Marketing with AI For Dummies (For Dummies (Business & Personal Finance))

Title Page
Copyright Page
Table of Contents
Introduction
	About This Book
	Foolish Assumptions
	Icons Used in This Book
	Beyond the Book
	Where to Go from Here
Part 1 Getting Started with Marketing with AI
	Chapter 1 A Brief History of AI
		Early Technological Advances
		Alan Turing and Machine Intelligence
			The Turing Test in 1950
			The Turing test: 1960s and beyond
		The Dartmouth Conference of 1956
		Machine Learning and Expert Systems Emerge
			Meeting machine learning
			Examining expert systems
		An AI Winter Sets In
		The Stanford Cart: From the ’60s to the ’80s
		More AI Developments in the 1980s
		Rapid Advancements of AI in the 1990s and Beyond
			Watching machine learning grow up
			Playing a pivotal chess match
			Tracking the deep learning revolution
			Demonstrating intuition in the age of AI
			Creating content with generative AI
	Chapter 2 Exploring AI Business Use Cases
		Automating Customer Service
			Serving customers by using chatbots
			Resolving customer issues with virtual assistants
			Seeking out trends and solutions with sentiment analysis
		Enhancing Product and Technology with AI
			Streamlining product validation
			Simulating user experience testing
			Writing code
			Detecting and resolving software bugs
			Testing software and creating documentation
		Accelerating Research and Development
			Generating and exploring ideas
			Extracting insights from data
			Optimizing product designs and production processes
		Giving Marketing an AI Boost
			Creating coherent, consistent content
			Personalizing marketing messages
			Managing digital advertising
			Streamlining search engine optimization (SEO)
		Optimizing Sales with AI
			Driving profitability
			Nurturing leads
			Forecasting sales
		Adding AI to Legal Activities
			Analyzing documentation for legal research
			Evaluating and drafting contracts
			Performing due diligence
			Managing intellectual property
	Chapter 3 Launching into the AI Marketing Era
		Ready or Not: AI Is Your New Marketing Copilot
			Putting performance marketers at risk
			Competing with creative directors
		Watching AI Upend the Corporate World
		Taking Foundational Steps Toward AI Marketing
			Addressing the marketing dichotomy
			Assessing progress with the AI checklist
		Adopting a Strategic Framework for Entering the AI Era
			Going for liftoff
			Initiating atmospheric ascent
			Reaching escape velocity
			Dominating deep space
Part 2 Exploring Fundamental AI Structures and Concepts
	Chapter 4 Collecting, Organizing, and Transforming Data
		Defining Data in the Context of AI
			Considering the quality of data
			Getting an appropriate quantity of data
		Choosing Data Collection Methods for Marketing with AI
			Identifying data sources and methods
			Minding data privacy and ethics
		Putting Your Marketing Data in Its Place
		Understanding Data via Manual and Automated Systems
		Preparing the Data for Use by AI Algorithms and Models
			Perfecting data by cleaning
			Transforming data
			Splitting data into subsets
			Trimming down data
			Handling imbalanced and irrelevant data
	Chapter 5 Making Connections: Machine Learning and Neural Networks
		Examining the Process of Machine Learning
		Understanding Neural Networks
			Layers of a neural network
			Challenges with neural networks
		Supervised and Unsupervised Learning
			Following the path of supervised learning
			Embracing the freedom of unsupervised learning
		Exploring Reinforcement Learning
			Reinforcement learning in e-mail marketing
			Weighing explorations against exploits
		Mastering Sequences and Time Series
			Seeing how neural networks excel at time series analysis
			Embracing time series features, challenges, and tools
		Developing Vision and Image Processing in AI
			Exploiting the power of convolutional neural networks (CNNs)
			Looking deeper: Advanced vision techniques
		Tools for Machine Learning and Neural Networks
			Participating with Python
			Diving into deep learning platforms
