COURSE FORMAT & DELIVERY DETAILS Learn on Your Terms, With Complete Confidence
You’re investing in your future, so we’ve designed every detail of this course to maximise value, flexibility, and peace of mind. This is not a gamble - it’s a structured, results-oriented journey that puts you in control from day one, with zero risk and 100% clarity on what you’ll gain. Self-Paced, Immediate Online Access
From the moment you enrol, you gain full access to the course platform. Learn at your own speed, on your schedule, with no rigid start dates, deadlines, or attendance requirements. You decide when, where, and how fast you move through the material. Most learners complete the course within 4 to 6 weeks by dedicating just a few focused hours per week. However, aggressive learners have applied the frameworks and begun executing high-impact strategies in under 10 days. Lifetime Access, Zero Future Costs
You’re not purchasing temporary knowledge - you’re securing a permanent asset. Once enrolled, you have lifetime access to all course materials, including every future update, refinement, and expansion. The field of AI-driven programmatic TV advertising evolves rapidly, and you’ll never pay extra to stay current. Our team continuously integrates the latest industry standards, algorithm advancements, and platform shifts so your knowledge remains cutting-edge for years to come. 24/7 Global, Mobile-Friendly Learning
Access your lessons from any device, anywhere in the world. Whether you're on a laptop during work hours, reviewing tactics on your tablet during a commute, or refining strategies on your phone during downtime, the platform adapts to your lifestyle. No downloads. No compatibility issues. Just seamless, responsive access whenever inspiration or urgency strikes. Direct Instructor Support & Strategic Guidance
This is not a course you navigate alone. You receive direct access to expert-led guidance through our dedicated support system. Ask questions, receive detailed feedback, and gain clarification on complex frameworks. Our instructors are practitioners with real-world experience in deploying AI-powered TV advertising at enterprise scale, and they’re committed to your success. You’re not just reading content - you’re being coached by top-tier professionals. Certificate of Completion Issued by The Art of Service
Upon finishing the course, you’ll earn a verified Certificate of Completion issued by The Art of Service - a globally recognised credential trusted by professionals in over 60 countries. This certificate carries weight in resumes, LinkedIn profiles, and job interviews. It signals to employers, clients, and peers that you’ve mastered a complex, high-value discipline with rigour and depth. It’s not participation, it’s validation of expertise. Transparent Pricing, No Hidden Fees
What you see is what you get. There are no subscriptions, no surprise charges, and no upsells after enrolment. The price you pay covers everything - lifetime access, all updates, certificate issuance, and ongoing support. We believe in fairness and clarity, because your trust is non-negotiable. Accepted Payment Methods
We accept all major payment options, including Visa, Mastercard, and PayPal. Your transaction is processed securely with bank-level encryption, ensuring your financial information remains protected at all times. 100% Money-Back Guarantee - Satisfied or Refunded
We eliminate every shred of risk with our unconditional money-back guarantee. If, at any point within 30 days, you determine the course doesn’t meet your expectations, simply request a refund. No forms, no follow-ups, no arguments. You walk away with your money and no loss. This guarantee ensures that trying this course costs you nothing - but not trying it could cost you your next career breakthrough. What Happens After Enrolment
Shortly after enrolment, you’ll receive an email confirming your registration. Once your course access is fully configured, a separate email will deliver your secure login details. This process ensures your learning environment is properly initialised and ready for an optimal experience. Please allow sufficient time for system coordination - we prioritise accuracy over speed to protect your access integrity. This Works Even If…
You’re uncertain about your technical background You’re transitioning from traditional TV or digital advertising You’ve never worked with AI or programmatic platforms before You're time-constrained and need fast, actionable insights ...because this course was built for exactly those challenges. Marketing Director, Elena Rivera, used the predictive audience modelling techniques to increase her client’s CTV campaign ROI by 227% in 8 weeks - despite having no prior AI training. Media Buyer, James Lin, went from managing basic OTT ads to leading his agency’s AI-powered programmatic division within 3 months of completing the course. Social proof confirms what the design ensures: this course is engineered for real people, in real roles, facing real market pressures. Whether you’re a strategist, media planner, performance marketer, or agency lead, the systems inside apply directly to your daily impact. You’re not gambling on theory. You’re gaining a battle-tested, step-by-step advantage - made safe by lifetime access, certified credibility, and a risk-free guarantee. Your career evolution starts here, with no downside and unlimited upside.
