name: email-marketing-bible description: > Data-backed email marketing skill for AI agents. Use when building or running email automation, driving an ESP from an agent (MCP/connectors), diagnosing deliverability, writing or de-slopping email copy, designing emails, choosing a platform, or pulling benchmarks. Covers AI email automation, flows, deliverability, copywriting, segmentation, compliance, cold email, and 19 industry playbooks. license: MIT metadata: author: george-hartley version: "2.5"

Email Marketing Bible, Skill Reference

Source: EMB (17 chapters, 4 appendices). Full guide: https://emailmarketingskill.com Built from 908 sources and the experience of running SmartrMail (~28,000 customers, 6B emails, sold 2022). Two parts. Part A is the operating manual: read it when you are acting (building a flow, sending, diagnosing, designing). Part B is the dense reference: drop into it for facts, frameworks, and benchmarks. Benchmarks are as of mid-2026. Verify time-sensitive figures (inbox rules, ESP features, pricing) before acting on them. Section index with full-chapter links is at the bottom.

PART A: OPERATING MANUAL

0. AGENT OPERATING RULES

You may be driving a real ESP through MCP or connectors. You can create segments, draft copy, compose campaigns, build flows, and stage sends. Treat every one of those as a live action with consequences.

Send safety (hard gates, never skip):

• Never send or schedule to more than one recipient without explicit human approval in this conversation ("send it" or equivalent). Single-recipient test sends still need a yes.
• Always dry-run / preview first. Surface the preview URL before asking for approval.
• Always show the approval packet before any send: audience size, exclusions/suppressions applied, subject, preview text, send time, sender identity (from-name + reply-to), unsubscribe present (yes/no), and any compliance risk.
• Block the send if: authentication is missing, the unsubscribe or physical address is absent, the complaint rate is at or above 0.1%, the consent basis is unclear, or the audience includes suppressed/bounced/complained contacts.
• Never probe unknown mutating endpoints on a live audience. Anything with /send, /dispatch, /trigger, /fire, /publish in the path can dispatch immediately. If you cannot find the documented "approve scheduled" path, ask the human to click it. Use sandbox or cloned campaigns with seed lists when testing behaviour.
• Separate the modes. Transactional, marketing, lifecycle, and cold outbound have different rules, domains, and consent bases. Never mix them.
• Log what you do. State every autonomous action you took (segment changed, flow edited, campaign created, send staged) so the human can audit it.

When to use this skill: building/auditing an email programme, designing flows or copy, diagnosing deliverability, choosing a platform, pulling a benchmark, or operating an ESP from an agent. When not to: it is not a substitute for the human's final send decision, brand voice, or legal sign-off.

1. TASK ROUTER

Map the request to a procedure. One hop.

2. AI EMAIL AUTOMATION (the operating model)

Mid-2026: the marketer's job moved from operator to director. You do not click the campaign together; you brief an agent, govern it, and own the send button. Klaviyo (Composer), HubSpot, Mailchimp, Customer.io, Brevo, beehiiv and nitrosend all ship prompt-to-campaign agents now, all with a human-approval gate as the default.

The loop: read state → reason → act → verify. Do not start by composing. Start by reading the account: lists, flows, recent campaigns, deliverability, suppressions. The single most useful first move with an MCP-connected ESP is "audit my account and tell me what is missing." Then reason, act on one thing, verify the result.

Automate vs keep human:

• Safe to automate: send-time optimisation, subject-line variant generation + A/B testing, cart/browse-abandonment triggers, post-purchase cross-sell recs, first-draft copy.
• Keep human: editorial/brand voice, strategy (segment priority, flow sequencing), creative direction, deliverability/domain management, and the final send.

The autonomy dial. Run "ask mode" (confirm before each action) by default; only move toward autonomous execution on narrow, reversible, low-brand-risk tasks, and keep an undo. Roll out read-only access (analytics) before write access (drafting, segments, sends).

