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Marketing & CMO AI curriculum — GEO, SEO, and brand-safe generative ops▌

This is a closed curriculum: fixed learning sequence, timeboxed sessions, and named deliverables (briefs, scorecards, checklists)—not a brainstorm. Marketing and growth leaders align brand governance with generative AI in organic and paid channels, including how AI search engines cite sources (GEO) and how traditional SEO still governs crawl and indexation. Typical runtime: three to four facilitated modules (in-person or virtual), each ending with a short knowledge check mapped to Bloom levels. Content follows enterprise B2B patterns: structured pages, FAQ blocks with JSON-LD where appropriate, and quantified claims only when your data supports them.

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instructional design: bloom’s taxonomy + measurable outcomes

Every module maps to explicit learning outcomes—not open-ended discussion without deliverables. We sequence along Bloom’s taxonomy (remember → understand → apply → analyze → evaluate → create): definitions and guardrails first, then applied exercises, then measurement and approvals. Facilitators run short checks for understanding after each block (2026 materials).

For organic and generative-engine visibility (GEO), we mirror patterns associated with stronger AI-search citation: answer-first sections, statistics where available, authoritative tone, clear H1–H3 structure, comparison tables when they reduce ambiguity, and FAQ blocks intended to pair with FAQPage JSON-LD. Teams produce briefs, scorecards, and checklists—not a generic “AI creativity” workshop.

Marketing track emphasis (on top of the standard Bloom sequence): Module 1 locks vocabulary and approvals; Module 2 applies GEO/SEO mechanics to real URLs and SERP features; Module 3 runs the creative intake-to-publish pipeline with legal/comms checkpoints; Module 4 ties spend and content decisions to measurement—not vanity metrics.

program objectives

  • (Remember / Understand) Define GEO vs. traditional SEO, AI Overview/SERP feature types, and brand-voice guardrails for generative assets used in public channels.
  • (Understand / Apply) Produce a one-page “GEO content brief” per priority URL: primary intent, answer-first outline, FAQ candidates, and schema intent (WebPage vs FAQPage vs Article).
  • (Apply) Operate a documented creative pipeline from brief → draft → brand/legal → localization → publish, with RACI and version control for AI-assisted copy and image variants.
  • (Analyze) Audit landing pages and blog posts for heading hierarchy, internal links, statistics placement, and citation-style references aligned with AI-search citation behavior (no keyword stuffing).
  • (Evaluate) Compare incrementality design for paid and lifecycle tests versus pre/post-only readouts; define kill criteria for AI pilots in marketing.
  • (Create) Consolidate outputs into a 30/60/90 plan pairing explainx.ai courses (e.g. ChatGPT SEO, digital marketing automation) with internal owners and office-hour cadence.

how we deliver

  1. 1

    Discovery call & problem framing

    We align on sponsors, success metrics, and constraints (2026 tool landscape, data rules, procurement gates) before anything is scheduled company-wide.

  2. 2

    Stakeholder interviews & day-in-the-life context

    Short conversations with practitioners (not only leadership) so scenarios reflect real workflows—not generic slide demos.

  3. 3

    Curriculum design & artifacts

    Modular agenda, exercise scripts, evaluation rubrics, and governance checkpoints matched to your vocabulary (banking, FMCG, engineering, etc.).

  4. 4

    Engaged, hands-on delivery

    Facilitation-led sessions with live exercises, breakout prompts, and documented failure modes—minimum passive lecture time.

  5. 5

    Post-session support: documentation & next steps

    Written recap, pilot backlog, links to explainx.ai courses for scaled upskilling, and optional office hours so momentum doesn’t stop at the workshop.

modules

Module 1 — Governance & vocabulary (Remember → Understand)

Shared definitions for CMO, brand, performance, legal, and agency partners before any tool rollout—so every later exercise uses the same vocabulary.

session outline

  • Bloom orientation for this program: how each module escalates cognitive load and what “done” looks like.
  • Brand voice matrix: allowed tones, forbidden claims categories, markets/languages, and when human approval is mandatory vs. AI-first draft.
  • Data rules: PII in prompts, customer lists in agents, retention of generated assets, and audit trail expectations for regulated industries.
  • RACI for generative assets across social, lifecycle email, paid landing pages, and partner co-marketing.
  • 90-minute checkpoint: glossary quiz + scenario cards (approve / revise / escalate) with named roles.

labs

  • Fill a live RACI for one real campaign in the room (no hypothetical startup).
  • Red-team three AI-generated headlines against your brand matrix.

beyond-catalog topics (custom)

  • Influencer and UGC workflows when AI drafts captions or scripts at scale—disclosure and territory nuances (structure only; legal signoff stays with client counsel).
  • Regional SEO nuance when HQ and local sites both publish (hreflang intent, duplicate-content checks).