EXTENSIVE & DETAILED COURSE CURRICULUM
Module 1: Foundations of Programmatic TV and the AI Revolution - Understanding the shift from linear TV to addressable CTV and OTT
- Defining programmatic TV advertising and its core mechanics
- How AI is redefining ad buying, targeting, and optimisation
- Key differences between traditional programmatic display and TV
- The evolution of connected TVs and smart streaming devices
- How consumer viewing habits are fragmented across platforms
- The role of data in modern TV advertising ecosystems
- Why manual TV buys are being replaced by intelligent automation
- Overview of major CTV platforms and their technical constraints
- The convergence of digital and television ad infrastructure
- Introduction to impression-level bidding and real-time decisions
- Understanding walled gardens vs open-marketplace environments
- Role of viewing IDs, household matching, and privacy-safe identifiers
- Preparing for the deprecation of third-party cookies in TV contexts
- How first-party data is leveraged in TV campaign planning
Module 2: Core Components of the Programmatic TV Ecosystem - Mapping the end-to-end programmatic TV supply chain
- Demand Side Platforms: selection, setup, and configuration
- Supply Side Platforms and publisher integrations
- Ad servers and video ad decisioning systems
- Understanding data management platforms in TV contexts
- Role of the ad exchange in CTV transactions
- How deal IDs function in guaranteed and non-guaranteed inventory
- Private marketplaces vs open auctions for TV inventory
- Pre-bid verification tools and fraud protection layers
- Post-bid analytics and performance reconciliation
- How programmatic guaranteed deals ensure premium placements
- Understanding STVs, AVOD, SVOD, and hybrid content models
- Key players: Hulu, Roku, Samsung Ads, Amazon Publisher Services
- How FAST channels are reshaping ad availability
- Integration of linear TV data into digital reporting stacks
Module 3: Data Architecture for AI-Driven Decisioning - First-party data ingestion strategies from CRM and web sources
- Building custom audience segments for vertical-specific campaigns
- Onboarding offline purchase data into programmatic environments
- Creating lookalike models using seed audience profiling
- How machine learning clusters viewers by intent and behaviour
- Implementing probabilistic vs deterministic matching systems
- Understanding identity resolution across multiple devices
- Creating unified household profiles from fragmented signals
- Data clean room integration for privacy-compliant targeting
- How AI prioritises data freshness and recency in decisioning
- Real-time data feedback loops and dynamic segmentation
- Setting up custom conversion tracking for CTV campaigns
- Attribution windows and cross-device pathing models
- Using predictive lift models to estimate audience responsiveness
- Leveraging historical campaign data to train AI models
Module 4: AI Algorithms and Decision Engines in Advertising - Overview of supervised and unsupervised machine learning models
- How reinforcement learning optimises bidding strategies
- Decision trees and ensemble methods in audience selection
- Neural networks for predicting conversion probabilities
- Natural language processing for content and context targeting
- Computer vision techniques in creative optimisation
- Real-time bidding algorithms and impression valuation models
- How budget pacing algorithms prevent overspending
- Forecasting models for inventory availability and cost trends
- AI-driven bid shading and cost efficiency maximisation
- Demand forecasting to align spend with audience availability
- Automated frequency capping based on engagement signals
- Dynamic creative optimisation using performance feedback
- Geo-conquesting and competitor overlap analysis via AI
- Contextual sentiment analysis for brand-safe placements
Module 5: Campaign Strategy Design and AI Integration - Defining KPIs aligned with business objectives
- Mapping media goals to technical capabilities
- Designing multi-touchpoint funnel strategies for CTV
- Building awareness, consideration, and conversion sequences
- How AI automates audience layering and suppression
- Sequential messaging strategies powered by decision engines
- Retargeting audiences across devices based on CTV exposure
- Creating exclusivity rules to prevent internal competition
- Setting up competitive exclusion zones to avoid ad waste
- Time-based triggers and dayparting intelligence
- Weather, location, and inventory-driven campaign rules
- Event-based activation using real-time triggers
- Developing companion campaigns across digital channels
- Overcoming ad fatigue through AI-powered rotation
- Designing OTT-first vs hybrid campaign architectures
Module 6: Platform Selection and Technical Implementation - Evaluating DSP capabilities for AI-readiness
- Comparing features across major platforms: The Trade Desk, DV360, Xandr, Magnite
- Integrating data sources into your chosen DSP
- Setting up automated campaign templates with dynamic variables
- Configuring pacing, frequency, and bid strategies
- Building audience stacks using layer logic and priority rules
- How to map creatives to audience segments programmatically
- Setting up automated rules for budget adjustments
- Creating alert systems for anomaly detection
- Implementing viewability and fraud filters at the impression level
- Integrating third-party verification tools
- Setting up custom metrics and KPI dashboards
- Using API integrations for data sync and automation
- Automating media plan generation from performance data
- Testing AI-generated campaign recommendations before launch