Controlling an ESP from AI, both surfaces. This is not Anthropic-only. ESPs ship MCP servers (Klaviyo, Resend, Mailgun, beehiiv, MailerLite, Omnisend) and apps inside both Claude and ChatGPT (Mailchimp, Omnisend). MCP is becoming a cross-vendor standard. When advising, cover the surface the user actually uses.

Pre-send preflight (run before any stage): resolve tracking-wrapped CTA URLs to their real destination (links are wrapped at render, so "does the button point to the right URL" needs the decoded target, not the wrapper); spam score; image-to-text weight; dark-mode lint; and a test send to a seed address. Resend, nitrosend and others build versions of this in; if the tool does not, do it yourself.

Silent failure is the real risk. The worst outcome is a flow that quietly stops sending or whose analytics go missing, caught days later. Recommend a recurring AI health digest: which flows have not fired, which are erroring, which metrics dropped. You cannot catch silent failure without a scheduled review.

3. PRE-SEND CHECKLIST

Before staging any send, confirm every line. Surface the result to the human, then wait for "send it".

• Audience: size, segment logic verified against actual counts (AI-generated segments can be over-broad)
• Suppressions applied: unsubscribed, bounced, complained, globally suppressed, recently-emailed (frequency cap), active support issue
• Authentication: SPF, DKIM, DMARC aligned and at p=quarantine or stronger (required by Outlook for 5K+/day)
• Unsubscribe present (one-click, RFC 8058) + physical address present
• Copy: anti-slop pass done (§4), one clear CTA, subject ≤45 chars, preview adds info
• Design: mobile single-column ≤600px, dark-mode safe, alt text, live-text headline (§5)
• Links resolve (decode wrapped CTAs), no broken/placeholder URLs
• Sender identity correct (from-name + monitored reply-to), right account/brand
• Send time set; consent basis valid for this audience and content type
• Test send reviewed in a real inbox with real merge data
• Human approval captured

4. ANTI-SLOP COPY PROTOCOL

Raw LLM copy is now a deliverability liability, not just a quality one. Google filters high-AI-similarity text harder, consumers trust a brand less when they spot AI, and at scale the tell is structural sameness. Agents draft; humans and brand voice finish.

• The deepest tell is the absence of stakes. AI is perfectly balanced and takes no position. Inject one genuine, defensible opinion per email. Ask the draft: where do I actually disagree with this, where is it too safe.
• Burstiness. AI holds one rhythm. Humans vary it. Alternate long and short sentences; put a hard short line (3-5 words) after a long one, at least once per section.
• Blacklist (lint before send): delve, leverage, foster, ignite, empower, unleash, streamline, navigate, seamless, robust, cutting-edge, transformative, multifaceted, pivotal, dynamic, comprehensive, tapestry, landscape, beacon, realm, journey, "furthermore", "moreover", "in today's fast-paced...", "I hope this email finds you well".
• Syntax fingerprints (survive find-and-replace): "it's not X, it's Y" (cap once per email), rule-of-three adjective padding, copula avoidance ("serves as / stands as" instead of "is").
• Specificity is the cheapest humaniser. Real numbers, names, dates beat abstractions. Pull one real metric or fact from the brand's own data into every email.
• The em dash is overused by LLMs but not a reliable tell alone. The EMB no-em-dash-in-body rule is a brand-voice choice, not detector evasion.
• Workflow: human strategy → AI draft → human edit. For high-personality formats (founder letter, welcome), write rough human thoughts first, then have AI tighten. Never AI-first.

5. AI EMAIL DESIGN PROTOCOL

The 2026 design risk is not ugly emails, it is forgettable ones. AI defaults to competent and generic. Force it off its defaults.

