AI in marketing, sales and service: how marketers without a data science degree can use AI, big data and bots

By: Gentsch, Peter
Material type: TextTextPublisher: Cham Springer Nature 2019Description: xix, 271 p.: col. ill. Includes bibliographical references and indexISBN: 9783030079048Subject(s): Marketing research | Industrial management | Marketing - Data processing | Big data | Artificial intelligenceDDC classification: 658.80028563 Summary: AI and Algorithmics have already optimized and automated production and logistics processes. Now it is time to unleash AI on the administrative, planning and even creative procedures in marketing, sales and management. This book provides an easy-to-understand guide to assessing the value and potential of AI and Algorithmics. It systematically draws together the technologies and methods of AI with clear business scenarios on an entrepreneurial level. With interviews and case studies from those cutting edge businesses and executives who are already leading the way, this book shows you: how customer and market potential can be automatically identified and profiled; how media planning can be intelligently automated and optimized with AI and Big Data; how (chat)bots and digital assistants can make communication between companies and consumers more efficient and smarter; how you can optimize Customer Journeys based on Algorithmics and AI; and how to conduct market research in more efficient and smarter way. A decade from now, all businesses will be AI businesses – Gentsch shows you how to make sure yours makes that transition better than your competitors. https://www.palgrave.com/gp/book/9783319899565
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Table of contents:

pt. I AI 101
1.AI Eats the World
1.1.AI and the Fourth Industrial Revolution
1.2.AI Development: Hyper, Hyper...
1.3.AI as a Game Changer
1.4.AI for Business Practice
Reference
2.A Bluffer's Guide to AI, Algorithmic and Big Data
2.1.Big Data-More Than "Big"
2.1.1.Big Data-What Is Not New
2.1.2.Big Data-What Is New
2.1.3.Definition of Big Data
2.2.Algorithms-The New Marketers?
2.3.The Power of Algorithms
2.4.AI the Eternal Talent Is Growing Up
2.4.1.AI-An Attempt at a Definition
2.4.2.Historical Development of AI
2.4.3.Why AI Is Not Really Intelligent-And Why That Does Not Matter Either
References
pt. II AI Business: Framework and Maturity Model
3.AI Business: Framework and Maturity Model
3.1.Methods and Technologies
3.1.1.Symbolic AI
3.1.2.Natural Language Processing (NLP)
3.1.3.Rule-Based Expert Systems
3.1.4.Sub-symbolic AI
3.1.5.Machine Learning
3.1.6.Computer Vision and Machine Vision
3.1.7.Robotics
3.2.Framework and Maturity Model
3.3.AI Framework-The 360° Perspective
3.3.1.Motivation and Benefit
3.3.2.The Layers of the AI Framework
3.3.3.AI Use Cases
3.3.4.Automated Customer Service
3.3.5.Content Creation
3.3.6.Conversational Commerce, Chatbots and Personal Assistants
3.3.7.Customer Insights
3.3.8.Fake and Fraud Detection
3.3.9.Lead Prediction and Profiling
3.3.10.Media Planning
3.3.11.Pricing
3.3.12.Process Automation
3.3.13.Product/Content Recommendation
3.3.14.Sales Volume Prediction
3.4.AI Maturity Model: Process Model with Roadmap
3.4.1.Degrees of Maturity and Phases
3.4.2.Benefit and Purpose
3.5.Algorithmic Business-On the Way Towards Self-Driven Companies
3.5.1.Classical Company Areas
3.5.2.Inbound Logistics
3.5.3.Production
3.5.4.Controlling
3.5.5.Fulfilment
3.5.6.Management
3.5.7.Sales/CRM and Marketing
3.5.8.Outbound Logistics
3.6.Algorithmic Marketing
3.6.1.AI Marketing Matrix
3.6.2.The Advantages of Algorithmic Marketing
3.6.3.Data Protection and Data Integrity
3.6.4.Algorithms in the Marketing Process
3.6.5.Practical Examples
3.6.6.The Right Use of Algorithms in Marketing
3.7.Algorithmic Market Research
3.7.1.Man Versus Machine
3.7.2.Liberalisation of Market Research
3.7.3.New Challenges for Market Researchers
3.8.New Business Models Through Algorithmics and AI
3.9.Who's in Charge
3.9.1.Motivation and Rationale
3.9.2.Fields of Activity and Qualifications of a CAIO
3.9.3.Role in the Scope of Digital Transformation
3.9.4.Pros and Cons
3.10.Conclusion
pt. III Conversational AI: How (Chat) Bots Will Reshape the Digital Experience
4.Conversational AI: How (Chat) Bots Will Reshape the Digital Experience
4.1.Bots as a New Customer Interface and Operating System
4.1.1.(Chat) Bots: Not a New Subject-What Is New?
4.1.2.Imitation of Human Conversation
4.1.3.Interfaces for Companies
4.1.4.Bots Meet AI-How Intelligent Are Bots Really?
4.1.5.Mitsuku as Best Practice AI-Based Bot
4.1.6.Possible Limitations of AI-Based Bots
4.1.7.Twitter Bot Tay by Microsoft
4.2.Conversational Commerce
4.2.1.Motivation and Development
4.2.2.Messaging-Based Communication Is Exploding
4.2.3.Subject-Matter and Areas
4.2.4.Trends That Benefit Conversational Commerce
4.2.5.Examples of Conversational Commerce
4.2.6.Challenges for Conversational Commerce
4.2.7.Advantages and Disadvantages of Conversational Commerce
4.3.Conversational Office
4.3.1.Potential Approaches and Benefits
4.3.2.Digital Colleagues
4.4.Conversational Home
4.4.1.The Butler Economy-Convenience Beats Branding
4.4.2.Development of the Personal Assistant
4.5.Conversational Commerce and AI in the GAFA Platform Economy
4.6.Bots in the Scope of the CRM Systems of Companies
4.6.1."Spooky Bots"-Personalised Dialogues with the Deceased
4.7.Maturity Levels and Examples of Bots and AI Systems
4.7.1.Maturity Model
4.8.Conversational AI Playbook
4.8.1.Roadmap for Conversational AI
4.8.2.Platforms and Checklist
4.9.Conclusion and Outlook
4.9.1.E-commerce-The Deck Is Being Reshuffled: The Fight for the New E-commerce Eco System
4.9.2.Markets Are Becoming Conversations at Last
pt. IV AI Best and Next Practices
5.AI Best and Next Practices
5.1.Sales and Marketing Reloaded-Deep Learning Facilitates New Ways of Winning Customers and Markets
5.1.1.Sales and Marketing 2017
5.1.2.Analogy of the Dating Platform
5.1.3.Profiling Companies
5.1.4.Firmographics
5.1.5.Topical Relevance
5.1.6.Digitality of Companies
5.1.7.Economic Key Indicators
5.1.8.Lead Prediction
5.1.9.Prediction Per Deep Learning
5.1.10.Random Forest Classifier
5.1.11.Timing the Addressing
5.1.12.Alerting
5.1.13.Real-World Use Cases
5.2.Digital Labor and What Needs to Be Considered from a Costumer Perspective
5.2.1.Acceptance of Digital Labor
5.2.2.Trust Is the Key
5.2.3.Customer Service Based on Digital Labor Must Be Fun
5.2.4.Personal Conversations on Every Channel or Device
5.2.5.Utility Is a Key Success Factor
5.2.6.Messaging Is Not the Reason to Interact with Digital Labor
5.2.7.Digital Labor Platform Blueprint
5.3.Artificial Intelligence and Big Data in Customer Service
5.3.1.Modified Parameters in Customer Service
5.3.2.Voice Identification and Voice Analytics
5.3.3.Chatbots and Conversational UI
5.3.4.Predictive Maintenance and the Avoidance of Service Issues
5.3.5.Conclusion: Developments in Customer Service Based on Big Data and AI