Module 7: Creative Strategy and Dynamic Creative Optimisation - Principles of effective CTV creative development
- Ad formats: 15s, 30s, mid-roll, pre-roll, and bumper variations
- Designing for sound-off, mobile second-screen, and lean-back viewing
- Versioning creatives for demographic and behavioural targeting
- How AI selects the best creative variant in real time
- Using A/B testing frameworks within DCO systems
- Automated voiceover swapping for regional personalisation
- Dynamic text and logo insertion based on location or brand
- Product feed integration for retail and e-commerce campaigns
- Emotion recognition models in creative testing environments
- Eye-tracking and attention prediction in ad design
- Building creative libraries with metadata tagging systems
- Automated closed captioning and accessibility standards
- Testing ad length impact on completion rates
- Creating sequential creative narratives across touchpoints
Module 8: Measurement, Attribution, and Performance Analysis - Multi-touch attribution models in cross-channel environments
- Incrementality testing to prove campaign causation
- Designing controlled lift studies without disrupting scale
- Understanding walled garden reporting limitations
- Integrating offline sales data with digital exposure logs
- Using statistical modelling to estimate offline impact
- How AI estimates true reach and frequency across households
- Viewability benchmarks and benchmarks for completion rates
- Analysing attention time vs passive exposure duration
- Setting threshold alerts for underperforming segments
- Automated anomaly detection in performance data
- Benchmarking CTV performance against other channels
- Calculating CPA, ROAS, and brand recall lift
- Building custom dashboards using Google Looker Studio
- Exporting raw data for external modelling and forecasting
Module 9: Advanced Optimisation Techniques and AI Feedback Loops - Automated bid adjustments based on real-time performance
- Machine learning models that predict optimal bid levels
- Dynamic budget reallocation across audience segments
- Automated pause and restart rules for underperforming cohorts
- Using confidence intervals to prevent over-optimisation
- Handling cold-start problems with new audiences
- Multi-objective optimisation: balancing reach, frequency, and conversion
- Latency-aware optimisation for fast-moving inventory
- Creating feedback loops between creative performance and targeting
- Automated audience refresh cycles based on engagement decay
- Seasonality adjustment algorithms for spend forecasting
- Competitor activity detection and counter-bidding logic
- AI-driven negotiation support for guaranteed deals
- Automated reporting and insight generation from raw logs
- Prescriptive analytics: getting recommendations, not just reports
Module 10: Privacy, Compliance, and Ethical AI Considerations - GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
Module 1: Foundations of Programmatic TV and the AI Revolution - Understanding the shift from linear TV to addressable CTV and OTT
- Defining programmatic TV advertising and its core mechanics
- How AI is redefining ad buying, targeting, and optimisation
- Key differences between traditional programmatic display and TV
- The evolution of connected TVs and smart streaming devices
- How consumer viewing habits are fragmented across platforms
- The role of data in modern TV advertising ecosystems
- Why manual TV buys are being replaced by intelligent automation
- Overview of major CTV platforms and their technical constraints
- The convergence of digital and television ad infrastructure
- Introduction to impression-level bidding and real-time decisions
- Understanding walled gardens vs open-marketplace environments
- Role of viewing IDs, household matching, and privacy-safe identifiers
- Preparing for the deprecation of third-party cookies in TV contexts
- How first-party data is leveraged in TV campaign planning
Module 2: Core Components of the Programmatic TV Ecosystem - Mapping the end-to-end programmatic TV supply chain
- Demand Side Platforms: selection, setup, and configuration
- Supply Side Platforms and publisher integrations
- Ad servers and video ad decisioning systems
- Understanding data management platforms in TV contexts
- Role of the ad exchange in CTV transactions
- How deal IDs function in guaranteed and non-guaranteed inventory
- Private marketplaces vs open auctions for TV inventory
- Pre-bid verification tools and fraud protection layers
- Post-bid analytics and performance reconciliation
- How programmatic guaranteed deals ensure premium placements
- Understanding STVs, AVOD, SVOD, and hybrid content models
- Key players: Hulu, Roku, Samsung Ads, Amazon Publisher Services
- How FAST channels are reshaping ad availability
- Integration of linear TV data into digital reporting stacks
Module 3: Data Architecture for AI-Driven Decisioning - First-party data ingestion strategies from CRM and web sources
- Building custom audience segments for vertical-specific campaigns
- Onboarding offline purchase data into programmatic environments
- Creating lookalike models using seed audience profiling
- How machine learning clusters viewers by intent and behaviour
- Implementing probabilistic vs deterministic matching systems
- Understanding identity resolution across multiple devices
- Creating unified household profiles from fragmented signals
- Data clean room integration for privacy-compliant targeting
- How AI prioritises data freshness and recency in decisioning
- Real-time data feedback loops and dynamic segmentation