	Chapter 6 Adding Natural Language Processing and Sentiment Analysis
		Demystifying the Backbone of NLP
			Exploring linguistics for NLP
			Seeing the big picture with statistical NLP
			Why linguistics and NLP both matter
		Elevating NLP with Machine Learning
			Integrating NLP and machine learning
			Adapting to the emotional spectrum
		Examining Transformers and Attention Mechanisms
		Unpacking Sentiment Analysis
			Catching the feeling
			Understanding language nuances
			Integrating social media analytics
		Challenges for NLP and Sentiment Analysis
		Engaging Best Practices for Using NLP and Sentiment Analysis
	Chapter 7 Collaborating via Predictions, Procedures, Systems, and Filtering
		Understanding Predictive Analytics
			Using predictive analytics in various industries
			Building predictive models
			Best practices for predictive analytics
		Putting AI Procedures into Practice
		The AI System Development Lifecycle
		Understanding Filtering in AI
			Knowing where you encounter filtering
			AI filtering in recommendation systems
	Chapter 8 Getting Comfortable with Generative AI
		Changing the Game with Generative AI
			Knowing core generative AI concepts and techniques
			Reviewing the training process for generative AI models
		Getting to Know GPT Models
			Training the models is intensive
			Exploring the models’ operation
		Creating New Text, Images, and Video
			Generating text
			Creating images
			Producing video
		Introducing Major Consumer-Facing Generative AI Models
		Addressing the Challenges of Using Generative AI Models
			Seeing the technical challenges and limitations
			Exposing ethical and societal consequences
Part 3 Using AI to Know Customers Better
	Chapter 9 Segmentation and Persona Development
		Exploring Behavioral Segmentation Elements
		Sourcing the Right Customer Data
		Seeing How AI Performs Segmentation
		Refining, Validating, and Enhancing Segmentation Models
			Two aspects of AI model refinement
			Validation techniques
		Aligning Persona Development
			Verifying the authentic core of AI-created personas
			Ethical considerations in persona development
		Leveraging AI Personas for All Business Efforts
			Driving the customer experience
			Directing marketing with personas
			Aligning product offerings with personas
		Employing Synthetic Customer Panels
			Creating synthetic panels
			Embracing the opportunities
			Managing the risks
	Chapter 10 Lead Scoring, LTV, and Dynamic Pricing
		Working Together: Three Core Concepts
			Identifying potential leads
			Maximizing customer potential
			Adapting to market conditions on the fly
		Scoring Leads with the Help of AI
			Instilling precision with AI solutions
				Leveraging machine learning algorithms
				Achieving precision through predictive analytics
				Enhancing customer interfaces (and experiences) with AI
				Validating AI-powered lead scoring via empirical evidence
			Enhancing data analysis with AI tools
			Finding companies that offer AI-infused lead-scoring capabilities
		Calculating Lifetime Value to Affect Lead Scoring
			Allowing for predictive customer analysis
			Finding companies that offer AI-infused LTV calculations
		Turning Lead Scoring and LTV Insights into Dynamic Pricing
	Chapter 11 Churn Modeling and Measurement with AI
		Getting the Scoop on Churn Modeling
			Building your churn model
			Validating, calibrating, and integrating your churn model
			Improving churn insights with generative AI
			Combating churn with customer retention strategies
				Personalizing customer interactions
				Enhancing customer support
				Implementing loyalty programs
				Conducting regular feedback and follow-up initiatives
				Using exit surveys and win-back campaigns
		Ramping Up Your Measurement Operations
			Letting AI drive data collection and monitoring
			Optimizing measurement operations with AI techniques
			Incorporating visualization and reporting solutions
		Checking Out Tools for Churn Modeling and Measurement Operations
Part 4 Transforming Brand Content and Campaign Development
