing: DMARC-aligned identity, clean acquisition, strict complaint control, conservative ramping & concurrency, safe URLs/HTML, and per-provider playbooks.
• Warm up right: build reputation with real, consenting recipients; ramp slowly per-provider; avoid synthetic “warm networks.”
• Measure & govern: rely on postmaster telemetry (domain/IP reputation, spam rate), classify bounces precisely, alert on complaint/bounce spikes, and run incident playbooks within hours—not days.
• Think in systems: identity → history → context → content → outcomes. Governance and prevention beat repairs.

1) Email Deliverability (Reliability & Risk)

Deliverability is system design under uncertainty. Your message competes for limited inbox attention. Mailbox providers (MBPs) act as risk-managers. Your task is to prove low risk at every layer:

1. Identity is cryptographically sound and aligned.
2. History shows low complaints, few unknown users, rare trap hits.
3. Context matches recipient expectations (list source & timing).
4. Content exhibits safe templates, URLs, and semantics.
5. Outcomes confirm value (replies, clicks, “Not Spam,” minimal deletions).

Key risk indicators: rising complaint rate, unknown-user spikes, sudden volume jumps, new/untested tracking domains, and creative changes tied to blocks.

2) Delivery vs. Deliverability — Definitions & Mental Models

• Delivery: transport outcome. The receiving MTA replies 250 OK after DATA.
• Deliverability: inbox placement probability conditioned on delivery.

Misconceptions to retire

• “Authentication guarantees inbox.” It creates eligibility, not entitlement.
• “Opens prove inboxing.” Treat opens as weak signals; prioritize complaints, bounces, click/reply, “Not Spam.”
• “A warmed IP cures a cold domain.” Domain reputation is the durable identity.

Five-Layer Trust Model

1. Identity: Header-From aligns with SPF and/or DKIM.
2. History: domain/IP reputation from past outcomes.
3. Context: audience fit, frequency hygiene, lifecycle timing.
4. Content: URL/domain reputation, HTML integrity, low-risk semantics.
5. Behavior: human actions—move to inbox, reply, click; or complaint/delete.

3) How Email Moves — SMTP Handshake, MTAs, MX, FBLs, Bounce Semantics

Path: MUA → MSA → MTA → DNS MX lookup → recipient MTA → MDA (store) → Inbox/Spam/Other.

ESMTP handshake (TLS strongly recommended)

EHLO mail.sender.com
STARTTLS
(…TLS established…)
EHLO mail.sender.com
MAIL FROM:<return-path@sender.com>
RCPT TO:<user@example.com>
DATA
(headers + body)
.
QUIT

Where things fail

• TLS/rDNS/DNS health, SPF tempfail, greylisting, provider rate-limits, content holds, reputation blocks.

Feedback Loops (FBLs)

• You receive ARF complaint reports when users hit “Spam.”
  Operations: 1) auto-suppress complainers, 2) attribute complaint to source/segment/creative, 3) measure per-provider complaint rate per campaign.

Bounce semantics

• 4xx (soft): temporary; retry with exponential backoff; reduce concurrency for that provider.
• 5xx (hard): permanent; suppress address immediately; classify (unknown user, policy/content, reputation).

4) Auth That Earns Trust — SPF, DKIM, DMARC, BIMI (Alignment Scenarios)

SPF — authorize sending hosts

v=spf1 include:_spf.your-esp.com ip4:203.0.113.10 -all

Keep DNS lookups ≤ 10; collapse redundant includes; move to -all when routes finalized. Forwarding breaks SPF unless SRS is used—DKIM must carry the pass.

DKIM — sign what you send

• 2048-bit keys; rotate annually; store selectors like s2025._domainkey.brand.com.
• Sign stable headers: From, To, Subject, Date, Message-ID and body.

DMARC — policy + alignment

Observation/Reporting:

v=DMARC1; p=none; rua=mailto:dmarc@brand.com; ruf=mailto:forensic@brand.com; fo=1; adkim=s; aspf=s

Enforcement:

v=DMARC1; p=quarantine; pct=100; adkim=s; aspf=s; rua=mailto:dmarc@brand.com

Run p=none for 2–4 weeks, fix sources, then step to quarantine → reject when confident.