- Setting up custom conversion tracking for CTV campaigns
- Attribution windows and cross-device pathing models
- Using predictive lift models to estimate audience responsiveness
- Leveraging historical campaign data to train AI models
Module 4: AI Algorithms and Decision Engines in Advertising - Overview of supervised and unsupervised machine learning models
- How reinforcement learning optimises bidding strategies
- Decision trees and ensemble methods in audience selection
- Neural networks for predicting conversion probabilities
- Natural language processing for content and context targeting
- Computer vision techniques in creative optimisation
- Real-time bidding algorithms and impression valuation models
- How budget pacing algorithms prevent overspending
- Forecasting models for inventory availability and cost trends
- AI-driven bid shading and cost efficiency maximisation
- Demand forecasting to align spend with audience availability
- Automated frequency capping based on engagement signals
- Dynamic creative optimisation using performance feedback
- Geo-conquesting and competitor overlap analysis via AI
- Contextual sentiment analysis for brand-safe placements
Module 5: Campaign Strategy Design and AI Integration - Defining KPIs aligned with business objectives
- Mapping media goals to technical capabilities
- Designing multi-touchpoint funnel strategies for CTV
- Building awareness, consideration, and conversion sequences
- How AI automates audience layering and suppression
- Sequential messaging strategies powered by decision engines
- Retargeting audiences across devices based on CTV exposure
- Creating exclusivity rules to prevent internal competition
- Setting up competitive exclusion zones to avoid ad waste
- Time-based triggers and dayparting intelligence
- Weather, location, and inventory-driven campaign rules
- Event-based activation using real-time triggers
- Developing companion campaigns across digital channels
- Overcoming ad fatigue through AI-powered rotation
- Designing OTT-first vs hybrid campaign architectures
Module 6: Platform Selection and Technical Implementation - Evaluating DSP capabilities for AI-readiness
- Comparing features across major platforms: The Trade Desk, DV360, Xandr, Magnite
- Integrating data sources into your chosen DSP
- Setting up automated campaign templates with dynamic variables
- Configuring pacing, frequency, and bid strategies
- Building audience stacks using layer logic and priority rules
- How to map creatives to audience segments programmatically
- Setting up automated rules for budget adjustments
- Creating alert systems for anomaly detection
- Implementing viewability and fraud filters at the impression level
- Integrating third-party verification tools
- Setting up custom metrics and KPI dashboards
- Using API integrations for data sync and automation
- Automating media plan generation from performance data
- Testing AI-generated campaign recommendations before launch
Module 7: Creative Strategy and Dynamic Creative Optimisation - Principles of effective CTV creative development
- Ad formats: 15s, 30s, mid-roll, pre-roll, and bumper variations
- Designing for sound-off, mobile second-screen, and lean-back viewing
- Versioning creatives for demographic and behavioural targeting
- How AI selects the best creative variant in real time
- Using A/B testing frameworks within DCO systems
- Automated voiceover swapping for regional personalisation
- Dynamic text and logo insertion based on location or brand
- Product feed integration for retail and e-commerce campaigns
- Emotion recognition models in creative testing environments
- Eye-tracking and attention prediction in ad design
- Building creative libraries with metadata tagging systems
- Automated closed captioning and accessibility standards
- Testing ad length impact on completion rates
- Creating sequential creative narratives across touchpoints
Module 8: Measurement, Attribution, and Performance Analysis - Multi-touch attribution models in cross-channel environments
- Incrementality testing to prove campaign causation
- Designing controlled lift studies without disrupting scale
- Understanding walled garden reporting limitations
- Integrating offline sales data with digital exposure logs
- Using statistical modelling to estimate offline impact
- How AI estimates true reach and frequency across households
- Viewability benchmarks and benchmarks for completion rates
- Analysing attention time vs passive exposure duration
- Setting threshold alerts for underperforming segments
- Automated anomaly detection in performance data
- Benchmarking CTV performance against other channels
- Calculating CPA, ROAS, and brand recall lift
- Building custom dashboards using Google Looker Studio
- Exporting raw data for external modelling and forecasting
Module 9: Advanced Optimisation Techniques and AI Feedback Loops - Automated bid adjustments based on real-time performance
- Machine learning models that predict optimal bid levels
- Dynamic budget reallocation across audience segments
- Automated pause and restart rules for underperforming cohorts
- Using confidence intervals to prevent over-optimisation
- Handling cold-start problems with new audiences
- Multi-objective optimisation: balancing reach, frequency, and conversion
- Latency-aware optimisation for fast-moving inventory
- Creating feedback loops between creative performance and targeting
- Automated audience refresh cycles based on engagement decay
- Seasonality adjustment algorithms for spend forecasting
- Competitor activity detection and counter-bidding logic
- AI-driven negotiation support for guaranteed deals