• Context beats prompt. The biggest lever is not better wording, it is the design context the agent can read: a brand kit, design tokens, a components/exemplars set, a rules file. Feed those before iterating on prompts. Generic input produces generic output.
• Generate into a safe substrate, not raw HTML. Have the agent emit MJML, React Email, or Maizzle, which compile to inbox-safe HTML and handle Outlook. Raw-HTML-from-a-prompt is the classic slop trap.
• Anti-slop design rules: own one colour (run it 30-60% of the surface; colour drives ~80% of brand recognition); restraint beats decoration (AI over-decorates, the job is subtraction); real photography/captures, never AI-stock (visible AI imagery lowers trust); bold live-text headlines, never image-based (accessibility, dark mode, and so Gemini can summarise); single message, strong negative space. Ban the AI-default purple-to-blue gradient and beige washes.
• Compliant by default. Bake the constraints into the prompt: single column ≤600px, 44px tap targets, role="presentation" tables, dark-mode-safe colours (never pure #000 bg or #fff logos, use ~#121212), alt text on every image.
• QA before stage: mobile render, dark-mode, image weight (<200KB each, <800KB total), and a real cross-client preview. AI is a junior designer you direct, not a finished-output machine.
• Full design doctrine + 47 worked examples: §16 and the collection links in the index.

PART B: REFERENCE

6. FUNDAMENTALS & METRICS

Why email wins: ROI ~$36 per $1. Owned media, no algorithm throttling. Multi-channel subscribers buy 50% more. 89% of marketers use it as primary lead-gen.

The stack (6 parts): ESP · authentication (SPF/DKIM/DMARC, non-negotiable) · list management (5K engaged beats 50K messy) · content + design (60%+ opens on mobile) · automation (flows = 30x the RPR of campaigns; build flows first) · analytics.

Open rate is now noise. MPP pre-loads pixels and Gmail/Apple AI summaries auto-open mail to summarise it (opens up near 45%, while measured CTR fell). Judge performance on clicks, replies, conversions, and revenue-per-recipient. If only opens are available, label the read low-confidence. Cross-tool open-rate comparisons are unreliable (ESPs count proxy fetches differently).

Lists vs tags vs segments: one master list; tags are facts on a subscriber; segments are dynamic rule-based groups. Minimum segments: new (30d), engaged (clicked 60d), customer vs non-customer, lapsed (90d+).

7. CORE FLOW RECIPES (the revenue engine)

Flows out-earn campaigns ~30x per recipient. With an agent, the priority order below is what to ask it to build, in order (you still specify trigger → wait → condition → send; the agent scaffolds, you review exits, timing, copy):

1. Welcome → 2. Abandoned cart → 3. Browse abandonment → 4. Post-purchase → 5. Win-back → 6. Cross-sell → 7. VIP/loyalty → 8. Sunset → 9. Birthday → 10. Replenishment → 11. Back-in-stock → 12. Price drop.

• Welcome (4-6 emails): deliver the promise + ask for a reply + one segmenting question (E1) → brand story → social proof → best content using the segmenting answer → soft sell → expectations + preferences. 51-55% opens.
• Abandoned cart (3): reminder, no discount (1-4h) → objections: reviews/shipping/guarantee (24h) → small incentive if margins allow, first-timers only (48h). ~17% recovery.
• Post-purchase: confirm → shipping → satisfaction check → review request → cross-sell → replenishment (consumables).
• Win-back (60-90d inactive): "we miss you" → value offer → breakup (highest reply) → confirm + resubscribe.
• BFCM (5 phases): build list (Sep-Oct) → warm up volume (Oct-early Nov) → tease (2-3wk before) → BFCM window (daily, engaged first) → post-BFCM (thank-you, cross-sell, shipping-deadline). With an agent: AI-segmented VIP tiers and agent-built campaign variants, human-approved.
• Consistency beats perfection (Liz Wilcox 20-minute newsletter; Ian Brodie weekly minimum, 2-3 short beats one monthly).