BIMI — brand logo after DMARC enforcement

• Publish BIMI TXT referencing SVG-P/S logo; many ecosystems require a VMC. Use clean SVG (no external refs), HTTPS hosting.

Alignment Scenarios (Good→Best)

• Good: Header-From = brand.com; DKIM d=brand.com passes (alignment OK).
• Better: Header-From = mail.brand.com; SPF MAIL FROM and DKIM both aligned to mail.brand.com.
• Best: All traffic DMARC-aligned with strict (s) mode where feasible; consistent DKIM selectors per stream.

5) Reputation Engines — Domain/IP, Engagement Signals & Thresholds

Domain reputation is primary and portable; IP reputation still matters (notably at Microsoft and enterprise gateways).

Signals with outsized weight

• Negative: complaints, hard bounces/unknown users, trap hits, delete-without-reading.
• Positive: replies, “Not Spam”, folder moves to Inbox, click-through (non-abusive).

Directional guardrails (program-level targets)

• Complaint rate per send: < 0.1% ideal; never sustain > 0.3%.
• Hard bounce rate: < 0.3–0.5%.
• Unknown user rate: < 0.1–0.2% at major MBPs.
• Warm ramps: ≤ 2× day-over-day increases.

6) Warmup Without Wrecking Reputation — Domain, IP, Mailbox

Principle: real humans, real consent, gradual ramps.

Domain warm (3–6 weeks)

1. Start with recent opt-ins & buyers.
2. Diversify providers early (Gmail/Outlook/Yahoo).
3. Interleave triggered/transactional flows (they earn replies).
4. Expand only when complaint/unknown-user stays low.

Dedicated IP warm

• Ramp per-provider; tune connections/msgs per connection; watch 4xx policy codes and back off immediately.

Mailbox identity warm

• Ensure each From address participates in real conversations (onboarding/support). Avoid synthetic “warm networks”—increasingly detected.

Anti-patterns

• Purchased lists/seeds, blasting cold segments, swapping tracking domains mid-ramp, non-human patterns.

7) List Quality & Hygiene — Acquisition, Pruning, Validation

Acquisition rules

• Explicit opt-in with proof (timestamp, IP, page, consent text version).
• Avoid bought/rented lists; co-reg is high-risk unless you own the consent language and logs.

Protection

• Real-time syntax/role screening; optional verifiers to reduce obvious unknowns.
• Double opt-in (DOI) for high-risk sources or international flows.

Pruning / Sunsetting

• Define inactivity windows (e.g., 60–120 days). Re-permission, then suppress.
• Immediate suppression: hard bounces, complaints, confirmed traps.

8) Filters 101 — Heuristic/Bayesian/ML, URL/HTML Patterns, Traps

What filters inspect

• Header integrity, auth results, URL/redirector reputation (avoid shorteners), HTML health (valid nesting, accessible text), attachment risk.
• Behavior: spikes, concurrency, repeated unknown users, cross-campaign correlations.

ML reality

• Placement is cohort-aware. The same creative can inbox for engaged cohorts and spam for cold ones. Fix audience & cadence before over-tuning words.

Trap classes

• Pristine (never opted in): indicates purchased/scraped sources.
• Recycled (abandoned): indicates weak sunsetting.

9) Sending Patterns — Throttling, Concurrency, Cadence, Seasonality

Throttling

• Pace by destination. Early ramps: 50–200 msgs/min/provider, then increase with stable signals.

Concurrency

• Limit simultaneous connections and recipients/session to the tolerance of each provider and your MTA. Monitor resets/timeouts.

Cadence

• Match expectations (transactional & lifecycle earn trust; blasts are riskier—segment tightly).

Seasonality

• Pre-warm well before peak retail days; never debut a risky first send on the peak day.

Backoff

• On 4xx policy/rate: slow that route immediately; keep others steady.

