Mastering AI-Powered Marketing Automation for High-Growth Campaigns
You're under pressure. Leads are drying up. Your campaigns aren't scaling. And while competitors leverage AI to personalise at scale, optimise budgets in real time, and outpace growth, you're stuck manually tweaking workflows and guessing at what works. Every wasted dollar on underperforming ads, every hour lost to repetitive tasks, every missed conversion window cuts into your credibility-and your career. The clock is ticking. But here's the truth: Mastering AI-Powered Marketing Automation for High-Growth Campaigns is not just another course. It's your exact blueprint to transform from reactive executor to strategic architect of self-optimising, high-velocity marketing systems. This program delivers the precise framework used by top-performing marketers at Fortune 500s and hyper-growth startups to launch AI-driven campaigns that convert at 3x industry averages. One student, Priya N., Marketing Director at a SaaS scale-up, applied Module 4 to redesign her email nurture flow. Within 11 days, open rates jumped 68%, and sales-qualified leads increased by 41%, all with no additional ad spend. Imagine walking into your next executive meeting with a documented AI automation strategy that reduces CAC by 30%, increases LTV by 50%, and demonstrates measurable ROI-all backed by real campaign data you built in this course. No fluff. No theory. Just battle-tested systems that scale. You will go from overwhelmed and uncertain to fully in control-equipped with the tools, frameworks, and certification to lead AI-powered marketing with authority. You’ll create board-ready campaign blueprints, automate lead-to-revenue pipelines, and future-proof your skillset in one focused 30-day execution plan. You’re not just learning automation. You’re mastering the competitive edge that top employers and investors now demand. Here’s how this course is structured to help you get there.Course Format & Delivery Details Self-Paced. On-Demand. Built for Real Professionals.
This is a fully self-paced, on-demand program. Enrol once, and gain instant access to all course materials. There are no fixed dates, no time zones to adjust to, and no deadlines-just a flexible, professional-grade curriculum designed around your schedule. Most learners complete the core modules in 30 days while applying each concept directly to their current campaigns. Many report seeing measurable improvements in campaign efficiency and performance within the first two weeks. The fastest-those with existing automation experience-apply the AI integration frameworks and see results in under 10 days. Lifetime Access. Continuous Updates. Zero Extra Cost.
Enrolment includes full lifetime access to all course content. As AI platforms evolve and new tools emerge, we update the curriculum regularly. You’ll receive all future upgrades automatically, at no additional charge. This isn’t a time-limited course-it’s a permanent, up-to-date asset in your professional toolkit. Access is available 24/7 from any device, anywhere in the world. The platform is fully mobile-optimised, so you can study during commutes, between meetings, or from your tablet at home-no software downloads or installations required. Expert-Led Guidance with Direct Support
You’re not learning in isolation. Throughout the program, you’ll have direct access to our team of certified AI marketing strategists. Submit your campaign drafts, automation logic flows, or personalisation frameworks for expert feedback. Our support team responds to inquiries within 24 business hours, ensuring you stay on track and build with confidence. Receive a Globally Recognised Certificate of Completion
Upon finishing the course requirements, you will earn a Certificate of Completion issued by The Art of Service. This credential is recognised by HR departments, tech leaders, and hiring managers across 94 countries. It validates your mastery of AI-powered marketing automation and signals your ability to design high-growth campaigns with measurable ROI. Transparent Pricing. No Hidden Fees. Full Risk Reversal.
The price covers everything. There are no hidden fees, no upsells, and no additional charges. Payment is accepted via Visa, Mastercard, and PayPal-secure and straightforward. If you complete the course and don’t believe it delivered exceptional value, we offer a full satisfaction guarantee. Submit your completed work, and if you’re not 100% convinced of its professional impact, you’ll be refunded-no questions asked. Your investment is 100% protected. Immediate Confirmation. Secure Access. Zero Wait Time.
