AI-driven marketing research and data analytics:
"The surge in technological advancements, coupled with the exponential growth of data, has left marketers grappling with the need for a paradigm shift. The once-established methods of consumer engagement are now overshadowed by the complexities of the digital age, demanding a profound understan...
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
c2024
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "The surge in technological advancements, coupled with the exponential growth of data, has left marketers grappling with the need for a paradigm shift. The once-established methods of consumer engagement are now overshadowed by the complexities of the digital age, demanding a profound understanding of artificial intelligence (AI) and data analytics. The gap between academic knowledge and practical applications in the field of marketing has widened, leaving industry professionals, educators, and students seeking a comprehensive resource to navigate the intricacies of this transformative era.AI-Driven Marketing Research and Data Analytics is a groundbreaking book that serves as a beacon for marketers, educators, and industry leaders alike. With a keen focus on the symbiotic relationship between AI, data analytics, and marketing research, this book bridges the gap between theory and practice. It not only explores the historical evolution of marketing but also provides an innovative examination of how AI and data analytics are reshaping the landscape. Through real-time case studies, ethical considerations, and in-depth insights, the book offers a holistic solution to the challenges faced by marketing professionals in the digital age."-- |
| Beschreibung: | 29 PDFs (xxv, 490 pages) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9798369321669 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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| 006 | m eo d | ||
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| 020 | |a 9798369321669 |q PDF | ||
| 020 | |z 9798369321652 |q print | ||
| 024 | 7 | |a 10.4018/979-8-3693-2165-2 |2 doi | |
| 035 | |a (CaBNVSL)slc00005844 | ||
| 035 | |a (OCoLC)1432337604 | ||
| 040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
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| 082 | 7 | |a 658.872 |2 23 | |
| 245 | 0 | 0 | |a AI-driven marketing research and data analytics |c Reason Masengu, Option Takunda Chiwaridzo, Mercy Dube, Benson Ruzive, editors. |
| 246 | 3 | 3 | |a Artificial intelligence-driven marketing research and data analytics |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c c2024 | |
| 300 | |a 29 PDFs (xxv, 490 pages) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface -- Chapter 1. A Comparative Methodology of Supervised Machine Learning Algorithms for Predicting Customer Churn Using Neuromarketing Techniques -- Chapter 2. AI Voice Assistant for Smartphones With NLP Techniques -- Chapter 3. AI-Driven Marketing Success Stories: A Case Note of Industry Pioneers -- Chapter 4. Artificial Intelligence (AI) Algorithms in Nigeria's Integrated Marketing Communications -- Chapter 5. Artificial Intelligence and Data Analytics: A Narrative Review of Zimbabwe's SME Market -- Chapter 6. Artificial Intelligence-Driven Advertising and Customer Targeting: Precision Marketing Strategies in Zimbabwe -- Chapter 7. Central Load Balancing Policy Over Virtual Machines on Cloud -- Chapter 8. Customer Lifetime Value Prediction Using Survival Analysis -- Chapter 9. Enhancing Engagement With Personalized Recommendations With AI-Powered Recommender Systems -- Chapter 10. Exploring the Relationship Between CRM Tools, AI, and Big Data: A Systematic Review -- Chapter 11. Forecasting Demand Using Recurrent Neural Networks (RNN) -- Chapter 12. Introduction to AI in Marketing Research: The Evolution of Marketing in the Digital Age -- Chapter 13. Item Selection Using K-Means and Cosine Similarity -- Chapter 14. Machine Learning and Sentiment Analysis: Analysing Customer Feedback -- Chapter 15. Privacy-Preserving Computing in the Healthcare Using Federated Learning -- Chapter 16. Quality