- Automated reporting and insight generation from raw logs
- Prescriptive analytics: getting recommendations, not just reports
Module 10: Privacy, Compliance, and Ethical AI Considerations - GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
- Mapping the end-to-end programmatic TV supply chain
- Demand Side Platforms: selection, setup, and configuration
- Supply Side Platforms and publisher integrations
- Ad servers and video ad decisioning systems
- Understanding data management platforms in TV contexts
- Role of the ad exchange in CTV transactions
- How deal IDs function in guaranteed and non-guaranteed inventory
- Private marketplaces vs open auctions for TV inventory
- Pre-bid verification tools and fraud protection layers
- Post-bid analytics and performance reconciliation
- How programmatic guaranteed deals ensure premium placements
- Understanding STVs, AVOD, SVOD, and hybrid content models
- Key players: Hulu, Roku, Samsung Ads, Amazon Publisher Services
- How FAST channels are reshaping ad availability
- Integration of linear TV data into digital reporting stacks
Module 3: Data Architecture for AI-Driven Decisioning - First-party data ingestion strategies from CRM and web sources
- Building custom audience segments for vertical-specific campaigns
- Onboarding offline purchase data into programmatic environments
- Creating lookalike models using seed audience profiling
- How machine learning clusters viewers by intent and behaviour
- Implementing probabilistic vs deterministic matching systems
- Understanding identity resolution across multiple devices
- Creating unified household profiles from fragmented signals
- Data clean room integration for privacy-compliant targeting
- How AI prioritises data freshness and recency in decisioning
- Real-time data feedback loops and dynamic segmentation
- Setting up custom conversion tracking for CTV campaigns
- Attribution windows and cross-device pathing models
- Using predictive lift models to estimate audience responsiveness
- Leveraging historical campaign data to train AI models
Module 4: AI Algorithms and Decision Engines in Advertising - Overview of supervised and unsupervised machine learning models
- How reinforcement learning optimises bidding strategies
- Decision trees and ensemble methods in audience selection
- Neural networks for predicting conversion probabilities
- Natural language processing for content and context targeting
- Computer vision techniques in creative optimisation
- Real-time bidding algorithms and impression valuation models
- How budget pacing algorithms prevent overspending
- Forecasting models for inventory availability and cost trends
- AI-driven bid shading and cost efficiency maximisation
- Demand forecasting to align spend with audience availability
- Automated frequency capping based on engagement signals
- Dynamic creative optimisation using performance feedback
- Geo-conquesting and competitor overlap analysis via AI
- Contextual sentiment analysis for brand-safe placements
Module 5: Campaign Strategy Design and AI Integration - Defining KPIs aligned with business objectives
- Mapping media goals to technical capabilities
- Designing multi-touchpoint funnel strategies for CTV
- Building awareness, consideration, and conversion sequences
- How AI automates audience layering and suppression
- Sequential messaging strategies powered by decision engines
- Retargeting audiences across devices based on CTV exposure
- Creating exclusivity rules to prevent internal competition
- Setting up competitive exclusion zones to avoid ad waste
- Time-based triggers and dayparting intelligence
- Weather, location, and inventory-driven campaign rules
- Event-based activation using real-time triggers
- Developing companion campaigns across digital channels
- Overcoming ad fatigue through AI-powered rotation
- Designing OTT-first vs hybrid campaign architectures
Module 6: Platform Selection and Technical Implementation - Evaluating DSP capabilities for AI-readiness
- Comparing features across major platforms: The Trade Desk, DV360, Xandr, Magnite
- Integrating data sources into your chosen DSP
- Setting up automated campaign templates with dynamic variables
- Configuring pacing, frequency, and bid strategies
- Building audience stacks using layer logic and priority rules
- How to map creatives to audience segments programmatically
- Setting up automated rules for budget adjustments
- Creating alert systems for anomaly detection
- Implementing viewability and fraud filters at the impression level
- Integrating third-party verification tools
- Setting up custom metrics and KPI dashboards
- Using API integrations for data sync and automation
- Automating media plan generation from performance data
- Testing AI-generated campaign recommendations before launch
Module 7: Creative Strategy and Dynamic Creative Optimisation - Principles of effective CTV creative development
- Ad formats: 15s, 30s, mid-roll, pre-roll, and bumper variations
- Designing for sound-off, mobile second-screen, and lean-back viewing
- Versioning creatives for demographic and behavioural targeting
- How AI selects the best creative variant in real time
- Using A/B testing frameworks within DCO systems
- Automated voiceover swapping for regional personalisation
- Dynamic text and logo insertion based on location or brand
- Product feed integration for retail and e-commerce campaigns
- Emotion recognition models in creative testing environments
- Eye-tracking and attention prediction in ad design
- Building creative libraries with metadata tagging systems
- Automated closed captioning and accessibility standards
- Testing ad length impact on completion rates