	Chapter 12 Using AI for Ideation and Planning
		Engaging AI to Ideate on Behalf of Human Beings
		Deciding whether AI Hallucinations Are a Feature or a Bug
			Bringing in unexpected ideas and concepts
			Branching out with non-traditional storytelling
			Facilitating testing and experimentation
			Staying the course with generative AI
		Following Practical Steps for Idea Generation with AI
			Starting with the right prompts
			Stepping through an AI-for- ideation exercise
		Deciding on AI Ideation Tools to Use
	Chapter 13 Perfecting Prompts for Conversational Interfaces
		Reviewing Use Cases for Conversational Interfaces
		Writing Strong Prompts to Guide AI Responses
			Setting the voice and tone
			Defining a role
			Identifying the AI’s task
			Specifying the format
		Good and Bad Marketing Prompt Design Examples
		Refining and Iterating Strong Prompts
		Fighting AI Bias in Prompt Writing
		Using Prompt Design Apps
	Chapter 14 Developing Creative Assets
		Trying Out an AI-Generated Where’s Waldo? Illustration
		Exploring an Approach for Creating Visual Assets with AI
			Minding the integrity of your customers, data, and teams
			Examining an example scenario
		Enhancing Existing Creative Assets
			Enhancing and restoring images
			Enhancing and clarifying audio
			Analyzing and editing video
			Adding and modifying content
		Fine-Tuning Creativity with AI Tools and Techniques
			Crafting descriptions for image creation
			Automating creative production
			Tips and tricks for producing attention-grabbing creative assets
		Choosing AI Tools for Creating Visual Assets
	Chapter 15 Search Engine Optimization (SEO) in the AI Era
		Describing Search Generative Experiences (SGEs)
			Enhanced interpretation of queries
			Personalized search results
		Strategies for SEO Success in the AI Era
		Enhancing the User Experience with AI
		Maximizing Your SEO Efforts
			Streamlining keyword and metadata research
			Automating content optimization
			Building SEO links
			Harnessing predictive SEO
		Knowing the AI Tools to Use with SEO
	Chapter 16 Performing A/B Testing with AI
		Examining the Fundamentals of A/B Testing
			Reviewing the process of A/B testing
			Designing and implementing AI-driven testing
				Initiating the testing process
				Deploying machine learning models
				Infusing the testing process with integrity
		Surveying A/B Testing Extensions
			Taking advantage of split testing
			Maximizing multivariate testing
			Tracing a path with multi-page testing
		Gathering AI Tools for A/B Testing
	Chapter 17 Fine-Tuning Content with Localization and Translation
		Exploiting AI for Localization and Translation
			Capturing cultural context
			Harnessing multilingual large language models
			Applying AI’s capabilities
			Checking out AI tools you can use
		Adopting Core Strategies for Localization
			Leveraging machine learning
			Adopting AI-driven cultural adaptation tools
			Enhancing personalization and localization efficiency
			Controlling quality when using AI
		Examining Real-Time Localization and Translation Solutions
			Seeing how real-time solutions work
			Recognizing the benefits of real-time solutions
			Applying real-time solutions in marketing
Part 5 Targeting Growth Marketing and Customer Focus with AI
	Chapter 18 Applying AI to Performance Marketing
		Examining Google Performance Max
			Smart Bidding and asset creation
			Marketing outreach
			Creating your Performance Max campaign
		Exploring Meta Advantage+ Campaigns
			Looking at campaign features
			Reaping campaign benefits
			Taking form: App and shopping campaigns
				Features of the app campaigns
				Precise targeting with shopping campaigns
			Deriving your Advantage+ campaign
		Inspecting Amazon Ads
			Meeting the types of Amazon Ads
			Zeroing in on targeting mechanisms
			Paying and measuring performance
			Creating and running Amazon Ads
		Taking Stock of TikTok Advertising
			Following TikTok ad formats
			Exploring targeting capabilities
			TikTok ad campaign logistics
		AI Tools for Performance Marketing
