*Changes may apply
AI Marketing Foundations, Prompting & Agentic Execution
- The AI-native marketer and marketing fundamentals: from channel manager to architect of end-to-end workflows connecting data, media, content, and product; full-funnel demand and pipeline thinking; and strategic coordination with R&D, finance, HR, and other business functions.
- AI types and Prompt Engineering: applying LLMs and Agentic AI through professional prompting frameworks, System Instructions, context design, and a consistent brand voice.
- No-code AI agents and Vibe Coding: building personal marketing assistants connected to Google workflows and deploying a live landing page or mini-application with Google Gemini and Google AI Studio.
- The agentic organization and governance: the five pillars of business model, operating model, governance, workforce, and technology and data, with Human-in-the-Loop oversight.
ICP, Market Intelligence, AI Content Strategy & Hyper-Personalization at Scale
- MaAI-powered audience and market research: defining ICPs, segments, and opportunity spaces; identifying customer pain points, purchase barriers, emerging needs, and live trends across search, social, reviews, G2/Capterra, and industry reports.
- Content systems and the creative factory: turning topic clusters, content gaps, audience intents, and research insights into hooks, marketing copy, product imagery, content variants, and a monthly editorial calendar.
- Hyper-personalization and value-based content: building AI-assisted content variants that support demand capture, creation, retention, and measurable outcomes – rather than vanity metrics.
Performance Marketing I: Search, Performance & App Economy
- Google Ads ecosystem: Search, Performance Max, Demand Gen, YouTube, and display, with a focus on intent capture and AI-driven automation.
- AI-powered performance optimization: smart bidding, AI Max for Search, asset generation in Performance Max, and event-based optimization for downstream actions.
- App economy and growth funnel: mobile economics, install and engagement campaigns, from impression to install, store presence, deep linking, ASO (optimization) App Store and Google Play.
- Mobile attribution and measurement: install vs. in-app events, last-click vs. multi-touch attribution, Self-Reporting Networks, SRNs, Mobile Measurement Partners, privacy constraints.
- Onboarding, monetization, and orchestration: activation psychology, friction reduction, IAA, IAP, subscriptions, off-app monetization, LTV, ROAS, and AI-agent coordination across push, in-app messages, email, SMS, web, and ad retargeting.
- Agentic campaign management: AI agents for real-time auditing, anomaly detection, and optimization recommendations, with human control over budgets, brand decisions, and priorities.
Performance Marketing II: Meta AI, Paid Social, B2B Platforms & Creative Systems
- Meta AI delivery and audiences: Advantage+ Shopping Campaigns, signal feeding, Custom Audiences, Lookalikes, CRM-based audiences, remarketing, and the Andromeda and GEM algorithms.
- Measurement and full-funnel portfolios: Meta Pixel, Events Manager, Meta Business Suite, event quality, performance metrics, cold and warm audiences, acquisition, remarketing, budget allocation, and campaign optimization.
- Platform selection and operating model: Meta Ads Manager account hierarchy, Learning Phase logic, Campaign Manager for B2C, B2B, and mobile-first experiences.
- Synthetic audience and digital-twin A/B testing: evaluating creative with AI-generated personas before committing media budgets.
- AI creative systems: modular concepts for feeds, Stories, Reels, and short-form video; UGC and AI co-creation for scripts, storyboards, and variants; brand-consistent generative media; and Creative Fatigue management.
SEO, GEO & Answer-Engine Optimization in the LLM Era
- SEO and content discovery foundations: crawlability, site architecture, Core Web Vitals, structured data, topic clusters, intent mapping, and authority signals.
- Generative Engine Optimization, GEO: entity-based optimization, llms.txt, and direct-answer patterns for AI Overviews, ChatGPT Search, Perplexity, Claude, and Gemini.
- Agentic SEO and GEO workflows: using AI agents to automate content audits, optimization opportunities, topic and entity analysis, and performance monitoring.
B2B AI-First Playbooks: LinkedIn, Podcasts, Thought Leadership & Executive Presence
- B2B oriented platforms and LinkedIn: demand creation, account targeting, buying committees, company pages, personal brands, employee advocacy, and pipeline-focused content.
- Thought leadership, podcasts, and executive presence: building audio, video, and written content streams that preserve the executive’s voice and uncopiable lived experience, based on the Joaquin Cuenca Abela and Freepik thesis.
- AI-assisted production and distribution: ideation, drafting, scripting, show notes, clips, repurposing, and multi-channel distribution while retaining authentic human expertise.
- Social B2B: TikTok, Instagram and Facebook usages and best practices for B2B campaigns, best practices and case studies.
Marketing Operations, Lifecycle, CRM, CRO & Agentic Automation
- Marketing Operations and lifecycle: the Revenue Operations mindset across Marketing, Sales, and Customer Success; acquisition, onboarding, activation, adoption, monetization, retention, expansion, and stage-specific KPIs.
- CRM architecture and Sales alignment: objects, events, scoring, segments, triggers, MQLs, SALs, SQLs, routing, ownership, SLAs, pipeline governance, and dashboards across HubSpot, Salesforce Marketing Cloud, and Marketo.
- The agentic marketing orchestrator: how non-technical marketers managing agent fleets, designing an AI-powered B2B SaaS lifecycle engine that connects CRM, automation, Sales handoff, and customer success metrics.
- CRO as growth engine – AI frameworks & processes: continuous experimentation across marketing, product, and business; evidence-based hypotheses, prioritization, common pitfalls, measurement, A/B and multivariate testing, and multi-armed bandits.
- AI-powered CRO workflows and application: AI supports customer research, UX analysis, conversion copywriting, hypothesis generation, experiment design, variant development, and on-page personalization across landing, pricing, and product pages.
Data, Analytics, Attribution & AI Co-Analysts
- AI-powered measurement workflow: from strategy to measurement planning, GTM implementation, GA4 analysis, AI-assisted coding and interpretation with Gemini, and human-validated marketing decisions.
- Predictive analytics and AI as a co-analyst: predicting churn and upsell propensity, scoring accounts, detecting anomalies, generating hypotheses and narratives, and automating executive briefings.
- Data governance and quality: confidence thresholds, source attribution, reliable signals, and human validation before insights influence spending or brand decisions.
- Attribution and Marketing Mix Modelling: last-click, first-click, linear, position-based, time-decay, Data-Driven Attribution, DDA, and the return of MMM.
Capstone Presentations, Industry Critique & Career Activation
- Capstone and career activation: teams present the business context, AI-first marketing architecture, customer journeys, media, and measurement to an industry panel, then translate the work into portfolio assets, target role profiles, and a 90-day learning plan.