Course in Artificial Intelligence Applications in Smart Marketing Strategies

In a world witnessing rapid transformations in consumer behavior and continuous technological advancements, smart marketing is no longer optional—it is a strategic necessity for staying competitive. Advanced AI applications in smart marketing strategies have emerged as key drivers reshaping the global marketing landscape. Through advanced data analytics, content personalization, purchasing behavior prediction, and more, AI enhances the effectiveness and efficiency of marketing campaigns. This course, offered by Geneva Institute of Business Administration, aims to provide participants with a deep understanding of integrating AI into modern marketing systems to support strategic decision-making and achieve high engagement and ROI.

Target Audience

• Marketing managers and brand directors.

• Specialists in data analysis and consumer behavior.

• Professionals involved in digital strategy development.

• Startup owners seeking to leverage modern technologies in marketing.

Course Objectives

• Understand the role of AI in developing more effective marketing strategies.

• Learn how to analyze and interpret behavioral data using AI techniques.

• Explore AI applications in personalizing the customer marketing experience.

• Enhance participants’ ability to make data-driven marketing decisions based on accurate predictions.

Course Outline

 Advanced Concepts of AI in Marketing

• Evolution of artificial intelligence in the marketing context.

• Differences between marketing automation and intelligent AI.

• The role of algorithms in directing marketing campaigns.

• AI models used in market analysis.

 Marketing Data Structure and AI Integration

• Sources of digital marketing data.

• Building machine learning–ready databases.

• Analyzing unstructured data (images, text, video).

• The importance of data quality in AI outcomes.

 Content Personalization Using AI Techniques

• Using smart recommendations to guide marketing messages.

• Techniques for analyzing consumer behavior and preferences.

• Developing real-time personalized experiences.

• Tools for generating automated, audience-targeted content.

 Predicting Buying Behavior and Strategic Planning

• Predictable purchasing patterns through machine learning.

• Analyzing customer life cycles and buying decisions.

• Forecasting conversion and churn rates.

• Using predictive analytics to shape marketing strategies.

 Managing Smart Advertising Campaigns

• Automating campaign scheduling based on audience patterns.

• Enhancing ad performance using real-time analytics.

• Applying AI in testing advertising messages.

• Evaluating performance and adjusting campaigns instantly.

 Understanding Digital Voice and Sentiment Analysis

• Techniques for analyzing reviews and textual feedback.

• The role of AI in detecting impressions and emotions.

• Tracking emotional engagement with the brand.

• Using natural language processing to analyze market language.

 AI Tools for Marketing Decision Support

• Smart dashboards and real-time analytics.

• Comparing human and AI-supported decisions.

• Interaction between marketing teams and smart technologies.

• Building a data-driven culture within the marketing department.

 Using AI in Customer Relationship Management (CRM)

• AI-powered customer management systems.

• Automating responses and improving user experience.

• Understanding and analyzing the customer journey.

• Identifying high-value customers.

 AI and Omnichannel Consumer Behavior

• Understanding cross-channel navigation and its marketing impact.

• Integrating data from multiple touchpoints.

• Personalizing messages across various platforms.

• Utilizing AI for integrated channel marketing.

 Ethical and Technical Challenges in AI Marketing

• Data privacy and potential risks.

• Algorithmic bias and transparency.

• Legal and regulatory considerations in smart marketing.

• Ensuring responsible AI use in marketing.