Arvind Sathi
Engaging Customers Using Big Data (eBook, PDF)
How Marketing Analytics Are Transforming Business
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Arvind Sathi
Engaging Customers Using Big Data (eBook, PDF)
How Marketing Analytics Are Transforming Business
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Data is transforming how and where we market to our customers. Using a series of case studies from pioneers, this book will describe how each marketing function is undergoing fundamental changes, and provides practical guidance about how companies can learn the tools and techniques to take advantage of marketing analytics.
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Data is transforming how and where we market to our customers. Using a series of case studies from pioneers, this book will describe how each marketing function is undergoing fundamental changes, and provides practical guidance about how companies can learn the tools and techniques to take advantage of marketing analytics.
Produktdetails
- Produktdetails
- Verlag: Palgrave Macmillan US
- Erscheinungstermin: 15. März 2017
- Englisch
- ISBN-13: 9781137386199
- Artikelnr.: 53152535
- Verlag: Palgrave Macmillan US
- Erscheinungstermin: 15. März 2017
- Englisch
- ISBN-13: 9781137386199
- Artikelnr.: 53152535
Dr. Arvind Sathi is the World Wide Communication Sector Architect for Big Data at IBM®. Dr. Sathi received his Ph.D. in Business Administration from Carnegie Mellon University and worked under Nobel Prize winner Dr. Herbert A. Simon. Dr. Sathi is a seasoned professional with more than 20 years of leadership in Information Management architecture and delivery. His primary focus has been in creating visions and roadmaps for Advanced Analytics at leading IBM clients in Telecommunications, Media & Entertainment, and Energy & Utilities organizations, worldwide. He has conducted a number of workshops on Big Data assessment and roadmap development.
Prior to joining IBM, Dr. Sathi was the pioneer in developing knowledge-based solutions for CRM at Carnegie Group. At BearingPoint, he led the development of Enterprise Integration, MDM, and Operations Support Systems/Business Support Systems (OSS/BSS) solutions for the communications market and also developed horizontal solutions for communications, financial services, and public services. At IBM, Dr. Sathi has led several Information Management programs in MDM, data security, business intelligence, advanced analytics, big data and related areas and has provided strategic architecture oversight to IBM's strategic accounts. He has also delivered a number of workshops and presentations at industry conferences on technical subjects including MDM and data architecture, and he holds two patents in data masking. His first book'Customer Experience Analytics' was released by MC Press in October 2011 and the second book 'Big Data Analytics' was released in October 2012. He has also been a contributing author in a number of Data Governance books written by Sunil Soares.
Prior to joining IBM, Dr. Sathi was the pioneer in developing knowledge-based solutions for CRM at Carnegie Group. At BearingPoint, he led the development of Enterprise Integration, MDM, and Operations Support Systems/Business Support Systems (OSS/BSS) solutions for the communications market and also developed horizontal solutions for communications, financial services, and public services. At IBM, Dr. Sathi has led several Information Management programs in MDM, data security, business intelligence, advanced analytics, big data and related areas and has provided strategic architecture oversight to IBM's strategic accounts. He has also delivered a number of workshops and presentations at industry conferences on technical subjects including MDM and data architecture, and he holds two patents in data masking. His first book'Customer Experience Analytics' was released by MC Press in October 2011 and the second book 'Big Data Analytics' was released in October 2012. He has also been a contributing author in a number of Data Governance books written by Sunil Soares.
Foreword PART I: INTRODUCTION 1. Why this Book? 2. Data Sources 3. Audience 4. Book Overview PART II: DISRUPTIVE FORCES 5. Introduction 6. Social Media and the Empowered Customer 7. Emergence of Big Data 8. Advanced Analytics 9. Public and Private Clouds and the Data Bazaar 10. Summary PART III: PIONEERS 11. Introduction 12. Consumer Research 13. Advertising 14. Promotions 15. Shopper Tracking 16. Order Tracking 17. Summary PART IV: PROPOSITION 1 - BIG DATA MEANS A LOT MORE OBSERVATIONS 18. Introduction 19. Data 20. Analytics 21. Change with Big Data 22. Summary PART V: PROPOSITION 2 - AUTOMATION AND SOCIAL MEDIA 23. Listening 24. Conversations 25. Participation in Games 26. Endorsements 27. Ambassadors and Advisors 28. Summary PART VI: PROPOSITION 3 - PERSONALIZED MARKETING 29. Introduction 30. Micro Segmentation 31. Directed Communication 32. Privacy Management 33. Single Customer View 34. Cross Channel Management 35. Organizational Implications 36. Summary PART VII: TECHNOLOGICAL ENABLERS 37. Introduction 38. Unstructured Data Analysis 39. Pattern Discovery 40. Experiment Design 41. Customer Identity Resolution 42. Real-time Bidding 43. Summary PART VIII: SKILLS REQUIREMENTS - DATA SCIENTISTS AND DATA ENGINEERS 44. Introduction 45. Data Warehouse and Business Intelligence Skills 46. Data Scientist 47. Data Engineer 48. Analytics as a Service 49. Evolution vs. Revolution 50. Summary PART IX: WHERE ARE WE HEADED? 51. Introduction 52. What did we cover? 53. What is the impact? 54. How can we get ready for the changes? 55. Conclusions