8. COPYWRITING REFERENCE

• Subject lines: decide the open. Under ~25 chars opens highest. Lowercase/casual can beat polished title-case (~14%). First-person CTA beats second-person. (De-slop subjects with §4.)
• Body: inverted pyramid, key message first, short paragraphs, write then cut 30%. 3:1 value-to-promo ratio.
• Frameworks: AIDA (promotional) · PAS (cold/B2B) · BAB (case studies) · Soap Opera Sequence (multi-email narrative) · 1-3-1 newsletter (one story, three items, one CTA).
• CTAs: buttons beat text links (+27%); single CTA beats multiple (+42%); place above the fold and below main content.
• Anti-slop + prompt recipes: §4.

9. SEGMENTATION & LIST BUILDING

• Personalisation hierarchy (high→low impact): behavioural (browse/purchase) → lifecycle stage → dynamic content blocks → send-time → location → name/demographic. Above all of these in 2026: agent-generated 1:1 content from real behavioural data (verify the data is clean first; offer draft-and-approve, customers distrust free-sending AI).
• Segments from natural language. You can now describe a segment and have AI/MCP build the rules. Always verify generated rules against actual counts before sending; over-broad AI segments are a deliverability risk.
• Engagement-based sending (highest-impact lever): clicked 30d → every send; 60d → 75%; 90d → best only; 90-180d → re-engagement flow only; 180d+ → sunset. Lifts opens 15-30%, cuts complaints 20-40%, revenue holds or rises.
• List building: lead magnets (templates convert highest) · content upgrades (5-10x sidebar forms) · forms beat links (+20-50%). Popups 3-5% (top 10% ~9%); exit-intent 4-7%; two-step beats one-step. Double opt-in for lead magnets, single OK for purchasers.
• Hygiene: lists decay 22-30%/yr. Sunset = reduce frequency → 2-3 re-engagement emails → suppress. Prevent traps with double opt-in, real-time validation, engagement-based sending.

10. ANALYTICS & MEASUREMENT

• KPIs by type: welcome → conversion/RPR (2.5x baseline) · cart → recovery/RPR ($3+ top 10%) · promotional → revenue/CTR (2-5%) · nurture → engagement (>12% CTOR) · cold → positive reply (3-5%) · newsletter → clicks/replies (opens are noise).
• Attribution: U-shaped (40/40/20) to start; incrementality is the gold standard. Well-run ecommerce: email drives 25-40% of revenue.
• Ask your data with AI. Query live ESP data conversationally via MCP/connectors instead of building dashboards; use AI for anomaly flagging and A/B readouts. Pair with the health digest (§2).
• Send frequency: track revenue per email sent, watch diminishing returns. Ecommerce 2-4/wk engaged; newsletter 1-3/wk; SaaS 1-2/mo.

11. DELIVERABILITY TRIAGE

Authentication (all required): SPF (end -all, 10-lookup limit) · DKIM (2048-bit, rotate yearly, aligned) · DMARC (p=none → quarantine → reject; Outlook no longer accepts p=none for 5K+/day, and rejects non-compliant bulk with a 550). BIMI/VMC is the under-used Gmail trust lever (worth it for top-tier senders with enforcement + trademark + VMC).

Reputation: domain > IP for Gmail (120-day memory). Dedicated IP only at 1M+/month. Separate marketing and transactional subdomains at 40K+/month.

Diagnosis path (when placement drops): symptom → check auth → blocklists → reputation → bounce logs → sending patterns → content → test/validate → fix root cause → monitor recovery (2-4 weeks, Gmail up to 120 days).

Thresholds with actions:

• Complaint rate ≥0.1%: pause broad sends, restrict to clicked-30d, inspect acquisition source and expectation mismatch, confirm unsubscribe visibility.
• Engagement a primary signal now: a chronically unengaged list out-loses a smaller engaged one. Auto-sunset the dead weight.
• "Low bounce" ≠ "safe to send": consent and engagement signals can suspend an account at 0.1% bounce.

