Marketing with AI for Dummies
Marketing with AI For Dummies is your introduction to the revolution that’s occurring in the marketing industry, thanks to artificial intelligence tools that can create text, images, audio, video, websites, and beyond. This book captures the insight of leading marketing executive Shiv Singh on how A...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
John Wiley & Sons, Inc
[2025]
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| Edición: | First edition |
| Colección: | --For dummies.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009850436606719 |
Tabla de Contenidos:
- Intro
- 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.