Foreword PART I: INTRODUCTION1. Why this Book? 2. Data Sources 3. Audience 4. Book Overview PART II: DISRUPTIVE FORCES5. Introduction 6. Social Media and the Empowered Customer 7. Emergence of Big Data 8. Advanced Analytics 9. Public and Private Clouds and the Data Bazaar 10. Summary PART III: PIONEERS11. Introduction 12. Consumer Research 13. Advertising 14. Promotions 15. Shopper Tracking 16. Order Tracking 17. Summary PART IV: PROPOSITION 1 - BIG DATA MEANS A LOT MORE OBSERVATIONS18. Introduction 19. Data 20. Analytics 21. Change with Big Data 22. Summary PART V: PROPOSITION 2 - AUTOMATION AND SOCIAL MEDIA23. Listening 24. Conversations 25. Participation in Games 26. Endorsements 27. Ambassadors and Advisors 28. Summary PART VI: PROPOSITION 3 - PERSONALIZED MARKETING29. Introduction 30. Micro Segmentation 31. Directed Communication 32. Privacy Management 33. Single Customer View 34. Cross Channel Management 35. Organizational Implications 36. Summary PART VII: TECHNOLOGICAL ENABLERS37. Introduction 38. Unstructured Data Analysis 39. Pattern Discovery 40. Experiment Design 41. Customer Identity Resolution 42. Real-time Bidding 43. Summary PART VIII: SKILLS REQUIREMENTS - DATA SCIENTISTS AND DATA ENGINEERS44. Introduction 45. Data Warehouse and Business Intelligence Skills 46. Data Scientist 47. Data Engineer 48. Analytics as a Service 49. Evolution vs. Revolution 50. Summary PART IX: WHERE ARE WE HEADED? 51. Introduction 52. What did we cover? 53. What is the impact? 54. How can we get ready for the changes? 55. Conclusions
Foreword PART I: INTRODUCTION 1. Why this Book? 2. Data Sources 3. Audience 4. Book Overview PART II: DISRUPTIVE FORCES 5. Introduction 6. Social Media and the Empowered Customer 7. Emergence of Big Data 8. Advanced Analytics 9. Public and Private Clouds and the Data Bazaar 10. Summary PART III: PIONEERS 11. Introduction 12. Consumer Research 13. Advertising 14. Promotions 15. Shopper Tracking 16. Order Tracking 17. Summary PART IV: PROPOSITION 1 - BIG DATA MEANS A LOT MORE OBSERVATIONS 18. Introduction 19. Data 20. Analytics 21. Change with Big Data 22. Summary PART V: PROPOSITION 2 - AUTOMATION AND SOCIAL MEDIA 23. Listening 24. Conversations 25. Participation in Games 26. Endorsements 27. Ambassadors and Advisors 28. Summary PART VI: PROPOSITION 3 - PERSONALIZED MARKETING 29. Introduction 30. Micro Segmentation 31. Directed Communication 32. Privacy Management 33. Single Customer View 34. Cross Channel Management 35. Organizational Implications 36. Summary PART VII: TECHNOLOGICAL ENABLERS 37. Introduction 38. Unstructured Data Analysis 39. Pattern Discovery 40. Experiment Design 41. Customer Identity Resolution 42. Real-time Bidding 43. Summary PART VIII: SKILLS REQUIREMENTS - DATA SCIENTISTS AND DATA ENGINEERS 44. Introduction 45. Data Warehouse and Business Intelligence Skills 46. Data Scientist 47. Data Engineer 48. Analytics as a Service 49. Evolution vs. Revolution 50. Summary PART IX: WHERE ARE WE HEADED? 51. Introduction 52. What did we cover? 53. What is the impact? 54. How can we get ready for the changes? 55. Conclusions
Foreword PART I: INTRODUCTION1. Why this Book? 2. Data Sources 3. Audience 4. Book Overview PART II: DISRUPTIVE FORCES5. Introduction 6. Social Media and the Empowered Customer 7. Emergence of Big Data 8. Advanced Analytics 9. Public and Private Clouds and the Data Bazaar 10. Summary PART III: PIONEERS11. Introduction 12. Consumer Research 13. Advertising 14. Promotions 15. Shopper Tracking 16. Order Tracking 17. Summary PART IV: PROPOSITION 1 - BIG DATA MEANS A LOT MORE OBSERVATIONS18. Introduction 19. Data 20. Analytics 21. Change with Big Data 22. Summary PART V: PROPOSITION 2 - AUTOMATION AND SOCIAL MEDIA23. Listening 24. Conversations 25. Participation in Games 26. Endorsements 27. Ambassadors and Advisors 28. Summary PART VI: PROPOSITION 3 - PERSONALIZED MARKETING29. Introduction 30. Micro Segmentation 31. Directed Communication 32. Privacy Management 33. Single Customer View 34. Cross Channel Management 35. Organizational Implications 36. Summary PART VII: TECHNOLOGICAL ENABLERS37. Introduction 38. Unstructured Data Analysis 39. Pattern Discovery 40. Experiment Design 41. Customer Identity Resolution 42. Real-time Bidding 43. Summary PART VIII: SKILLS REQUIREMENTS - DATA SCIENTISTS AND DATA ENGINEERS44. Introduction 45. Data Warehouse and Business Intelligence Skills 46. Data Scientist 47. Data Engineer 48. Analytics as a Service 49. Evolution vs. Revolution 50. Summary PART IX: WHERE ARE WE HEADED? 51. Introduction 52. What did we cover? 53. What is the impact? 54. How can we get ready for the changes? 55. Conclusions