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URL: https://www.coursera.org/learn/ai-driven-brand-campaign-strategy-and-optimization

⇱ AI-Driven Brand Campaign Strategy and Optimization | Coursera


AI-Driven Brand Campaign Strategy and Optimization

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AI-Driven Brand Campaign Strategy and Optimization

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Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Build your subject-matter expertise

This course is part of the Brand Management with AI: Strategy to Execution Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Design scalable, AI-powered brand campaigns that integrate creative automation, predictive targeting, experimentation, and performance intelligence. This advanced course develops the capability to build high-performing omnichannel systems using generative AI, machine learning signals, and real-time optimization frameworks.

The curriculum covers AI-driven creative generation and structured testing workflows, predictive audience modelling and personalization strategies, automated experimentation systems, and cross-channel attribution modelling. It emphasizes balancing short-term efficiency metrics such as ROAS and CAC with long-term brand equity and sustainable growth. Performance dashboards and predictive KPIs are used to translate data signals into strategic decisions. By the end, the course enables the design of integrated AI-enhanced campaign architectures that continuously learn, optimize, and scale across platforms. By the End, You Will: • Design AI-powered omnichannel campaigns with structured creative testing • Apply predictive targeting and personalization frameworks at scale • Implement experimentation systems for real-time optimization • Evaluate performance using attribution models and AI-driven dashboards This Course Is Ideal For: • Brand and performance marketing professionals • Growth and media strategy leaders • Agency teams managing cross-channel campaigns • Analysts building AI-enabled marketing systems Develop the expertise required to transform campaign execution into an intelligent, continuously optimizing growth engine. Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.

This module introduces learners to the use of generative AI in creative strategy, content production, and testing workflows. Learners explore how AI tools can accelerate ideation, generate multiple creative variations, and support brand-aligned execution across formats such as text, visuals, and video. The module emphasizes evaluating AI-generated assets for consistency, inclusivity, and brand fit, ensuring creativity remains strategic rather than automated for speed alone. Learners also study AI-driven creative testing methods, including hook analysis, format comparison, attention modeling, and fatigue detection. In addition, the module covers scalable content automation pipelines—demonstrating how AI can streamline production, localization, and quality control while reducing manual effort. By the end of this module, learners will be able to design automated creative workflows, assess predicted performance signals, and deploy AI responsibly to enhance both efficiency and creative effectiveness.

What's included

11 videos5 readings4 assignments1 discussion prompt1 plugin

11 videosTotal 63 minutes
  • Introduction to the Course5 minutes
  • Career Scope: Creative Strategy in the Age of AI4 minutes
  • Using GenAI (ChatGPT, Midjourney, Runway) for Concepts & Variations8 minutes
  • Evaluating Brand Alignment of AI Creative Assets4 minutes
  • AI Tools for Creative Testing: Pattern Recognition & Variant Ranking6 minutes
  • Testing Hooks, Story Angles & Format Variations6 minutes
  • Heatmaps, Eye-Tracking, Attention Modeling6 minutes
  • Creative Fatigue, Wear-Out & Lifecycle Management6 minutes
  • Content Automation Workflows Using AI6 minutes
  • AI-Assisted Video Editing, Formatting & Localization6 minutes
  • Scalability, Resource Savings & Quality Controls7 minutes
5 readingsTotal 55 minutes
  • Syllabus5 minutes
  • Glossary5 minutes
  • Creative AI Tools Matrix15 minutes
  • AI Creative Testing Case Studies15 minutes
  • Content Pipeline Automation Guide15 minutes
4 assignmentsTotal 105 minutes
  • AI for Creative Development & Content Automation60 minutes
  • Generating AI-Powered Creative Concepts & Variations15 minutes
  • AI-Driven Creative Testing (Hooks, Formats, Visuals)15 minutes
  • Automation in Creative Production & Content Pipelines15 minutes
1 discussion promptTotal 5 minutes
  • Can AI Really Create a Winning Campaign Idea?5 minutes
1 pluginTotal 5 minutes
  • Quick Course Check-In5 minutes

This module focuses on using AI to design personalized, privacy-aware marketing experiences across channels. Learners examine predictive audience modeling, behavioral signals, and automated targeting systems used by major advertising platforms. The module explores how AI-driven personalization improves relevance, engagement, and efficiency while addressing the challenges of scale and regulation. Learners design omnichannel journeys that adapt messaging and content delivery in real time, guided by AI performance signals. A strong emphasis is placed on privacy-first personalization, including zero-party data strategies, ethical frameworks, and compliance with global data regulations. The module also addresses a critical strategic challenge—balancing short-term performance optimization with long-term brand equity. By the end of this module, learners will be able to build responsible personalization strategies that drive measurable outcomes without compromising brand distinctiveness or consumer trust.