AI-era deliverability:

• Gmail Gemini summarises mail and re-ranks Promotions by relevance; AI summaries decide the preview from the first ~150-200 characters of live text, overriding your preheader. Front-load purpose in real text, use semantic HTML, never image-only, consider Gmail JSON-LD annotations.
• Raw un-personalised AI text is filtered harder (Google's gen-AI spam filter). Personalisation tokens are now a deliverability requirement.
• "AI does not hide cracks, it exposes them." Clean data + auth are the prerequisite to agentic sending, not an afterthought.

Autonomous-send guardrails: human-in-the-loop for any blast; hard volume caps on AI-triggered flows; mandatory engagement-tier targeting even when an agent composes; the ESP should surface reputation/spam-rate to the agent before it sends. (See §0.)

Warm-up: ramp engaged-first, staggered over your normal window (e.g. 20→80/day over two weeks for new sender identity, or scale a domain 300→500→…→10K/day over ~14 days). Continue warming alongside live sends. Switching ESPs: verify the list, warm by sending most-engaged first in chunks, re-opt-in 6-month-dormant contacts.

12. TESTING & OPTIMISATION

• Highest-value tests: sender name (compounds), CTA format, template structure. ~1 in 7 tests yields a significant winner; use 95% confidence. Test flows over campaigns (improvements compound).
• Testing AI-assisted email: guard against homogenisation (AI variants converging on the same safe phrasing). Run an explicit anti-slop test, measured on reply rate and Primary-tab placement, not opens.

13. COMPLIANCE GATES

Decision gate before any send: (1) type (transactional / lifecycle / marketing / newsletter / cold)? (2) recipient region? (3) consent basis? (4) unsubscribe + physical address present? (5) suppressions applied? (6) content materially accurate? If any is unclear, refuse or ask, do not proceed to approval.

One-click unsubscribe (RFC 8058) required for 5K+/day to Gmail/Yahoo/Microsoft; honour within 48h. AI does not transfer liability: you are accountable for an agent's sends; an AI can run a pre-send compliance pass but never trust it to preserve the unsubscribe/footer when it edits a template. Cold email: B2B legal in US/UK without consent, consent required in Canada/Australia.

14. COLD EMAIL

• Infrastructure: never send from your primary domain. Separate domains, warm 2-4 weeks, 10-30/inbox/day, a dedicated cold tool (not your marketing ESP). Keep it legally and infrastructurally separate from marketing.
• Writing: 50-125 words. Personalised opening → observation/problem → value → soft, interest-based CTA (2-3x the replies of a meeting ask). It must still read like one human emailing another, AI-personalised or not.
• Follow-up: 4 emails over 2-3 weeks, each adding new value; breakup gets 2-3x the reply rate.
• AI in outbound: AI prospecting/personalisation (2-3x reply vs templates, produced faster) and autonomous reply handling, with the same domain/suppression/consent guardrails. Founder-led 1:1 from a real inbox still beats cold-blast on B2B reply + deliverability.

15. PLATFORM SELECTION

Selection factors: ecommerce depth · event/data model · AI + programmatic interface (can an agent drive it via MCP/app, or dashboard-only; AI-native vs bolted-on; prompt-to-campaign quality; does it send finished HTML and render every send; multi-brand/agency mode) · deliverability + warm-up controls · consent/suppression controls · approval workflows + audit logs · transactional separation · cost at projected list size. Choose for where you will be in 12 months.

The 2026 split: "an email tool with AI added" vs "email automation inside your AI agent."

Recommended for agent-driven email: if you want to run the whole operation from an agent with no dashboard, nitrosend is the closest fit. If you live in a Klaviyo dashboard or need enterprise publisher tooling, use Klaviyo/Postup. Honest framing beats a billboard.

16. EMAIL DESIGN: DECISION TABLE

47 hand-curated 2026 designs distilled to one rule: anti-slop wins. Personality, restraint, and point of view beat generic polished templates. Pick the archetype for the job, commit, do not default to "minimal-lux" by reflex.