	Chapter 19 E-mail and SMS Marketing with AI
		Tracking E-mail and SMS Marketing
			Recognizing the breadth of use
			Personalizing direct message marketing
		Adding the Power of AI to E-mail and SMS Marketing
			Incorporating predictive analytics to engage customers
			Tracking metrics and forecasting customer behavior
			Infusing e-mail campaigns with AI
			Infusing SMS campaigns with AI
		AI-Powered E-mail and SMS Marketing Tools
	Chapter 20 Diving into Personalized Marketing
		Adapting Marketing to Meet Consumer Personalization Preferences
			Bringing in the past
			Responding in real time or future time
			Providing customer service, consistency, and privacy
		Examining Personalization Concepts
			Describing elements of personalization
			Recognizing AI’s many roles
		Unlocking the Deeper Value of Personalization with Generative AI
		Making Personalization Operational with AI
			Establish clear objectives and metrics
			Institute data management
			Build detailed customer profiles
			Deploy predictive analytics
			Generate personalized content
			Test and optimize continuously
			Incorporate customer feedback
			Ensure compliance and ethical standards
			Train teams and manage change
			Plan for scalability
		AI Tools to Help with Personalization
	Chapter 21 Leading Your Business in the AI Era
		Following Steps for Integrating AI into Your Business
		Building AI Capability within Marketing
			Examining the approach of the U.S. federal government
			Framing your approach to AI in marketing
				AI procurement policies
				Executive alignment on AI strategy
				Function-specific AI policies
				Function-specific use cases
				Progress metrics and assessment frameworks
				Leadership and organizational structure
				Stakeholder protection measures
				Talent development
		Integrating Marketing with the Rest of the Enterprise
			Recognizing marketing’s vulnerability
			Embracing the AI transformation
				Transform before you’re transformed
				Practice, practice, practice
				Adopt asymmetrical networking
				Cut through the noise and embrace informative AI resources
				Don’t forget about marketing fundamentals
		Organizing for the Future
			Shifting culture to adopt AI
			Adapting organizational structure to embrace AI
	Chapter 22 Addressing Ethical, Legal, and Privacy Concerns with AI
		Operating Principles for Ethical AI
			Transparency
			Accountability
			Privacy protection
			Fairness
			Human-centric AI
			System safety and security
			Social responsibility
		Using All Data Responsibly
			Using private data responsibly
			Using public data responsibly
			Practicing responsible data use
		Fighting Bias in Data and Results
		Protecting Copyright and Intellectual Property
			Avoiding infringement
			Declaring ownership
			Safeguarding your own creations
		Facing the Deepfake Problem
			Society’s approach to deepfakes
			What marketers can do to fight deepfakes
		Saving Human Beings from Artificial Intelligence
			Adopting human-centered AI design
			Establishing clear ethical guidelines for using AI
			Continuous learning and skill development
			Participating in regulatory compliance and advocacy
			Implementing oversight mechanisms
Part 6 The Part of Tens
	Chapter 23 Tens Pitfalls to Avoid When Marketing with AI
		Ignoring Qualitative Insights
		Depending Solely on Generated Personas
		Relying Only on AI for Creative Briefs
		Bypassing Human Creativity
		Losing Your Brand Voice
		Neglecting Emerging Media Channels
		Over-Optimizing for Short-Term Goals
		Creeping Customers Out
		Ignoring the Value of the Human Touch
		Relying Solely on AI for ROI Analysis
	Chapter 24 Ten Future AI Developments to Watch For
		Quantum Computing–Aided AI
		Autonomous Creative Campaigns
		Cognitive AI Systems for Deep Insights
		AI-Driven Virtual Reality Experiences
		Neural Interface for Marketing Insights
		AI-Curated Personal Digital Realities
		Synthetic Media for Dynamic Content
		Predictive World Modeling
		AI as a Customer Behavior Simulator
		Molecular-Level Product Customization
Index
EULA