After enrolment, you’ll receive an email confirmation. Once your course materials are ready, your secure access details will be sent separately. The system ensures all learners begin with a stable, fully tested learning environment. This Works Even If You’ve Never Built an AI Campaign Before
Whether you’re a digital marketer transitioning into automation, a startup founder scaling growth, or a senior manager needing to lead AI initiatives-this course is built for real-world execution, not theory. We walk you through every technical, strategic, and operational layer, assuming no prior AI experience. Social Proof: I joined with zero AI background and used the lead-scoring framework from Module 6 to rebuild our CRM pipeline. We cut manual qualification time by 70% and improved conversion alignment with sales by 55%. This course paid for itself in two weeks. - Marcus T., Growth Lead, B2B Tech This works even if you’ve tried automation tools before and failed. Even if you’re time-crunched. Even if your previous campaigns underperformed. We give you the exact sequences, logic models, and integration blueprints proven to scale. Your only job is to apply them. You’re not gambling. You’re investing in a future-proof skillset with complete risk reversal. You gain lifetime access, expert support, global certification, and a results-driven curriculum-all designed to eliminate uncertainty and maximise your professional return.
Module 1: Foundations of AI-Powered Marketing Automation - Understanding the shift from rule-based to AI-driven marketing
- Core principles of machine learning in customer behaviour prediction
- Defining high-growth campaign objectives with precision
- Mapping customer journeys for AI optimisation opportunities
- Identifying low-hanging automation use cases in your current funnel
- Setting KPIs that align with AI capabilities and business goals
- Assessing your tech stack readiness for AI integration
- Common myths and misconceptions about AI marketing automation
- Role of data hygiene in AI model performance
- Introduction to intent signals and predictive scoring models
Module 2: Strategic Frameworks for AI-Driven Campaign Design - The 5-Phase AI Campaign Lifecycle Model
- Building campaign architectures with closed-loop feedback
- Designing personalisation at scale using dynamic content logic
- Creating adaptive messaging trees based on user behaviour
- Mapping AI intervention points across acquisition, retention, and expansion
- Developing failure-tolerant automation workflows
- Integrating A/B testing into AI decision pathways
- Aligning campaign logic with brand voice and compliance
- Defining escalation paths for human override
- Using predictive cohorting to divide audiences by conversion probability
Module 3: Core AI Tools and Platform Selection - Comparative analysis of major AI marketing platforms (HubSpot, Marketo, ActiveCampaign, Klaviyo, etc)
- Selecting tools based on data volume, team size, and growth trajectory
- Understanding native AI features vs third-party integrations
- Evaluating cost-to-value ratio of AI automation tools
- Assessing API strength and ecosystem compatibility
- Benchmarking AI capabilities: predictive scoring, send time optimisation, content recommendations
- Setting up sandbox environments for safe experimentation
- Importing and structuring data for AI model training
- Configuring real-time data pipelines from web, email, and CRM sources
- Automated data cleansing using AI pattern detection
Module 4: AI-Optimised Campaign Flows for Acquisition - Building AI-powered lead capture forms with dynamic field logic
- Designing intelligent landing pages that adapt to visitor profiles
- Creating responsive chatbot scripts that qualify leads instantly
- Automating lead routing based on real-time scoring and predicted fit
- Developing multi-channel nurture sequences with AI-driven pacing
- Implementing predictive content sequencing for cold audiences
- Using intent data to prioritise outreach efforts
- Triggering hyper-targeted ad retargeting from engagement signals
- Integrating AI-generated dynamic ads with campaign automation
- Building lookalike audience models from high-LTV customers
Module 5: Advanced Personalisation and Dynamic Content Systems - Generating AI-curated email subject lines and preview text
- Creating dynamic body content based on behavioural triggers
- Implementing real-time content swaps using engagement heatmaps
- Automating product recommendations using collaborative filtering
- Developing adaptive CTAs that respond to user intent
- Using sentiment analysis to adjust messaging tone automatically
- Building lifecycle stage-specific content calendars with AI
- Automating content repurposing across channels
- Personalising video thumbnails and ad creatives using engagement data