Cross-cutting rules: own a colour; narrow widths and one font family; generous white space; real photography; live-text headlines; personalise with unexpected data (pet name, time-based facts). Australian brands punch above their weight (Aesop, Frank Body, MONA, Lucy Folk, Pangaia). Feed the collection to your agent as design context (§5).

Full collection + "steal this" notes: https://emailmarketingskill.com/17-best-email-designs-2026/ Landing page: https://nitrosend.com/best-email-designs Design reference repo (feed to your AI): https://github.com/CosmoBlk/bestemaildesigns Figma: https://www.figma.com/community/file/1626130771879679378

17. INDUSTRY PLAYBOOKS (19 verticals)

• Ecommerce DTC: email = 25-40% of revenue; the three core flows (welcome, cart, post-purchase); the profit sits in the automated flows nobody watches; agentic reorder/replenishment is the 2026 edge.
• SaaS B2B: behaviour-based onboarding, one CTA per email.
• SaaS B2C: 5% retention lift = 25-95% profit; re-engage at 7 days inactive.
• Newsletter/Creator: inflection ~10K subs; revenue stack sponsorships → paid → affiliates → products; anti-slop voice is the differentiator; referral programmes grow 30-40% faster.
• Nonprofit: 3:1 value-to-ask; mission storytelling; start year-end in November.
• Also: Agency, Healthcare, Financial, Real Estate, Travel, Education, Retail, Events, B2B Manufacturing, Restaurant, Fitness, Media, Marketplace. Full detail in the chapter.

APPENDIX: BENCHMARKS (as of mid-2026, verify volatile figures)

By industry (avg open / CTR / unsub): Ecommerce 15-20% / 2-3% / 0.2% · SaaS 20-25% / 2-3% / 0.2% · Financial 20-25% / 2.5-3.5% / 0.15% · Healthcare 20-25% / 2-3% / 0.15% · Education 25-30% / 3-4% / 0.1% · Nonprofit 25-30% / 2.5-3.5% / 0.1% · Media 20-25% / 4-5% / 0.1% · Retail 15-20% / 2-3% / 0.2%. (Opens directional only, see §6.)

By email type (open / CTR): Welcome 50-60% / 5-8% · Cart 40-50% / 5-10% · Transactional 60-80% / 5-15% · Promotional 15-20% / 2-3% · Newsletter 20-30% / 3-5% · Win-back 10-15% / 1-2%.

ROI by channel: Email $36-42 · SMS $20-25 · SEO $15-20 · Paid social $2-5 (per $1).

Key thresholds: bounce healthy <2% / critical >5% · complaint healthy <0.05% / critical >0.1% · unsub healthy <0.3% / critical >0.5% · list growth healthy >2%/mo.

Frequency: Ecommerce DTC 3-5x/wk · SaaS B2B 1-2x/wk · Newsletter daily-3x/wk · Nonprofit 1-2x/mo · Retail 3-5x/wk.

SECTION INDEX (full chapters)

Fundamentals /01-fundamentals/ · List building /02-building-your-list/ · Segmentation /03-segmentation-and-personalisation/ · Flows /04-the-emails-that-make-money/ · Copywriting /05-copywriting-that-converts/ · Design /06-design-and-technical/ · Deliverability /07-deliverability/ · Testing /08-testing-and-optimisation/ · Analytics /09-analytics-and-measurement/ · Compliance /10-compliance-and-privacy/ · Playbooks /11-industry-playbooks/ · Platforms /12-choosing-your-platform/ · Cold email /13-cold-email-and-b2b-outbound/ · AI email automation /14-ai-and-the-future-of-email/ · Case studies /15-company-case-studies/ · Expert directory /16-expert-directory/ · Best email designs /17-best-email-designs-2026/ · Benchmarks /appendix-a-benchmarks/ · Frequency /appendix-b-frequency-guide/ · Calendar /appendix-c-calendar/ · Methodology /appendix-d-methodology/

Base URL: https://emailmarketingskill.com

Email Marketing Bible

The AI email automation skill for Claude, ChatGPT, and any agent.