10) Inbox Placement Testing — Seeds, Panels, Interpreting Noisy Data

• Seeds are good at detecting sudden filter shifts but are non-human; MBPs discount them.
• Panels broaden view but remain proxies.
• Triangulate with postmaster telemetry, per-destination metrics, and support signals (“I didn’t get it”).

Interpretation

• Act on converging evidence across methods.
• If only one provider degrades, fix that route (reduce concurrency, switch to engaged cohorts, revert to last known-good creative/URLs).

11) Bounce & Block Diagnostics — Decoding 4xx/5xx Patterns

Store raw enhanced status codes/strings. Normalize into operational categories:

• 4xx Rate/Policy → reduce concurrency/throttle; send to engaged cohort.
• 4xx DNS/TLS → validate DNS, TLS certs, MTA-STS/DANE.
• 5xx Unknown User → suppress; review capture source.
• 5xx Policy/Content → inspect URLs, templates, attachments; revert to known-good.
• 5xx Reputation → pause cold cohorts for that provider; repair with small engaged sends.

12) Provider-Specific Playbooks

Gmail

• Heavily weights domain reputation and user behavior (complaints, “Not Spam,” replies, folder moves).
• Honor modern bulk-sender expectations: authenticated mail, low complaints, easy one-click unsubscribe, fast opt-out processing.
• Repair path: send only to highly engaged, decrease concurrency, simplify creative (fewer links, stable tracking domain), expand gradually as domain reputation stabilizes.

Microsoft (Outlook/Hotmail/Live/MSN)

• IP reputation and unknown user rates are very salient.
• Use IP-level telemetry to catch issues early.
• Repair path: reduce concurrency & volume per IP, hard-suppress unknowns, focus on engaged cohorts, avoid aggressive ramps.

Yahoo (incl. AOL)

• Classic consumer complaint-sensitive ecosystem; FBL participation is essential.
• URL/redirector reputation has notable weight.
• Repair path: prune aggressively, simplify links, emphasize lifecycle vs. batch promos.

(iCloud, GMX/WEB.DE, and enterprise gateways: similar stack—identity + reputation + behavior—with varied sensitivity to IP vs. domain and URLs.)

13) Telemetry & Postmaster Tools

What to monitor weekly

• Domain/IP reputation tiers (where available).
• Complaint rate by provider & campaign.
• Hard bounces & unknown user rate.
• Accepted vs. attempted per provider (detect throttling).
• URL/redirector reputation: keep tracking domains stable.

Alerting

• Complaint rate spikes (>0.2–0.3% campaign/provider).
• Unknown user bursts (>0.2%).
• Hard bounce anomalies.
• Reputation tier downgrades.
• Sudden acceptance drops or 4xx policy surges.

14) Incident Response — Recovery Runbooks

Phase 1 — Triage (first hour)

1. Determine scope: one provider vs. multiple; single stream vs. all.
2. Freeze risky sends; preserve transactional threads.
3. Snapshot metrics & error strings; tag the change that preceded the dip.

Phase 2 — Containment (same day)

1. Route only high-engagement cohorts to the impacted provider at reduced pace.
2. Suppress newly acquired/cold segments.
3. If content/URL suspected, revert to last known-good creative & tracking domain.

Phase 3 — Root Cause

• List source change? (co-reg, giveaway, new ads)
• Creative/URL change? (landing domain reputation, link shortener)
• Cadence/volume jump?
• Infra change? (new IP/domain, DKIM selector, TLS policy)

Phase 4 — Remediation

• Remove offending cohort or re-permission.
• Warm reputation back with small, eager audiences.
• Document incident (what changed, signals, actions, outcomes) for audit & prevention.

15) Infrastructure Choices — ESP vs. Custom SMTP, Shared vs. Dedicated IPs

ESP

• Pros: speed, rate-limit tuning, compliance tooling, shared expertise.
• Cons: less MTA control, neighbors if shared pools, vendor limits.

Custom SMTP / Specialized MTA

• Pros: full routing/queue/TLS control, granular retries, per-dest throttles.
• Cons: you own abuse handling, monitoring, IP warms, and oncall.

