How and What Marketing Algorithms Think 1st edition by Roberto Brognara ISBN 1527548066 978-1527548060

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ISBN 10: 1527548066
ISBN 13:  978-1527548060
Author: Roberto Brognara

This book argues that the apparent omnipotence of algorithms today is not what it seems, particularly, in marketing, where they actually offer less than they could. Considering the reasons behind this, it also notes that Big Data has relaunched a kind of data glorification and automated procedures that, culturally, marketing has already recognized and overcome at least once. This first generation of “programmatic marketing”, which the giants of the digital economy launched 15 years ago and consolidated worldwide, can be significantly improved, with corresponding business results as well, but, first, as this book shows, we need to know which strategic and cultural boundaries impact Big Data.

How and What Marketing Algorithms Think 1st Table of contents:

Introduction

• Understanding the Intersection of Algorithms and Marketing
• The Rise of Data-Driven Marketing
• How Algorithms Influence Marketing Decisions
• Purpose and Structure of the Book

Chapter 1: The Basics of Marketing Algorithms

• What are Marketing Algorithms?
• How Algorithms Process Data in Marketing
• A Brief Overview of Key Algorithmic Concepts
• The Role of Artificial Intelligence and Machine Learning in Marketing

Chapter 2: Algorithms and Consumer Behavior

• How Algorithms Analyze Consumer Data
• Predictive Models and Consumer Insights
• The Influence of Algorithms on Customer Journey Mapping
• Case Study: Algorithmic Insights into Customer Purchase Behavior

Chapter 3: Segmentation and Personalization

• How Algorithms Segment Customers
• Personalizing Content and Offers with Algorithms
• The Power of Behavioral Targeting and Retargeting
• Dynamic Pricing: How Algorithms Optimize Pricing Strategies

Chapter 4: Recommendation Systems and Marketing

• How Recommendation Algorithms Work
• Collaborative Filtering vs. Content-Based Filtering
• Personalized Product Recommendations and Their Impact on Sales
• Case Study: How Netflix and Amazon Use Recommendation Algorithms

Chapter 5: Algorithms in Digital Advertising

• The Role of Algorithms in Programmatic Advertising
• Real-Time Bidding and Ad Targeting Algorithms
• Optimizing Ad Campaigns with Machine Learning
• Understanding Algorithmic Decision-Making in Facebook and Google Ads

Chapter 6: Predictive Analytics in Marketing

• What is Predictive Analytics?
• How Algorithms Predict Consumer Behavior
• Lead Scoring and Sales Forecasting with Algorithms
• Using Predictive Analytics for Campaign Optimization

Chapter 7: Natural Language Processing and Content Marketing

• How Algorithms Understand and Generate Text
• The Role of NLP in Social Media and Content Strategy
• Sentiment Analysis: Analyzing Consumer Sentiment with Algorithms
• Case Study: Chatbots and AI in Customer Engagement

Chapter 8: Machine Learning and Marketing Automation

• How Machine Learning Powers Marketing Automation
• Automating Email Marketing with AI
• Algorithm-Driven Campaign Optimization
• Using Algorithms for A/B Testing and Continuous Improvement

Chapter 9: Data Ethics and Algorithmic Transparency

• The Ethical Implications of Marketing Algorithms
• Privacy Concerns and Data Usage in Marketing
• Building Trust with Algorithmic Transparency
• Addressing Bias in Algorithmic Decision-Making

Chapter 10: Algorithms and Social Media Marketing

• How Algorithms Drive Social Media Content Distribution
• Optimizing Social Media Strategies Using Data and Algorithms
• Algorithmic Influence on Engagement and Content Reach
• Case Study: How Instagram and Twitter Use Algorithms to Shape Content

Chapter 11: Measuring Success with Marketing Algorithms

• Key Performance Indicators (KPIs) and Algorithmic Metrics
• Using Algorithms for ROI Measurement and Campaign Performance
• Data-Driven Insights for Marketing Strategy Refinement
• How to Evaluate Algorithmic Success in Marketing

Chapter 12: The Future of Marketing Algorithms

• Emerging Trends in Marketing Algorithms
• The Impact of AI and Machine Learning on the Future of Marketing
• How Algorithms Will Shape the Marketing Landscape in the Coming Years
• Preparing for a More Automated and Data-Driven Marketing World

Conclusion

• Key Takeaways: How Algorithms Are Transforming Marketing
• Building a Data-Driven Marketing Strategy with Algorithms
• Next Steps for Marketers: Leveraging Algorithms for Success

Appendices

• A. Glossary of Key Terms in Marketing Algorithms
• B. Resources and Tools for Marketing Algorithms and AI
• C. Case Studies and Real-World Applications of Marketing Algorithms
• D. Further Reading and Research Recommendations

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