What's included

12 videos4 readings5 assignments

12 videosTotal 81 minutes
  • Behavioral Signals, Lookalike Modeling & Predictive Scoring6 minutes
  • Automated Targeting in Meta, TikTok, YouTube & Programmatic7 minutes
  • Evaluating Prediction-Based Audience Performance7 minutes
  • Designing Cross-Channel Personalized Journeys6 minutes
  • Content Delivery Optimization Using AI Signals6 minutes
  • How Personalization Affects Engagement, Efficiency & Brand Lift7 minutes
  • GDPR, CCPA & Global Privacy Regulations7 minutes
  • Zero-Party Data Collection & Value Exchange Models7 minutes
  • Ethical Personalization Frameworks7 minutes
  • Short-Term Performance vs Long-Term Brand Equity7 minutes
  • AI Optimization Risks to Brand Distinctiveness7 minutes
  • Designing Dual-KPI Campaign Systems7 minutes
4 readingsTotal 60 minutes
  • Audience Modeling Report15 minutes
  • Cross-Channel Journey Template15 minutes
  • Privacy-First Targeting Toolkit15 minutes
  • Brand–Performance Balance Playbook15 minutes
5 assignmentsTotal 120 minutes
  • Personalization, Targeting & Omnichannel Delivery60 minutes
  • AI-Driven Audience Modelling & Predictive Targeting15 minutes
  • Personalization at Scale Across Omnichannel Ecosystems15 minutes
  • Privacy-First Personalization & Zero-Party Data15 minutes
  • Balancing Brand Building & Performance Marketing15 minutes

This module equips learners with the frameworks and tools required to run continuous, data-driven optimization programs. Learners study experimentation methods such as A/B testing, multivariate testing, and sequential testing, with a focus on statistical validity and noise reduction. The module then advances into real-time optimization systems powered by AI—covering automated bidding, budget allocation, targeting adjustments, and live performance monitoring. Learners analyse dashboards to detect anomalies, interpret AI-generated signals, and decide when human intervention is necessary. The module also introduces automated experimentation platforms and continuous learning loops that enable always-on optimization. Finally, learners explore incrementality testing and lift studies to distinguish true causal impact from correlation-based attribution. By the end of this module, learners will be able to design reliable experiments, evaluate optimization outcomes, and make confident, evidence-based decisions in dynamic campaign environments.

What's included

12 videos4 readings5 assignments1 discussion prompt

12 videosTotal 61 minutes
  • A/B, Multivariate, Sequential Testing Explained4 minutes
  • Designing Experiments for Creative, Targeting & Media4 minutes
  • Sample Size, Statistical Significance & Noise5 minutes
  • AI Optimization Systems: Bidding, Budgets, Targeting5 minutes
  • Real-Time Dashboards: Detecting Patterns & Anomalies5 minutes
  • Intervention Decision-Making Using Live AI Signals5 minutes
  • Automated Testing Platforms (Meta Advantage+, Google Performance Max)6 minutes
  • Continuous Learning Systems & Feedback Loops5 minutes
  • Long-Term ROI from Always-On Optimization6 minutes
  • Why Attribution Is Not Enough: Correlation vs Causation5 minutes
  • Incrementality Testing, Holdouts & Lift Studies6 minutes
  • Using AI to Design & Interpret Incrementality Tests6 minutes
4 readingsTotal 60 minutes
  • Experimentation Framework Templates15 minutes
  • Optimization Workflow Guide15 minutes
  • Continuous Optimization Handbook15 minutes
  • Incrementality & Causal Testing Toolkit15 minutes
5 assignmentsTotal 120 minutes
  • Real-Time Optimization, A/B Testing & Automated Experimentation60 minutes
  • Designing Experimentation Frameworks15 minutes
  • Real-Time Optimization With AI Tools15 minutes
  • Automated Experimentation & Continuous Learning Systems15 minutes
  • Incrementality, Lift Studies & Causal Measurement15 minutes
1 discussion promptTotal 5 minutes
  • When Should AI Step In—and When Should You?5 minutes