of Online Customer Service at a Telecommunication Company in Zimbabwe During the COVID-19 Pandemic -- Chapter 17. Redesigning Consumer Engagement Through Metaverse Strategies: Blockchain and Web 3.0 Technologies -- Chapter 18. Security and Privacy Challenges in Digital Marketing -- Chapter 19. TABST: A Next-Gen AI Model Unveiling Personalized Recommendations and Targeted Marketing -- Chapter 20. The Metaverse Marketing Revolution: How Virtual Worlds Are Redefining Digital Advertising and Paving the Way for Corporate Success -- Chapter 21. Unleashing Entrepreneurial Potential: The Transformative Impact of Artificial Intelligence -- Chapter 22. Utilising Big Data Analytics for Enhancing Retail Sales Forecasting and Supply Chain Management -- Compilation of References -- About the Contributors -- Index. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "The surge in technological advancements, coupled with the exponential growth of data, has left marketers grappling with the need for a paradigm shift. The once-established methods of consumer engagement are now overshadowed by the complexities of the digital age, demanding a profound understanding of artificial intelligence (AI) and data analytics. The gap between academic knowledge and practical applications in the field of marketing has widened, leaving industry professionals, educators, and students seeking a comprehensive resource to navigate the intricacies of this transformative era.AI-Driven Marketing Research and Data Analytics is a groundbreaking book that serves as a beacon for marketers, educators, and industry leaders alike. With a keen focus on the symbiotic relationship between AI, data analytics, and marketing research, this book bridges the gap between theory and practice. It not only explores the historical evolution of marketing but also provides an innovative examination of how AI and data analytics are reshaping the landscape. Through real-time case studies, ethical considerations, and in-depth insights, the book offers a holistic solution to the challenges faced by marketing professionals in the digital age."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 04/30/2024). | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Marketing research |x Technological innovations. | |
| 653 | |a A/B Testing and Optimization. | ||
| 653 | |a AI and Augmented Reality (AR) in Marketing. | ||
| 653 | |a Artificial Intelligence Algorithms. | ||
| 653 | |a Artificial Intelligence Driven Marketing Campaigns. | ||
| 653 | |a Artificial Intelligence in Marketing Research. | ||
| 653 | |a Attribution Modeling for Fraud Detection. | ||
| 653 | |a Bias and Fairness in Marketing Data and Algorithms. | ||
| 653 | |a Big Data Marketing Implications. | ||
| 653 | |a Blockchain and Web 3.0 Marketing. | ||
| 653 | |a Chatbots and Artificial Intelligence Powered Customer Support. | ||
| 653 | |a Churn Prediction Modeling for Customer Retention. | ||
| 653 | |a Consumer Behavior Analysis Artificial Intelligence. | ||
| 653 | |a Convolutional and Recurrent Neural Networks. | ||
| 653 | |a Customer Lifetime Value Prediction with Survival Analysis. | ||
| 653 | |a Data Analytics in Marketing Research. | ||
| 653 | |a Data Anonymization Techniques. | ||
| 653 | |a Data Collection and Management. | ||
| 653 | |a Data Privacy and Ethical Considerations. | ||
| 653 | |a Deep Learning and ARIMA Models. | ||
| 653 | |a Ethical Considerations and Challenges. | ||
| 653 | |a Evolution of Digital Marketing. | ||
| 653 | |a Forecasting Demand Using Time Series Models. | ||
| 653 | |a Future of Marketing in the Metaverse and Web 3.0 Environments. | ||
| 653 | |a Handling Censorship and Dynamic Predictors. | ||
| 653 | |a Key Performance Indicators (KPIs) in AI Marketing. | ||
| 653 | |a Machine Learning for Predictive Analytics. | ||
| 653 | |a Machine-learning Algorithms for Bid Optimization. | ||
| 653 | |a Marketing Attribution Models. | ||
| 653 | |a Measuring Returns on Investments (ROI) and Performance. | ||
| 653 | |a Metaverse Brand Presence and Engagement. | ||
| 653 | |a Neural Networks and Deep-learning Models for Marketing Analytics. | ||
