Pideya Learning Academy

AI for Content Personalization and Ad Targeting

Upcoming Schedules

  • Live Online Training
  • Classroom Training

Date Venue Duration Fee (USD)
24 Feb - 28 Feb 2025 Live Online 5 Day 3250
31 Mar - 04 Apr 2025 Live Online 5 Day 3250
26 May - 30 May 2025 Live Online 5 Day 3250
23 Jun - 27 Jun 2025 Live Online 5 Day 3250
11 Aug - 15 Aug 2025 Live Online 5 Day 3250
01 Sep - 05 Sep 2025 Live Online 5 Day 3250
27 Oct - 31 Oct 2025 Live Online 5 Day 3250
24 Nov - 28 Nov 2025 Live Online 5 Day 3250

Course Overview

In an era dominated by algorithmic feeds, fragmented attention spans, and content overload, delivering personalized and context-aware digital experiences is no longer a competitive edge—it’s an essential business imperative. The AI for Content Personalization and Ad Targeting training by Pideya Learning Academy is designed to equip professionals with the strategic insights, technical knowledge, and ethical frameworks necessary to deploy intelligent marketing campaigns that resonate with audiences at scale.
Modern consumers expect brands to understand their preferences and behaviors across multiple touchpoints. Artificial Intelligence (AI) is the force powering this evolution, enabling marketers to move beyond basic demographic segmentation and embrace advanced personalization techniques driven by behavioral data, predictive analytics, and natural language processing (NLP). This training explores the full spectrum of AI applications in content strategy and ad delivery, helping participants learn how to build deeper, more meaningful digital connections.
Recent research underscores the growing importance of AI in marketing. According to McKinsey & Company, personalization can deliver five to eight times the ROI on marketing efforts and drive sales lifts of over 10%. Gartner highlights a 20% increase in customer satisfaction among organizations leveraging AI for personalized experiences. Meanwhile, Salesforce’s “State of Marketing” report reveals that 78% of marketers are now using AI for real-time personalization and 71% for audience segmentation and predictive modeling. These statistics reflect a fundamental industry shift toward data-driven engagement and automated optimization.
Participants of this Pideya Learning Academy course will gain a comprehensive understanding of how AI enhances both content personalization and targeted advertising across digital ecosystems. Throughout the course, learners will benefit from strategic takeaways such as:
Exploration of AI-powered recommendation engines and dynamic content delivery systems
Application of machine learning algorithms for audience segmentation and predictive targeting
Use of NLP to tailor content contextually based on user intent and language cues
Integration of AI in programmatic advertising to improve campaign accuracy and ROI
Understanding of data privacy, regulatory compliance, and ethical AI usage in personalization
Utilization of AI analytics for campaign performance enhancement and content optimization
Familiarity with leading AI platforms and tools used by global digital marketing teams
Each module focuses on building capabilities that bridge the gap between emerging AI technologies and real-world marketing strategies. The course emphasizes the importance of personalization frameworks that are both scalable and adaptable across channels—whether in content curation, email targeting, customer journey mapping, or digital ad placements.
As digital noise increases and customer expectations evolve, Pideya Learning Academy positions participants to lead with intelligent, user-centric marketing initiatives. By translating data into actionable insights and automated personalization workflows, learners will be empowered to deliver impactful experiences that drive user loyalty and increase brand value.
Whether you’re a marketing strategist, content specialist, data analyst, or digital campaign manager, this course prepares you to leverage AI for stronger audience alignment and optimized media investments. With the growing need for marketers who can orchestrate AI-powered personalization across multiple touchpoints, the skills gained through this training will remain in high demand across industries and regions.
Ultimately, this program is not just about understanding AI—it’s about mastering the transformation of digital marketing into a responsive, personalized, and performance-driven discipline. By completing the AI for Content Personalization and Ad Targeting course with Pideya Learning Academy, participants will be equipped to shape tomorrow’s marketing strategies using today’s most intelligent tools.

