Data-Driven AI Marketing Strategies
( 30 Modules )

Module #1
Introduction to Data-Driven AI Marketing
Overview of the importance of data and AI in modern marketing, and what to expect from this course

Module #2
Understanding Your Customer
How to collect and analyze customer data to create accurate personas and target audiences

Module #3
AI Fundamentals for Marketers
Introduction to artificial intelligence, machine learning, and natural language processing concepts

Module #4
Data Sources for AI Marketing
Overview of various data sources, including customer data, social media, and IoT devices

Module #5
Data Quality and Preprocessing
Best practices for ensuring data quality, cleaning, and preprocessing for AI model training

Module #6
Introduction to Predictive Analytics
Overview of statistical modeling and machine learning for predictive analytics

Module #7
Building Customer Propensity Models
Using predictive analytics to identify customer segments and predict behavior

Module #8
AI-Powered Customer Segmentation
Using clustering and other AI techniques to identify high-value customer segments

Module #9
Personalization Strategies
Using data and AI to deliver personalized messages, offers, and experiences

Module #10
Content Generation and Curation
Using AI to generate and curate content, including natural language processing and computer vision

Module #11
AI-Driven Email Marketing
Using AI to optimize email campaigns, including subject lines, send times, and content

Module #12
Chatbots and Conversational Marketing
Using AI-powered chatbots to deliver customer service and support

Module #13
Social Media Listening and Analysis
Using natural language processing and machine learning to analyze social media conversations

Module #14
Influencer Identification and Scoring
Using AI to identify and score influencer partnerships

Module #15
Customer Journey Mapping and Optimization
Using data and AI to map and optimize customer journeys

Module #16
Marketing Attribution and ROI Analysis
Using data and AI to measure marketing attribution and ROI

Module #17
AI Ethics and Governance
Best practices for ensuring ethical and responsible AI use in marketing

Module #18
Implementing AI Marketing Strategies
Practical considerations for implementing AI marketing strategies in your organization

Module #19
Measuring and Evaluating AI Marketing Success
Metrics and KPIs for measuring the success of AI marketing strategies

Module #20
Case Studies in AI Marketing
Real-world examples of successful AI marketing strategies and campaigns

Module #21
The Future of AI in Marketing
Expert insights and predictions for the future of AI in marketing

Module #22
AI Tools and Platforms for Marketers
Overview of popular AI tools and platforms for marketers, including Salesforce Einstein and HubSpot

Module #23
Building an AI Marketing Team
Best practices for building and managing an AI marketing team, including roles and skills

Module #24
Change Management and Adoption
Strategies for driving adoption and change management in the organization

Module #25
Budgeting and Resource Allocation
Practical considerations for budgeting and resource allocation for AI marketing initiatives

Module #26
AI Marketing for B2B and Account-Based Marketing
Special considerations for applying AI marketing strategies in B2B and account-based marketing

Module #27
AI Marketing for E-commerce and Retail
Special considerations for applying AI marketing strategies in e-commerce and retail

Module #28
AI Marketing for Non-Profit and Social Impact
Special considerations for applying AI marketing strategies in non-profit and social impact organizations

Module #29
Advanced AI Techniques for Marketers
Advanced AI concepts, including deep learning and reinforcement learning

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Data-Driven AI Marketing Strategies career

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Data-Driven AI Marketing Strategies ( 30 Modules )

Data-Driven AI Marketing Strategies
( 30 Modules )