- Integrating custom AI language models for brand-aligned copy generation
Module 6: Predictive Lead Scoring and Sales Alignment - Designing multi-factor lead scoring models using AI
- Training models on historical conversion data for accuracy
- Integrating behavioural, demographic, and firmographic signals
- Automating score updates in real time across CRM and marketing tools
- Setting dynamic thresholds for sales handoff
- Building feedback loops from sales teams to refine scoring logic
- Creating dashboard alerts for high-intent prospects
- Reducing false positives with anomaly detection algorithms
- Aligning marketing and sales on AI-generated lead definitions
- Documenting scoring logic for audit and compliance
Module 7: ROI Measurement and Attribution Modelling - Implementing multi-touch attribution powered by AI
- Mapping customer journeys across fragmented touchpoints
- Using Shapley value models to assign credit accurately
- Automating budget reallocation based on channel performance
- Building predictive spend optimisation models
- Forecasting CAC and LTV using historical and real-time data
- Creating automated ROI dashboards with anomaly detection
- Identifying underperforming segments for AI intervention
- Validating attribution model accuracy with holdout testing
- Generating board-ready ROI reports with automated commentary
Module 8: Behavioural Triggers and Real-Time Automation - Setting up website engagement triggers for campaign activation
- Automating email sends based on scroll depth and time on page
- Using dwell time to trigger follow-up sequences
- Creating cart abandonment flows with predictive discount timing
- Triggering SMS sequences from mobile app inactivity
- Integrating offline behaviour (call duration, event attendance) into triggers
- Building win-back campaigns based on engagement decay patterns
- Using login frequency to segment product adoption risk
- Automating re-engagement for dormant users using decay algorithms
- Developing weather, location, and time-based triggers
Module 9: AI in Email, SMS, and Push Notification Automation - Optimising send times using individual engagement history
- Automating subject line selection based on predicted open rates
- Personalising sender names to increase perceived familiarity
- Creating lifecycle-based SMS cadences with opt-out preservation
- Using AI to prioritise push notification messaging
- Generating click-prediction scores for message variants
- Automating message suppression for over-communicated segments
- Building dark mode and accessibility-aware content templates
- Testing emoji usage with sentiment-aligned selection
- Integrating location-based push triggers with CRM data
Module 10: AI-Driven Ad Campaign Automation - Automating audience segmentation for platform-specific targeting
- Building dynamic creative optimisation (DCO) workflows
- Using AI to generate and test ad copy variants at scale
- Automating bid strategies based on conversion probability
- Integrating conversion API data for model accuracy
- Creating feedback loops from ad performance into email flows
- Optimising ad spend allocation across channels in real time
- Using AI to detect and pause underperforming creatives
- Building geo-conquesting campaigns with competitor location data
- Automating lookalike expansion based on engagement thresholds
Module 11: Customer Retention and Upsell Automation - Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Understanding the shift from rule-based to AI-driven marketing
- Core principles of machine learning in customer behaviour prediction
- Defining high-growth campaign objectives with precision
- Mapping customer journeys for AI optimisation opportunities
- Identifying low-hanging automation use cases in your current funnel
- Setting KPIs that align with AI capabilities and business goals
- Assessing your tech stack readiness for AI integration
- Common myths and misconceptions about AI marketing automation
- Role of data hygiene in AI model performance
- Introduction to intent signals and predictive scoring models
Module 2: Strategic Frameworks for AI-Driven Campaign Design - The 5-Phase AI Campaign Lifecycle Model
- Building campaign architectures with closed-loop feedback
- Designing personalisation at scale using dynamic content logic
- Creating adaptive messaging trees based on user behaviour
- Mapping AI intervention points across acquisition, retention, and expansion
- Developing failure-tolerant automation workflows
- Integrating A/B testing into AI decision pathways
- Aligning campaign logic with brand voice and compliance
- Defining escalation paths for human override
- Using predictive cohorting to divide audiences by conversion probability
Module 3: Core AI Tools and Platform Selection - Comparative analysis of major AI marketing platforms (HubSpot, Marketo, ActiveCampaign, Klaviyo, etc)