Course Objectives

After completing this Pideya Learning Academy training, the participants will learn to:
Identify key AI technologies enabling content personalization and targeted advertising.
Build AI-driven segmentation and user profiling models for marketing campaigns.
Apply NLP techniques for enhancing content relevance and personalization.
Optimize advertising strategies using predictive analytics and AI algorithms.
Utilize AI platforms for programmatic ad buying and campaign automation.
Address ethical, legal, and privacy considerations in AI-driven personalization.
Evaluate and refine personalization strategies using AI-generated analytics.

Personal Benefits

Build competitive expertise in AI-driven digital marketing strategies.
Master key personalization and targeting frameworks applicable across industries.
Develop critical understanding of AI analytics and performance measurement.
Increase professional value in data-driven, high-performance marketing roles.
Gain exposure to modern AI tools adopted by leading marketing departments.

Organisational Benefits

Enhance marketing ROI through precision targeting and data-driven personalization.
Improve customer satisfaction and retention with relevant and adaptive content.
Streamline digital advertising efforts using automation and AI decision-making.
Foster innovation by integrating AI into core marketing and campaign design.
Strengthen brand equity with consistent, tailored user experiences across platforms.

Who Should Attend

This course is ideal for:
Marketing and digital strategy professionals
Content managers and brand specialists
Data analysts and customer insights officers
Advertising executives and media planners
CRM and loyalty program managers
UX designers interested in content personalization
Anyone responsible for user engagement, campaign effectiveness, or marketing ROI
Detailed Training

Course Outline

Module 1: Foundations of AI in Marketing
Introduction to AI in digital marketing The shift from rule-based to learning-based personalization Key AI concepts: ML, NLP, and recommendation engines Overview of AI applications across the customer journey Types of personalization: explicit vs. implicit Common AI tools used in marketing Trends and future outlook
Module 2: User Profiling and Segmentation with AI
Behavioral, demographic, and psychographic data Supervised vs. unsupervised segmentation Lookalike modeling and clustering algorithms Persona development using AI insights Real-time data capture and modeling Dynamic audience profiling AI-based journey mapping
Module 3: Recommendation Engines and Personalization Models
Collaborative filtering techniques Content-based filtering and hybrid models Real-time vs. historical data modeling Personalized product/content recommendations Context-aware engines using NLP Cross-channel personalization strategies Model evaluation metrics (RMSE, Precision, Recall)
Module 4: NLP for Contextual and Dynamic Content
NLP in digital marketing: applications and tools Sentiment analysis for tone adjustment Topic modeling and keyword clustering Entity recognition for content tagging Text generation and content summarization AI-driven headline and CTA optimization Multilingual content adaptation
Module 5: Predictive Analytics in Ad Targeting
Forecasting consumer behavior using AI Conversion prediction models Churn prediction and re-engagement strategies Timing and frequency optimization AI in A/B testing and performance prediction Cross-device targeting strategies Campaign lift analysis
Module 6: Programmatic Advertising and AI Automation
Understanding programmatic ecosystems Real-time bidding and AI optimization Demand-side platforms and AI targeting Ad fraud detection using machine learning Bid strategy automation Contextual ad targeting Campaign performance optimization
Module 7: Ethics, Privacy, and Compliance in Personalization
AI transparency and accountability GDPR, CCPA, and global privacy frameworks Consent management and user rights Data anonymization and minimization AI bias in personalization algorithms Ethical segmentation strategies Auditing AI-driven campaigns
Module 8: Multichannel and Omnichannel Personalization
Synchronizing AI across web, mobile, email, and social Real-time personalization engines AI for personalized push notifications Channel-specific user behavior modeling Consistent experience orchestration Funnel-based targeting Attribution modeling with AI
Module 9: Measuring Campaign Effectiveness with AI
Attribution models enhanced by machine learning Sentiment-based performance analysis ROI prediction models Conversion rate optimization (CRO) frameworks Customer lifetime value modeling Personalization metrics and dashboards Continuous feedback loops using AI
Module 10: Future of AI in Marketing and AdTech
Generative AI in content ideation and curation AI in video and interactive content personalization Voice AI and hyper-personalized interfaces Predictive loyalty programs AI-powered user intent detection Integration with blockchain for ad transparency Preparing for AI-led marketing roles

Have Any Question?

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