This final module focuses on measuring impact, guiding investment decisions, and translating analytics into strategic growth actions. Learners explore advanced attribution models—including multi-touch, data-driven, and algorithmic approaches—to understand true channel contribution. The module also covers AI-powered performance dashboards, predictive KPIs, and forecasting techniques used to evaluate both short-term efficiency and long-term value. Learners examine how media mix modeling complements attribution by capturing long-term and cross-channel effects. In addition, the module addresses leadership-level challenges such as over-optimization risks, algorithmic bias, and governance of AI-driven systems. The course culminates in a capstone project where learners design, analyze, and present a complete AI-optimized brand campaign supported by dashboards and strategic reporting. By the end of this module, learners will be able to defend performance recommendations, guide budget allocation, and operate AI-driven campaign systems with strategic oversight.

What's included

16 videos5 readings6 assignments

16 videosTotal 103 minutes
  • Last-Click, MTA, DDA, Algorithmic Attribution6 minutes
  • Evaluating Channel Contribution with Advanced Models7 minutes
  • Budget Allocation Using Attribution Insights6 minutes
  • Building Performance Dashboards Using AI Tools7 minutes
  • Predictive KPIs: ROAS, CAC, LTV, Brand Lift Forecasting6 minutes
  • Interpreting Insights from AI-Based Reports5 minutes
  • Designing the Full Campaign System (Creative → Media → Optimization)5 minutes
  • Creating the Performance Dashboard7 minutes
  • Crafting the Strategic Performance Report6 minutes
  • What Is MMM & When to Use It7 minutes
  • How AI Is Modernizing MMM & Forecasting6 minutes
  • Using MMM Insights for Strategic Budget Allocation8 minutes
  • Over-Optimization Traps in AI-Driven Campaigns7 minutes
  • When Humans Must Override AI Systems7 minutes
  • Operating Models for AI-Driven Campaign Teams7 minutes
  • Course Closure - Gratitude !5 minutes
5 readingsTotal 65 minutes
  • Attribution Model Comparison Guide15 minutes
  • Dashboard & Reporting Templates15 minutes
  • Capstone Rubric & Submission Guide15 minutes
  • Case Study5 minutes
  • AI Campaign Operating Model & Risk Playbook15 minutes
6 assignmentsTotal 135 minutes
  • Attribution Modelling, Performance Reporting & AI-Driven Growth60 minutes
  • Attribution Modelling in AI-Driven Environments15 minutes
  • AI-Powered Performance Dashboards & Predictive KPIs15 minutes
  • Capstone: Build & Present an AI-Optimized Brand Campaign15 minutes
  • Media Mix Modelling (MMM) & Long-Term Growth Planning15 minutes
  • AI Risk, Over-Optimization & Leadership Decision-Making15 minutes

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Board Infinity
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Frequently asked questions

No coding or data science background is required. The course focuses on applying AI tools and frameworks through practical marketing workflows rather than technical model building.

You’ll work with tools like Chat GPT, Mid journey, Meta Advantage+, Google Performance Max, AI testing platforms, and performance dashboards. The emphasis is on real-world tools used by modern brand and performance teams.

This course covers both. You’ll learn how to use AI for performance optimization while protecting long-term brand equity through dual-KPI systems and experimentation guardrails.

The course is beginner-friendly but professionally deep. You’ll start with core AI concepts and progress to advanced use cases like incrementality testing, attribution modelling, and media mix modelling.

The course takes approximately 20–24 hours in total. Most learners complete it over 4 weeks with 5–6 hours of study per week.

Yes. You’ll complete a capstone project where you build a full AI-optimized brand campaign, including creative strategy, optimization logic, and a performance dashboard.

Absolutely. You’ll learn A/B testing, multivariate testing, automated experimentation, and incrementality measurement using AI-driven optimization systems.

The course includes dedicated lessons on GDPR, CCPA, zero-party data, and ethical personalization frameworks. You’ll learn how to design AI-driven campaigns that are privacy-safe and compliant.

This course is ideal for digital marketers, brand managers, performance marketers, marketing analysts, and professionals transitioning into AI-driven marketing roles.

Learners get practice quizzes, AI dialogues, graded assessments, templates, frameworks, and access to Board Infinity’s learner community and career resources.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,