- Creating sequential creative narratives across touchpoints
Module 8: Measurement, Attribution, and Performance Analysis - Multi-touch attribution models in cross-channel environments
- Incrementality testing to prove campaign causation
- Designing controlled lift studies without disrupting scale
- Understanding walled garden reporting limitations
- Integrating offline sales data with digital exposure logs
- Using statistical modelling to estimate offline impact
- How AI estimates true reach and frequency across households
- Viewability benchmarks and benchmarks for completion rates
- Analysing attention time vs passive exposure duration
- Setting threshold alerts for underperforming segments
- Automated anomaly detection in performance data
- Benchmarking CTV performance against other channels
- Calculating CPA, ROAS, and brand recall lift
- Building custom dashboards using Google Looker Studio
- Exporting raw data for external modelling and forecasting
Module 9: Advanced Optimisation Techniques and AI Feedback Loops - Automated bid adjustments based on real-time performance
- Machine learning models that predict optimal bid levels
- Dynamic budget reallocation across audience segments
- Automated pause and restart rules for underperforming cohorts
- Using confidence intervals to prevent over-optimisation
- Handling cold-start problems with new audiences
- Multi-objective optimisation: balancing reach, frequency, and conversion
- Latency-aware optimisation for fast-moving inventory
- Creating feedback loops between creative performance and targeting
- Automated audience refresh cycles based on engagement decay
- Seasonality adjustment algorithms for spend forecasting
- Competitor activity detection and counter-bidding logic
- AI-driven negotiation support for guaranteed deals
- Automated reporting and insight generation from raw logs
- Prescriptive analytics: getting recommendations, not just reports
Module 10: Privacy, Compliance, and Ethical AI Considerations - GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
- Overview of supervised and unsupervised machine learning models
- How reinforcement learning optimises bidding strategies
- Decision trees and ensemble methods in audience selection
- Neural networks for predicting conversion probabilities
- Natural language processing for content and context targeting
- Computer vision techniques in creative optimisation
- Real-time bidding algorithms and impression valuation models
- How budget pacing algorithms prevent overspending
- Forecasting models for inventory availability and cost trends
- AI-driven bid shading and cost efficiency maximisation
- Demand forecasting to align spend with audience availability
- Automated frequency capping based on engagement signals
- Dynamic creative optimisation using performance feedback
- Geo-conquesting and competitor overlap analysis via AI
- Contextual sentiment analysis for brand-safe placements
Module 5: Campaign Strategy Design and AI Integration - Defining KPIs aligned with business objectives
- Mapping media goals to technical capabilities
- Designing multi-touchpoint funnel strategies for CTV
- Building awareness, consideration, and conversion sequences
- How AI automates audience layering and suppression
- Sequential messaging strategies powered by decision engines
- Retargeting audiences across devices based on CTV exposure
- Creating exclusivity rules to prevent internal competition
- Setting up competitive exclusion zones to avoid ad waste
- Time-based triggers and dayparting intelligence
- Weather, location, and inventory-driven campaign rules
- Event-based activation using real-time triggers
- Developing companion campaigns across digital channels
- Overcoming ad fatigue through AI-powered rotation
- Designing OTT-first vs hybrid campaign architectures
Module 6: Platform Selection and Technical Implementation - Evaluating DSP capabilities for AI-readiness
- Comparing features across major platforms: The Trade Desk, DV360, Xandr, Magnite
- Integrating data sources into your chosen DSP
- Setting up automated campaign templates with dynamic variables
- Configuring pacing, frequency, and bid strategies
- Building audience stacks using layer logic and priority rules
- How to map creatives to audience segments programmatically
- Setting up automated rules for budget adjustments
- Creating alert systems for anomaly detection
- Implementing viewability and fraud filters at the impression level
- Integrating third-party verification tools
- Setting up custom metrics and KPI dashboards
- Using API integrations for data sync and automation
- Automating media plan generation from performance data
- Testing AI-generated campaign recommendations before launch
Module 7: Creative Strategy and Dynamic Creative Optimisation - Principles of effective CTV creative development
- Ad formats: 15s, 30s, mid-roll, pre-roll, and bumper variations
- Designing for sound-off, mobile second-screen, and lean-back viewing
- Versioning creatives for demographic and behavioural targeting
- How AI selects the best creative variant in real time
- Using A/B testing frameworks within DCO systems
- Automated voiceover swapping for regional personalisation
- Dynamic text and logo insertion based on location or brand
- Product feed integration for retail and e-commerce campaigns
- Emotion recognition models in creative testing environments
- Eye-tracking and attention prediction in ad design
- Building creative libraries with metadata tagging systems
- Automated closed captioning and accessibility standards
- Testing ad length impact on completion rates