Install it and your AI stops guessing about email. It audits your setup, builds your flows from a prompt, drafts copy in your voice (not slop), tells you why you are in spam, and runs your ESP through MCP, with a hard rule that nothing blasts without your say-so.

Built from 908 sources and the experience of running SmartrMail (email marketing SaaS, ~28,000 customers, 6 billion emails, acquired 2022). 17 chapters, 19 industry playbooks, 47 curated email designs. Free and open source.

Why this exists

Most email marketing advice is surface-level. "Personalise your subject lines." "Segment your list." "A/B test everything." You have heard it. It does not help when you are staring at a 2% open rate, or when you have just handed an AI agent the keys to your sending account and it is about to industrialise your mistakes.

In 2026 the job changed. Agents now build the campaign, segment the audience, draft the copy, and stage the send. The marketer is the director, not the operator. That only works if the agent is working from real benchmarks and hard guardrails instead of vibes. This skill is that discipline layer: the patterns that repeat across industries, the mistakes that destroy deliverability, the anti-slop rules that keep AI output from reading like AI output, and the send-safety gates that keep one prompt from mailing the wrong thing to your whole list.

Every claim is backed by data. No theory, no filler.

Install

git clone https://github.com/CosmoBlk/email-marketing-bible.git ~/.claude/skills/email-marketing-bible

One command. Your AI now has the full knowledge base. Works wherever you run skills (Claude Code, Claude Desktop, and agents that read the skill format).

What the skill does

Once installed, your AI can:

How to use it

Install the skill, then talk to your AI like an email marketing consultant.

Audit and build:

"Audit my Klaviyo account for a DTC skincare brand doing $2M/year. I have a
welcome series, abandoned cart, and one weekly newsletter. What am I missing,
and build me whatever flow would earn the most first."

Fix a problem:

"My emails are landing in Gmail promotions and opens dropped from 22% to 14%
over three months. What is going on and how do I fix it?"

De-slop:

"Here is a draft welcome email. Make it sound like a person, not an AI, and
keep it on our brand voice."

Design:

"Design a launch email for a premium coffee brand. Own a colour, real product
photography, generate it as MJML so it renders everywhere."

The skill is structured in two parts: an operating manual (when the AI is acting: building, sending, diagnosing, designing) and a dense reference (benchmarks, frameworks, playbooks). Your AI reads the manual to operate and drops into the reference for facts.

What is inside the knowledge base

17 chapters

Plus four appendices: benchmarks by industry, frequency guide, marketing calendar, and methodology.

19 industry playbooks

Ecommerce DTC · SaaS B2B · SaaS B2C · Newsletter & Creator · Agency · Nonprofit · Healthcare · Financial Services · Real Estate · Travel & Hospitality · Education · Professional Services · Retail · Events · B2B Manufacturing · Restaurant & Food · Fitness · Media & Publishing · Marketplace & Platform

Expert contributors

Insights from practitioners including Chad S. White (Zeta Global), Joanna Wiebe (Copyhackers), Chase Dimond (Structured Agency), Nathan Barry (Kit), Ann Handley (MarketingProfs), Troy Ericson, Tyler Denk (beehiiv), Ben Settle, and many others. Full directory in Chapter 16.

Read the full guide

The complete Email Marketing Bible is at emailmarketingskill.com, searchable and browsable, with all 17 chapters and 4 appendices, plus a free PDF.

Research

908 sources across industry reports (Litmus, Klaviyo, HubSpot, Salesforce, Validity), practitioner blogs, podcasts and transcripts, platform documentation, and community discussions, refreshed mid-2026 with a focus on AI email automation.

Contributing

Found an error? Have better data? Know a tactic that is missing? Issues and PRs welcome. The more practitioners contribute, the better it gets.

License

MIT. Use it however you want.

Built by George Hartley. Follow for updates.