- Selecting tools based on data volume, team size, and growth trajectory
- Understanding native AI features vs third-party integrations
- Evaluating cost-to-value ratio of AI automation tools
- Assessing API strength and ecosystem compatibility
- Benchmarking AI capabilities: predictive scoring, send time optimisation, content recommendations
- Setting up sandbox environments for safe experimentation
- Importing and structuring data for AI model training
- Configuring real-time data pipelines from web, email, and CRM sources
- Automated data cleansing using AI pattern detection
Module 4: AI-Optimised Campaign Flows for Acquisition - Building AI-powered lead capture forms with dynamic field logic
- Designing intelligent landing pages that adapt to visitor profiles
- Creating responsive chatbot scripts that qualify leads instantly
- Automating lead routing based on real-time scoring and predicted fit
- Developing multi-channel nurture sequences with AI-driven pacing
- Implementing predictive content sequencing for cold audiences
- Using intent data to prioritise outreach efforts
- Triggering hyper-targeted ad retargeting from engagement signals
- Integrating AI-generated dynamic ads with campaign automation
- Building lookalike audience models from high-LTV customers
Module 5: Advanced Personalisation and Dynamic Content Systems - Generating AI-curated email subject lines and preview text
- Creating dynamic body content based on behavioural triggers
- Implementing real-time content swaps using engagement heatmaps
- Automating product recommendations using collaborative filtering
- Developing adaptive CTAs that respond to user intent
- Using sentiment analysis to adjust messaging tone automatically
- Building lifecycle stage-specific content calendars with AI
- Automating content repurposing across channels
- Personalising video thumbnails and ad creatives using engagement data
- Integrating custom AI language models for brand-aligned copy generation
Module 6: Predictive Lead Scoring and Sales Alignment - Designing multi-factor lead scoring models using AI
- Training models on historical conversion data for accuracy
- Integrating behavioural, demographic, and firmographic signals
- Automating score updates in real time across CRM and marketing tools
- Setting dynamic thresholds for sales handoff
- Building feedback loops from sales teams to refine scoring logic
- Creating dashboard alerts for high-intent prospects
- Reducing false positives with anomaly detection algorithms
- Aligning marketing and sales on AI-generated lead definitions
- Documenting scoring logic for audit and compliance
Module 7: ROI Measurement and Attribution Modelling - Implementing multi-touch attribution powered by AI
- Mapping customer journeys across fragmented touchpoints
- Using Shapley value models to assign credit accurately
- Automating budget reallocation based on channel performance
- Building predictive spend optimisation models
- Forecasting CAC and LTV using historical and real-time data
- Creating automated ROI dashboards with anomaly detection
- Identifying underperforming segments for AI intervention
- Validating attribution model accuracy with holdout testing
- Generating board-ready ROI reports with automated commentary
Module 8: Behavioural Triggers and Real-Time Automation - Setting up website engagement triggers for campaign activation
- Automating email sends based on scroll depth and time on page
- Using dwell time to trigger follow-up sequences
- Creating cart abandonment flows with predictive discount timing
- Triggering SMS sequences from mobile app inactivity
- Integrating offline behaviour (call duration, event attendance) into triggers
- Building win-back campaigns based on engagement decay patterns
- Using login frequency to segment product adoption risk
- Automating re-engagement for dormant users using decay algorithms
- Developing weather, location, and time-based triggers
Module 9: AI in Email, SMS, and Push Notification Automation - Optimising send times using individual engagement history
- Automating subject line selection based on predicted open rates
- Personalising sender names to increase perceived familiarity
- Creating lifecycle-based SMS cadences with opt-out preservation
- Using AI to prioritise push notification messaging
- Generating click-prediction scores for message variants
- Automating message suppression for over-communicated segments
- Building dark mode and accessibility-aware content templates
- Testing emoji usage with sentiment-aligned selection
- Integrating location-based push triggers with CRM data
Module 10: AI-Driven Ad Campaign Automation - Automating audience segmentation for platform-specific targeting
- Building dynamic creative optimisation (DCO) workflows