- Creating sequential creative narratives across touchpoints
Module 8: Measurement, Attribution, and Performance Analysis - Multi-touch attribution models in cross-channel environments
- Incrementality testing to prove campaign causation
- Designing controlled lift studies without disrupting scale
- Understanding walled garden reporting limitations
- Integrating offline sales data with digital exposure logs
- Using statistical modelling to estimate offline impact
- How AI estimates true reach and frequency across households
- Viewability benchmarks and benchmarks for completion rates
- Analysing attention time vs passive exposure duration
- Setting threshold alerts for underperforming segments
- Automated anomaly detection in performance data
- Benchmarking CTV performance against other channels
- Calculating CPA, ROAS, and brand recall lift
- Building custom dashboards using Google Looker Studio
- Exporting raw data for external modelling and forecasting
Module 9: Advanced Optimisation Techniques and AI Feedback Loops - Automated bid adjustments based on real-time performance
- Machine learning models that predict optimal bid levels
- Dynamic budget reallocation across audience segments
- Automated pause and restart rules for underperforming cohorts
- Using confidence intervals to prevent over-optimisation
- Handling cold-start problems with new audiences
- Multi-objective optimisation: balancing reach, frequency, and conversion
- Latency-aware optimisation for fast-moving inventory
- Creating feedback loops between creative performance and targeting
- Automated audience refresh cycles based on engagement decay
- Seasonality adjustment algorithms for spend forecasting
- Competitor activity detection and counter-bidding logic
- AI-driven negotiation support for guaranteed deals
- Automated reporting and insight generation from raw logs
- Prescriptive analytics: getting recommendations, not just reports
Module 10: Privacy, Compliance, and Ethical AI Considerations - GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
- Evaluating DSP capabilities for AI-readiness
- Comparing features across major platforms: The Trade Desk, DV360, Xandr, Magnite
- Integrating data sources into your chosen DSP
- Setting up automated campaign templates with dynamic variables
- Configuring pacing, frequency, and bid strategies
- Building audience stacks using layer logic and priority rules
- How to map creatives to audience segments programmatically
- Setting up automated rules for budget adjustments
- Creating alert systems for anomaly detection
- Implementing viewability and fraud filters at the impression level
- Integrating third-party verification tools
- Setting up custom metrics and KPI dashboards
- Using API integrations for data sync and automation
- Automating media plan generation from performance data
- Testing AI-generated campaign recommendations before launch
Module 7: Creative Strategy and Dynamic Creative Optimisation - Principles of effective CTV creative development
- Ad formats: 15s, 30s, mid-roll, pre-roll, and bumper variations
- Designing for sound-off, mobile second-screen, and lean-back viewing
- Versioning creatives for demographic and behavioural targeting
- How AI selects the best creative variant in real time
- Using A/B testing frameworks within DCO systems
- Automated voiceover swapping for regional personalisation
- Dynamic text and logo insertion based on location or brand
- Product feed integration for retail and e-commerce campaigns
- Emotion recognition models in creative testing environments
- Eye-tracking and attention prediction in ad design
- Building creative libraries with metadata tagging systems
- Automated closed captioning and accessibility standards
- Testing ad length impact on completion rates
- Creating sequential creative narratives across touchpoints
Module 8: Measurement, Attribution, and Performance Analysis - Multi-touch attribution models in cross-channel environments
- Incrementality testing to prove campaign causation
- Designing controlled lift studies without disrupting scale
- Understanding walled garden reporting limitations
- Integrating offline sales data with digital exposure logs
- Using statistical modelling to estimate offline impact
- How AI estimates true reach and frequency across households
- Viewability benchmarks and benchmarks for completion rates
- Analysing attention time vs passive exposure duration
- Setting threshold alerts for underperforming segments
- Automated anomaly detection in performance data
- Benchmarking CTV performance against other channels
- Calculating CPA, ROAS, and brand recall lift
- Building custom dashboards using Google Looker Studio
- Exporting raw data for external modelling and forecasting
Module 9: Advanced Optimisation Techniques and AI Feedback Loops - Automated bid adjustments based on real-time performance
- Machine learning models that predict optimal bid levels
- Dynamic budget reallocation across audience segments
- Automated pause and restart rules for underperforming cohorts
- Using confidence intervals to prevent over-optimisation
- Handling cold-start problems with new audiences
- Multi-objective optimisation: balancing reach, frequency, and conversion
- Latency-aware optimisation for fast-moving inventory
- Creating feedback loops between creative performance and targeting
- Automated audience refresh cycles based on engagement decay
- Seasonality adjustment algorithms for spend forecasting
- Competitor activity detection and counter-bidding logic
- AI-driven negotiation support for guaranteed deals
- Automated reporting and insight generation from raw logs
- Prescriptive analytics: getting recommendations, not just reports