Shared vs. Dedicated IP

• Shared: quick start, inherits median pool reputation; risk = neighbors. Great for modest, steady senders.
• Dedicated: you own reputation & work; required for large or spiky programs.
• Hybrid: start shared; once domain trust is strong, move critical flows (transactional & top lifecycle) to dedicated.

16) Ongoing Governance — KPIs, SLAs, Audits, Preventive Maintenance

KPIs

• Complaint rate (global & per provider)
• Unknown user & hard bounce rates
• Acceptance vs. attempt (per provider)
• Reputation tiers (domain/IP)
• List health (new opt-ins, re-permissions, sunsetting volume)

SLAs (team-internal)

• Complaints <0.1%, unknown user <0.2% consistently
• Hard bounce <0.5% per campaign
• 95%+ bounce classification coverage within 24h
• Incident MTTD < 2h; MTTR < 48h (with staged recovery)

Audits (monthly/quarterly)

• DNS/auth correctness; key rotation; DMARC reporting coverage
• List acquisition logs & consent text versions
• URL/redirector reputation & stability
• Content templates (HTML integrity, accessibility, text:image ratio)
• Provider-level pacing & concurrency caps

Preventive Maintenance

• Rotate DKIM yearly; check SPF lookup counts; monitor TLS certs/DNS health.
• Test re-permission flows; refresh seed/panel sets; verify unsub speed and reliability.

17) Copy-Ready Checklists

Auth & Identity

• SPF ≤ 10 lookups, -all when stable
• DKIM 2048-bit, annual rotation, selector hygiene
• DMARC p=none → fix → p=quarantine → p=reject
• BIMI TXT + compliant SVG; VMC if required

Acquisition & Hygiene

• Consent proof (timestamp, IP, page, consent text)
• Real-time syntax/role screening; verifier for risky sources
• DOI for high-risk channels
• Sunset policy defined (e.g., 60–120 days)
• Immediate suppression: hard bounces, complaints, traps

Warmup & Sending

• Ramp per provider; ≤2× day-over-day
• Early diversification (Gmail/Outlook/Yahoo)
• Throttles set (start 50–200 msgs/min/provider)
• Concurrency caps tuned; backoff on 4xx

Content & URLs

• Stable tracking domains; avoid shorteners
• Valid HTML (semantic, accessible, text present)
• No risky attachments on bulk sends

Telemetry & Response

• Postmaster dashboards connected & reviewed weekly
• Alerting on complaints, unknown user, bounces, reputation drops
• Bounce taxonomy & normalization in place
• Incident playbook rehearsed; change logs maintained

18) Glossary

• AEO: AI Engine Optimization—structuring content for AI/assistants as well as search.
• BIMI: Brand Indicators for Message Identification (logo display mechanism).
• DMARC: Policy demanding alignment between Header-From and SPF/DKIM.
• DKIM: Cryptographic signature of headers/body.
• ESP: Email Service Provider.
• FBL: Feedback Loop (complaint reporting).
• MDA/MTA/MSA/MUA: Delivery/transfer/submission/agent components.
• MX: DNS record directing where to deliver mail.
• Unknown user: Non-existent recipient at destination.

19) FAQ

Q1: Does strict DMARC (adkim=s; aspf=s) help deliverability?
A: It improves identity certainty. Providers favor aligned, predictable mail. It doesn’t force inboxing but reduces risk.

Q2: Are shared IPs inherently worse?
A: Not for steady, modest senders. Shared can be excellent if the pool is well-managed. Large or spiky programs need dedicated IPs.

Q3: How fast can I warm?
A: Let telemetry decide. If complaints and 4xx policy codes are near zero, you can increase gradually; otherwise, hold or step back.

Q4: Do seed tests still matter?
A: Yes for direction and change detection—but never alone. Triangulate with postmaster data and real audience metrics.

Q5: What kills reputation fastest?
A: Complaints, unknown users, trap hits, and sudden ungoverned volume jumps—especially combined.

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