- Using AI to generate and test ad copy variants at scale
- Automating bid strategies based on conversion probability
- Integrating conversion API data for model accuracy
- Creating feedback loops from ad performance into email flows
- Optimising ad spend allocation across channels in real time
- Using AI to detect and pause underperforming creatives
- Building geo-conquesting campaigns with competitor location data
- Automating lookalike expansion based on engagement thresholds
Module 11: Customer Retention and Upsell Automation - Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Comparative analysis of major AI marketing platforms (HubSpot, Marketo, ActiveCampaign, Klaviyo, etc)
- Selecting tools based on data volume, team size, and growth trajectory
- Understanding native AI features vs third-party integrations
- Evaluating cost-to-value ratio of AI automation tools
- Assessing API strength and ecosystem compatibility
- Benchmarking AI capabilities: predictive scoring, send time optimisation, content recommendations
- Setting up sandbox environments for safe experimentation
- Importing and structuring data for AI model training
- Configuring real-time data pipelines from web, email, and CRM sources
- Automated data cleansing using AI pattern detection
Module 4: AI-Optimised Campaign Flows for Acquisition - Building AI-powered lead capture forms with dynamic field logic
- Designing intelligent landing pages that adapt to visitor profiles
- Creating responsive chatbot scripts that qualify leads instantly
- Automating lead routing based on real-time scoring and predicted fit
- Developing multi-channel nurture sequences with AI-driven pacing
- Implementing predictive content sequencing for cold audiences
- Using intent data to prioritise outreach efforts
- Triggering hyper-targeted ad retargeting from engagement signals
- Integrating AI-generated dynamic ads with campaign automation
- Building lookalike audience models from high-LTV customers
Module 5: Advanced Personalisation and Dynamic Content Systems - Generating AI-curated email subject lines and preview text
- Creating dynamic body content based on behavioural triggers
- Implementing real-time content swaps using engagement heatmaps
- Automating product recommendations using collaborative filtering
- Developing adaptive CTAs that respond to user intent
- Using sentiment analysis to adjust messaging tone automatically
- Building lifecycle stage-specific content calendars with AI
- Automating content repurposing across channels
- Personalising video thumbnails and ad creatives using engagement data
- Integrating custom AI language models for brand-aligned copy generation
Module 6: Predictive Lead Scoring and Sales Alignment - Designing multi-factor lead scoring models using AI
- Training models on historical conversion data for accuracy
- Integrating behavioural, demographic, and firmographic signals
- Automating score updates in real time across CRM and marketing tools
- Setting dynamic thresholds for sales handoff
- Building feedback loops from sales teams to refine scoring logic
- Creating dashboard alerts for high-intent prospects
- Reducing false positives with anomaly detection algorithms
- Aligning marketing and sales on AI-generated lead definitions
- Documenting scoring logic for audit and compliance
Module 7: ROI Measurement and Attribution Modelling - Implementing multi-touch attribution powered by AI
- Mapping customer journeys across fragmented touchpoints
- Using Shapley value models to assign credit accurately
- Automating budget reallocation based on channel performance
- Building predictive spend optimisation models
- Forecasting CAC and LTV using historical and real-time data
- Creating automated ROI dashboards with anomaly detection
- Identifying underperforming segments for AI intervention
- Validating attribution model accuracy with holdout testing
- Generating board-ready ROI reports with automated commentary
Module 8: Behavioural Triggers and Real-Time Automation - Setting up website engagement triggers for campaign activation
- Automating email sends based on scroll depth and time on page
- Using dwell time to trigger follow-up sequences
- Creating cart abandonment flows with predictive discount timing
- Triggering SMS sequences from mobile app inactivity
- Integrating offline behaviour (call duration, event attendance) into triggers
- Building win-back campaigns based on engagement decay patterns
- Using login frequency to segment product adoption risk
- Automating re-engagement for dormant users using decay algorithms
- Developing weather, location, and time-based triggers
Module 9: AI in Email, SMS, and Push Notification Automation - Optimising send times using individual engagement history
- Automating subject line selection based on predicted open rates