5.4.Customer Engagement with Chatbots and Collaboration Bots: Methods, Chances and Risks of the Use of Bots in Service and Marketing
5.4.1.Relevance and Potential of Bots for Customer Engagement
5.4.2.Overview and Systemisation of Fields of Use
5.4.3.Abilities and Stages of Development of Bots
5.4.4.Some Examples of Bots That Were Already Used at the End of 2016
5.4.5.Proactive Engagement Through a Combination of Listening and Bots
5.4.6.Cooperation Between Man and Machine
5.4.7.Planning and Rollout of Bots in Marketing and Customer Service
5.4.8.Factors of Success for the Introduction of Bots
5.4.9.Usability and Ability to Automate
5.4.10.Monitoring and Intervention
5.4.11.Brand and Target Group
5.4.12.Conclusion
5.5.The Bot Revolution Is Changing Content Marketing-Algorithms and AI for Generating and Distributing Content
5.5.1.Robot Journalism Is Becoming Creative
5.5.2.More Relevance in Content Marketing Through AI
5.5.3.Is a Journalist's Job Disappearing?
5.5.4.The Messengers Take Over the Content
5.5.5.The Bot Revolution Has Announced Itself
5.5.6.A Huge Amount of Content Will Be Produced
5.5.7.Brands Have to Offer Their Content on the Platforms
5.5.8.Platforms Are Replacing the Free Internet
5.5.9.Forget Apps-The Bots Are Coming!
5.5.10.Competition Around the User's Attention Is High
5.5.11.Bots Are Replacing Apps in Many Ways
5.5.12.Companies and Customers Will Face Each Other in the Messenger in the Future
5.5.13.How Bots Change Content Marketing
5.5.14.Examples of News Bots
5.5.15.Acceptance of Chat Bots Is Still Controversial
5.5.16.Alexa and Google Assistant: Voice Content Will Assert Itself
5.5.17.Content Marketing Always Has to Align with Something New
5.5.18.Content Marketing Officers Should Thus Today Prepare Themselves for a World in Which ...
5.6.Chatbots: Testing New Grounds with a Pinch of Pixie Dust?
5.6.1.Rogue One: A Star Wars Story-Creating an Immersive Experience
5.6.2.Xmas Shopping: Providing Service and Comfort to Shoppers with Disney Fun
5.6.3.Do You See Us?
5.6.4.Customer Services, Faster Ways to Answer Consumers' Request
5.6.5.A Promising Future
5.6.6.Three Takeaways to Work on When Creating Your Chatbot
5.7.Alexa Becomes Relaxa at an Insurance Company
5.7.1.Introduction: The Health Care Market-The Next Victim of Disruption?
5.7.2.The New Way of Digital Communication: Speaking
5.7.3.Choice of the Channel for a First Case
5.7.4.The Development of the Skill "TK Smart Relax"
5.7.5.Communication of the Skill
5.7.6.Target Achievement
5.7.7.Factors of Success and Learnings
5.8.The Future of Media Planning
5.8.1.Current Situation
5.8.2.Software Eats the World
5.8.3.New Possibilities for Strategic Media Planning
5.8.4.Media Mix Modelling Approach
5.8.5.Giant Leap in Modelling
5.8.6.Conclusion
5.9.Corporate Security: Social Listening, Disinformation and Fake News
5.9.1.Introduction: Developments in the Process of Early Recognition
5.9.2.The New Threat: The Use of Bots for Purposes of Disinformation
5.9.3.The Challenge: "Unkown Unknowns"
5.9.4.The Solution Approach: GALAXY-Grasping the Power of Weak Signals
5.10.Next Best Action-Recommender Systems Next Level
5.10.1.Real-Time Analytics in Retail
5.10.2.Recommender Systems
5.10.3.Reinforcement Learning
5.10.4.Reinforcement Learning for Recommendations
5.10.5.Summary
5.11.How Artificial Intelligence and Chatbots Impact the Music Industry and Change Consumer Interaction with Artists and Music Labels
5.11.1.The Music Industry
5.11.2.Conversational Marketing and Commerce
5.11.3.Data Protection in the Music Industry
5.11.4.Outlook into the Future
pt. V Conclusion and Outlook: Algorithmic Business-Quo Vadis?
6.Conclusion and Outlook: Algorithmic Business
6.1.Super Intelligence: Computers Are Taking Over-Realistic Scenario or Science Fiction?
6.1.1.Will Systems Someday Reach or Even Surmount the Level of Human Intelligence?
6.2.AI: The Top 11 Trends of 2018 and Beyond
6.3.Implications for Companies and Society

AI and Algorithmics have already optimized and automated production and logistics processes. Now it is time to unleash AI on the administrative, planning and even creative procedures in marketing, sales and management.
This book provides an easy-to-understand guide to assessing the value and potential of AI and Algorithmics. It systematically draws together the technologies and methods of AI with clear business scenarios on an entrepreneurial level.
With interviews and case studies from those cutting edge businesses and executives who are already leading the way, this book shows you:
how customer and market potential can be automatically identified and profiled;
how media planning can be intelligently automated and optimized with AI and Big Data;
how (chat)bots and digital assistants can make communication between companies and consumers more efficient and smarter;
how you can optimize Customer Journeys based on Algorithmics and AI; and
how to conduct market research in more efficient and smarter way.
A decade from now, all businesses will be AI businesses – Gentsch shows you how to make sure yours makes that transition better than your competitors.

https://www.palgrave.com/gp/book/9783319899565

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