Module 2 — SEO foundations & GEO / AI-search visibility (Understand → Apply → Analyze)

Technical and on-page SEO essentials plus GEO: structuring content so traditional engines and AI answer engines can extract authoritative answers—without gimmicks.

session outline

  • Search intent mapping: informational vs commercial vs transactional; how that maps to page types you already own.
  • On-page checklist: title/H1 discipline, meta descriptions, heading depth, internal link hubs, image alt patterns, Core Web Vitals talking points for dev handoffs.
  • GEO pattern set (aligned to common AI-citation research): answer-first ledes, extractable statistics, quotations with attribution, comparison tables, and topic breadth vs. thin pages.
  • Structured data selection: when FAQPage, Article, Course, or Organization JSON-LD adds clarity—validator habits (Rich Results / schema.org).
  • Competitive excerpt review: screenshot SERP + AI-summary panels for 2 competitor URLs; identify gaps your properties can close.

labs

  • Build a GEO content brief for one priority URL: headings, FAQ list, stat slots, internal/outbound link plan.
  • Pair edit of a live draft to add answer-first structure + one comparison table without stuffing keywords.

beyond-catalog topics (custom)

  • Editorial calendar tie-in: pillar/cluster models and how generative drafts propagate safely through localization.
  • Crawl budget and indexation discussion for large catalogs (e-commerce / marketplaces) at high level—engage SEO lead + engineering when invited.

Module 3 — Creative & lifecycle ops at scale (Apply → Create)

Run the production line: creative intake, generative assistance, legal/brand approval, localization, and publication with measurement hooks.

session outline

  • Intake template: audience, offer, proof points, proof sources, CTA, localization matrix, asset sizes.
  • Prompt and agent boundaries: where retrieval vs. pure generation is allowed; golden-set checks before wider rollout.
  • Rights: stock, talent, music, influencer contracts, and AI disclosure obligations by channel.
  • Lifecycle choreography: email vs. paid vs. organic sequencing with frequency caps and fatigue metrics.
  • Handoff package to analytics: UTM discipline, conversion definitions, and holdout design placeholders.

labs

  • End-to-end desk exercise: one net-new brief → draft → revision log → approval stamps (role-played).
  • Localization punch list: idioms, regulated claims, and forbidden superlatives by region.

beyond-catalog topics (custom)

  • Affiliate and partner co-brand assets when AI speeds variant volume—contractual labeling and review lanes.
  • Crisis workflow for off-brand generative output detected in the wild (takedown + root cause).

Module 4 — Measurement, incrementality, and pilot governance (Analyze → Evaluate)

Connect AI-assisted marketing work to P&L-adjacent metrics and staged investment—kill criteria included.

session outline

  • Marketing mix and incrementality vocabulary aligned with finance: geo tests, causal lift vs. correlation.
  • Pilot charter template for AI tools: hypothesis, baseline window, success metrics, guardrails, rollback triggers.
  • Vendor evaluation scorecard for generative vendors and agencies (data handling, SLA, model disclosure, indemnities—discussion framework, not legal advice).
  • Scorecard review for active pilots using your own numbers where available; otherwise teach with anonymized benchmarks.
  • Capstone: 30/60/90 plan with owners, course assignments on explainx.ai, and office-hour cadence.

labs

  • Draft a pilot charter for one real use case with explicit kill criteria.
  • Executive readout template (1 page) connecting program outputs to QBR metrics sponsors already track.

beyond-catalog topics (custom)

  • Board/regulator-ready narrative for AI in customer-facing copy—what to disclose vs. what stays internal.
  • Integration hooks to DAM, CMP, and consent tools when generative assets multiply.

quick contact

Scope or pilot this curriculum

Share sponsor, headcount, and cities — we reply with timing and options. Rough budget helps us match the right depth.

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faq

Is this curriculum generic prompt training?

No. It is a fixed multi-module sequence with Bloom-aligned outcomes, knowledge checks, and concrete artifacts (briefs, RACI, GEO outlines, pilot charters). Prompt patterns appear only where they support audited workflows.

How does GEO differ from classic SEO for our marketing team?

Classic SEO focuses on crawl, index, ranking, and CTR from traditional results pages. GEO (generative-engine optimization) focuses on how AI answer engines extract, summarize, and cite sources—so content needs clear structure, authoritative statements, statistics where valid, and FAQ/schema alignment. This curriculum trains both, with exercises on your real URLs.

Will we implement JSON-LD in the workshop?

We cover selection and validation patterns (FAQPage, Article, etc.) and how to brief engineering—not live production deploys unless your team schedules separate technical slots. Validation via Rich Results Test / schema.org is part of the checklist.

How do brand and performance marketers stay aligned?

Module 1 establishes shared RACI and approval gates; Module 3 runs an end-to-end creative exercise so channel conflicts surface in-room with facilitation—not as surprises in launch week.

What proof points do you use in facilitation?

We prefer your internal numbers for pilots. Where external context helps, we use anonymized benchmarks and well-sourced industry patterns—never fabricated statistics. That matches GEO guidance (credible, quantified claims) without overclaiming.

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