- Personalising sender names to increase perceived familiarity
- Creating lifecycle-based SMS cadences with opt-out preservation
- Using AI to prioritise push notification messaging
- Generating click-prediction scores for message variants
- Automating message suppression for over-communicated segments
- Building dark mode and accessibility-aware content templates
- Testing emoji usage with sentiment-aligned selection
- Integrating location-based push triggers with CRM data
Module 10: AI-Driven Ad Campaign Automation - Automating audience segmentation for platform-specific targeting
- Building dynamic creative optimisation (DCO) workflows
- Using AI to generate and test ad copy variants at scale
- Automating bid strategies based on conversion probability
- Integrating conversion API data for model accuracy
- Creating feedback loops from ad performance into email flows
- Optimising ad spend allocation across channels in real time
- Using AI to detect and pause underperforming creatives
- Building geo-conquesting campaigns with competitor location data
- Automating lookalike expansion based on engagement thresholds
Module 11: Customer Retention and Upsell Automation - Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Generating AI-curated email subject lines and preview text
- Creating dynamic body content based on behavioural triggers
- Implementing real-time content swaps using engagement heatmaps
- Automating product recommendations using collaborative filtering
- Developing adaptive CTAs that respond to user intent
- Using sentiment analysis to adjust messaging tone automatically
- Building lifecycle stage-specific content calendars with AI
- Automating content repurposing across channels
- Personalising video thumbnails and ad creatives using engagement data
- Integrating custom AI language models for brand-aligned copy generation
Module 6: Predictive Lead Scoring and Sales Alignment - Designing multi-factor lead scoring models using AI
- Training models on historical conversion data for accuracy
- Integrating behavioural, demographic, and firmographic signals
- Automating score updates in real time across CRM and marketing tools
- Setting dynamic thresholds for sales handoff
- Building feedback loops from sales teams to refine scoring logic
- Creating dashboard alerts for high-intent prospects
- Reducing false positives with anomaly detection algorithms
- Aligning marketing and sales on AI-generated lead definitions
- Documenting scoring logic for audit and compliance
Module 7: ROI Measurement and Attribution Modelling - Implementing multi-touch attribution powered by AI
- Mapping customer journeys across fragmented touchpoints
- Using Shapley value models to assign credit accurately
- Automating budget reallocation based on channel performance
- Building predictive spend optimisation models
- Forecasting CAC and LTV using historical and real-time data
- Creating automated ROI dashboards with anomaly detection
- Identifying underperforming segments for AI intervention
- Validating attribution model accuracy with holdout testing
- Generating board-ready ROI reports with automated commentary
Module 8: Behavioural Triggers and Real-Time Automation - Setting up website engagement triggers for campaign activation
- Automating email sends based on scroll depth and time on page
- Using dwell time to trigger follow-up sequences
- Creating cart abandonment flows with predictive discount timing
- Triggering SMS sequences from mobile app inactivity
- Integrating offline behaviour (call duration, event attendance) into triggers
- Building win-back campaigns based on engagement decay patterns
- Using login frequency to segment product adoption risk
- Automating re-engagement for dormant users using decay algorithms
- Developing weather, location, and time-based triggers
Module 9: AI in Email, SMS, and Push Notification Automation - Optimising send times using individual engagement history
- Automating subject line selection based on predicted open rates
- Personalising sender names to increase perceived familiarity
- Creating lifecycle-based SMS cadences with opt-out preservation
- Using AI to prioritise push notification messaging
- Generating click-prediction scores for message variants
- Automating message suppression for over-communicated segments
- Building dark mode and accessibility-aware content templates
- Testing emoji usage with sentiment-aligned selection
- Integrating location-based push triggers with CRM data
Module 10: AI-Driven Ad Campaign Automation - Automating audience segmentation for platform-specific targeting
- Building dynamic creative optimisation (DCO) workflows
- Using AI to generate and test ad copy variants at scale
- Automating bid strategies based on conversion probability
- Integrating conversion API data for model accuracy