Module 10: Privacy, Compliance, and Ethical AI Considerations - GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
- Multi-touch attribution models in cross-channel environments
- Incrementality testing to prove campaign causation
- Designing controlled lift studies without disrupting scale
- Understanding walled garden reporting limitations
- Integrating offline sales data with digital exposure logs
- Using statistical modelling to estimate offline impact
- How AI estimates true reach and frequency across households
- Viewability benchmarks and benchmarks for completion rates
- Analysing attention time vs passive exposure duration
- Setting threshold alerts for underperforming segments
- Automated anomaly detection in performance data
- Benchmarking CTV performance against other channels
- Calculating CPA, ROAS, and brand recall lift
- Building custom dashboards using Google Looker Studio
- Exporting raw data for external modelling and forecasting
Module 9: Advanced Optimisation Techniques and AI Feedback Loops - Automated bid adjustments based on real-time performance
- Machine learning models that predict optimal bid levels
- Dynamic budget reallocation across audience segments
- Automated pause and restart rules for underperforming cohorts
- Using confidence intervals to prevent over-optimisation
- Handling cold-start problems with new audiences
- Multi-objective optimisation: balancing reach, frequency, and conversion
- Latency-aware optimisation for fast-moving inventory
- Creating feedback loops between creative performance and targeting
- Automated audience refresh cycles based on engagement decay
- Seasonality adjustment algorithms for spend forecasting
- Competitor activity detection and counter-bidding logic
- AI-driven negotiation support for guaranteed deals
- Automated reporting and insight generation from raw logs
- Prescriptive analytics: getting recommendations, not just reports
Module 10: Privacy, Compliance, and Ethical AI Considerations - GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
- GDPR, CCPA, and global privacy frameworks in CTV
- How AI respects opt-out signals and consent layers
- Anonymous audience targeting without PII
- Ensuring algorithmic fairness in audience selection
- Mitigating bias in machine learning models
- Transparency in AI decision-making for regulatory compliance
- Auditing AI systems for discriminatory patterns
- Data retention policies and secure deletion protocols
- Working with clean rooms and privacy-safe environments
- How to document AI logic for internal governance
- Certifications and compliance checks for vendors
- Disclosure requirements for automated decisioning
- Handling children’s content and COPPA restrictions
- Brand safety frameworks and content classification systems
- Monitoring for hate speech, misinformation, and extremism
Module 11: Real-World Project: Building a Full AI-Driven Campaign - Defining a business challenge for a real or hypothetical brand
- Conducting market and competitive analysis for CTV opportunities
- Setting primary and secondary campaign objectives
- Creating a detailed media plan with budget allocation
- Selecting target verticals and ideal customer profiles
- Building data onboarding pipelines and segment structures
- Designing creative versions and DCO logic trees
- Selecting a DSP and configuring account settings
- Setting up campaign groups with AI bid strategies
- Integrating third-party measurement and verification
- Launching a test flight with limited spend
- Monitoring initial results and adjusting targeting parameters
- Scaling winning segments based on performance thresholds
- Applying optimisation rules based on real-time data
- Generating final performance report and ROI analysis
Module 12: Integration with Broader Marketing Ecosystems - Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer
Module 13: Certification, Career Advancement, and Next Steps - Final assessment to validate comprehensive understanding
- Review of key concepts and real-world applications
- Submit your project for expert evaluation and feedback
- Receive personalised recommendations for growth areas
- Official Certificate of Completion issued by The Art of Service
- How to showcase your credential on LinkedIn and resumes
- Access to exclusive alumni resources and updates
- Joining a network of AI-driven advertising professionals
- Building a portfolio of certified campaign blueprints
- Guidance on transitioning to higher-responsibility roles
- Negotiating salary increases with certified expertise
- Preparing for leadership in media technology and innovation
- Continuing education pathways in AI and data science
- Staying ahead of platform changes and algorithm updates
- Accessing live Q&A and advanced workshops post-completion
- Aligning CTV strategy with overall brand media plans
- Coordinating programmatic TV with search and social
- Creating omnichannel frequency capping
- Using CTV exposure to trigger follow-up digital activity
- Seeding social listening from CTV campaign performance
- Integrating CRM data for closed-loop reporting
- Feeding CTV insights into product development and messaging
- Using performance data to influence creative agencies
- Reporting CTV impact to executive stakeholders
- Aligning KPIs across departments and measurement tools
- Automating insights handoff to sales and retention teams
- Scaling successful models across regions and languages
- Building reusable campaign frameworks for future launches
- Creating governance models for cross-functional teams
- Documenting best practices for organisational knowledge transfer