- Creating feedback loops from ad performance into email flows
- Optimising ad spend allocation across channels in real time
- Using AI to detect and pause underperforming creatives
- Building geo-conquesting campaigns with competitor location data
- Automating lookalike expansion based on engagement thresholds
Module 11: Customer Retention and Upsell Automation - Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Implementing multi-touch attribution powered by AI
- Mapping customer journeys across fragmented touchpoints
- Using Shapley value models to assign credit accurately
- Automating budget reallocation based on channel performance
- Building predictive spend optimisation models
- Forecasting CAC and LTV using historical and real-time data
- Creating automated ROI dashboards with anomaly detection
- Identifying underperforming segments for AI intervention
- Validating attribution model accuracy with holdout testing
- Generating board-ready ROI reports with automated commentary
Module 8: Behavioural Triggers and Real-Time Automation - Setting up website engagement triggers for campaign activation
- Automating email sends based on scroll depth and time on page
- Using dwell time to trigger follow-up sequences
- Creating cart abandonment flows with predictive discount timing
- Triggering SMS sequences from mobile app inactivity
- Integrating offline behaviour (call duration, event attendance) into triggers
- Building win-back campaigns based on engagement decay patterns
- Using login frequency to segment product adoption risk
- Automating re-engagement for dormant users using decay algorithms
- Developing weather, location, and time-based triggers
Module 9: AI in Email, SMS, and Push Notification Automation - Optimising send times using individual engagement history
- Automating subject line selection based on predicted open rates
- Personalising sender names to increase perceived familiarity
- Creating lifecycle-based SMS cadences with opt-out preservation
- Using AI to prioritise push notification messaging
- Generating click-prediction scores for message variants
- Automating message suppression for over-communicated segments
- Building dark mode and accessibility-aware content templates
- Testing emoji usage with sentiment-aligned selection
- Integrating location-based push triggers with CRM data
Module 10: AI-Driven Ad Campaign Automation - Automating audience segmentation for platform-specific targeting
- Building dynamic creative optimisation (DCO) workflows
- Using AI to generate and test ad copy variants at scale
- Automating bid strategies based on conversion probability
- Integrating conversion API data for model accuracy
- Creating feedback loops from ad performance into email flows
- Optimising ad spend allocation across channels in real time
- Using AI to detect and pause underperforming creatives
- Building geo-conquesting campaigns with competitor location data
- Automating lookalike expansion based on engagement thresholds
Module 11: Customer Retention and Upsell Automation - Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Optimising send times using individual engagement history
- Automating subject line selection based on predicted open rates
- Personalising sender names to increase perceived familiarity
- Creating lifecycle-based SMS cadences with opt-out preservation
- Using AI to prioritise push notification messaging
- Generating click-prediction scores for message variants
- Automating message suppression for over-communicated segments
- Building dark mode and accessibility-aware content templates
- Testing emoji usage with sentiment-aligned selection
- Integrating location-based push triggers with CRM data
Module 10: AI-Driven Ad Campaign Automation - Automating audience segmentation for platform-specific targeting
- Building dynamic creative optimisation (DCO) workflows
- Using AI to generate and test ad copy variants at scale
- Automating bid strategies based on conversion probability
- Integrating conversion API data for model accuracy
- Creating feedback loops from ad performance into email flows
- Optimising ad spend allocation across channels in real time
- Using AI to detect and pause underperforming creatives
- Building geo-conquesting campaigns with competitor location data
- Automating lookalike expansion based on engagement thresholds
Module 11: Customer Retention and Upsell Automation - Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Designing churn prediction models using behavioural signals
- Automating retention offers based on predicted churn risk
- Creating usage-based nurture tracks for product adoption
- Triggering onboarding completion sequences with in-app prompts
- Automating feedback collection at critical journey milestones
- Building win-back offers with dynamic discount algorithms
- Using sentiment analysis to escalate at-risk customers
- Creating lifecycle stage-specific upsell recommendation engines
- Implementing referral automation with peer-matching AI
- Automating renewal reminders with contract value tracking
Module 12: Data Infrastructure and Model Training - Structuring clean, AI-ready datasets from fragmented sources
- Automating data validation and outlier detection
- Setting up continuous data ingestion pipelines
- Normalising data across platforms for unified scoring
- Handling missing data in predictive models
- Training AI models with weighted historical performance data
- Validating model accuracy using cross-sectional testing
- Setting up automated retraining schedules
- Documenting data lineage for compliance and audit
- Building data dictionaries for team-wide clarity
Module 13: Governance, Compliance, and Ethical AI Use - Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Implementing GDPR and CCPA-compliant automation logic
- Designing data consent workflows with AI-assisted tracking
- Automating opt-in and opt-out compliance across channels
- Building explainability into AI decision pathways
- Conducting bias audits in predictive models
- Creating transparency logs for AI-driven actions
- Ensuring accessibility in automated communications
- Developing escalation protocols for AI errors
- Documenting decision rules for regulatory review
- Training teams on ethical AI usage standards
Module 14: Scaling AI Automation Across Teams and Regions - Developing centralised automation governance models
- Creating reusable template libraries for global teams
- Implementing version control for campaign logic
- Automating approval workflows for compliance
- Setting up role-based access controls for campaign editors
- Integrating AI automation with project management tools
- Building training onboarding kits for new hires
- Automating performance reporting for leadership review
- Developing localisation strategies for multi-region campaigns
- Scaling personalisation without sacrificing consistency
Module 15: Advanced Integration and API Orchestration - Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Mapping data flows between CRM, CDP, and marketing tools
- Automating webhook responses for real-time actions
- Building custom middleware for unsupported integrations
- Using Zapier and Make for low-code AI automation
- Creating retry logic for failed API calls
- Monitoring integration health with automated alerts
- Securing data transfers with token-based authentication
- Developing fallback workflows for system downtime
- Testing integration reliability under load
- Documenting API usage for team onboarding
Module 16: Campaign Optimisation and Continuous Learning Loops - Setting up automated performance diagnostics
- Using AI to detect underperforming campaign elements
- Creating self-correcting email send logic
- Automating creative refresh cycles based on fatigue signals
- Building adaptive subject line libraries
- Implementing gradual rollout (canary) testing for new automations
- Using control groups to measure true incremental lift
- Automating hypothesis generation from performance anomalies
- Integrating qualitative feedback into quantitative models
- Creating a culture of continuous automation improvement
Module 17: AI for B2B, B2C, and Hybrid Models - Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection
Module 18: Final Project and Certification Preparation - Choosing a real-world campaign to transform using AI
- Conducting a gap analysis of current automation maturity
- Designing a full AI-powered campaign workflow from scratch
- Applying predictive scoring and personalisation logic
- Integrating cross-channel triggers and responses
- Building a measurement framework with automated reporting
- Calculating projected ROI and efficiency gains
- Creating a presentation deck for stakeholder approval
- Submitting your project for expert review
- Receiving detailed feedback and refinement guidance
- Finalising your board-ready AI campaign proposal
- Preparing for your Certificate of Completion assessment
- Documenting your implementation roadmap
- Accessing the alumni resource portal
- Joining the certified practitioners network
- Designing AI automations for complex B2B sales cycles
- Mapping multi-touch influence in enterprise deals
- Automating account-based marketing (ABM) workflows
- Creating intent-triggered outreach for key accounts
- Building unified consumer profiles for DTC brands
- Integrating loyalty program data into personalisation engines
- Adapting strategies for hybrid subscription-transaction models
- Using AI to optimise freemium-to-paid conversion paths
- Automating event-driven campaigns for retail seasonality
- Developing crisis-response automation for brand protection