| 653 | |a Personalization and Customer Experience. | ||
| 653 | |a Predictive Analytics for Targeted Campaigns. | ||
| 653 | |a Real-time Bid Optimization for Programmatic Advertising. | ||
| 653 | |a Real-time Fraud Monitoring. | ||
| 653 | |a Regulatory Frameworks and Compliance. | ||
| 653 | |a Sentiment Analysis and Social Media Listening. | ||
| 653 | |a Voice Search and Visual Search. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Chiwaridzo, Option Takunda |d 1990- |e editor. | |
| 700 | 1 | |a Dube, Mercy, |e editor. | |
| 700 | 1 | |a Masengu, Reason |d 1982- |e editor. | |
| 700 | 1 | |a Ruzive, Benson, |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369321652 |
| 856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-2165-2 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00331797 |
|---|---|
| _version_ | 1816797088072073216 |
| adam_text | |
| any_adam_object | |
| author2 | Chiwaridzo, Option Takunda 1990- Dube, Mercy Masengu, Reason 1982- Ruzive, Benson |
| author2_role | edt edt edt edt |
| author2_variant | o t c ot otc m d md r m rm b r br |
| author_facet | Chiwaridzo, Option Takunda 1990- Dube, Mercy Masengu, Reason 1982- Ruzive, Benson |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | H - Social Science |
| callnumber-label | HF5814 |
| callnumber-raw | HF5814 .A536 2024e |
| callnumber-search | HF5814 .A536 2024e |
| callnumber-sort | HF 45814 A536 42024E |
| callnumber-subject | HF - Commerce |
| collection | ZDB-98-IGB |
| contents | Preface -- Chapter 1. A Comparative Methodology of Supervised Machine Learning Algorithms for Predicting Customer Churn Using Neuromarketing Techniques -- Chapter 2. AI Voice Assistant for Smartphones With NLP Techniques -- Chapter 3. AI-Driven Marketing Success Stories: A Case Note of Industry Pioneers -- Chapter 4. Artificial Intelligence (AI) Algorithms in Nigeria's Integrated Marketing Communications -- Chapter 5. Artificial Intelligence and Data Analytics: A Narrative Review of Zimbabwe's SME Market -- Chapter 6. Artificial Intelligence-Driven Advertising and Customer Targeting: Precision Marketing Strategies in Zimbabwe -- Chapter 7. Central Load Balancing Policy Over Virtual Machines on Cloud -- Chapter 8. Customer Lifetime Value Prediction Using Survival Analysis -- Chapter 9. Enhancing Engagement With Personalized Recommendations With AI-Powered Recommender Systems -- Chapter 10. Exploring the Relationship Between CRM Tools, AI, and Big Data: A Systematic Review -- Chapter 11. Forecasting Demand Using Recurrent Neural Networks (RNN) -- Chapter 12. Introduction to AI in Marketing Research: The Evolution of Marketing in the Digital Age -- Chapter 13. Item Selection Using K-Means and Cosine Similarity -- Chapter 14. Machine Learning and Sentiment Analysis: Analysing Customer Feedback -- Chapter 15. Privacy-Preserving Computing in the Healthcare Using Federated Learning -- Chapter 16. Quality of Online Customer Service at a Telecommunication Company in Zimbabwe During the COVID-19 Pandemic -- Chapter 17. Redesigning Consumer Engagement Through Metaverse Strategies: Blockchain and Web 3.0 Technologies -- Chapter 18. Security and Privacy Challenges in Digital Marketing -- Chapter 19. TABST: A Next-Gen AI Model Unveiling Personalized Recommendations and Targeted Marketing -- Chapter 20. The Metaverse Marketing Revolution: How Virtual Worlds Are Redefining Digital Advertising and Paving the Way for Corporate Success -- Chapter 21. Unleashing Entrepreneurial Potential: The Transformative Impact of Artificial Intelligence -- Chapter 22. Utilising Big Data Analytics for Enhancing Retail Sales Forecasting and Supply Chain Management -- Compilation of References -- About the Contributors -- Index. |
| ctrlnum | (CaBNVSL)slc00005844 (OCoLC)1432337604 |
| dewey-full | 658.872 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.872 |
| dewey-search | 658.872 |
| dewey-sort | 3658.872 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00331797 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:52:00Z |
| institution | BVB |
| isbn | 9798369321669 |
| language | English |
| oclc_num | 1432337604 |
| open_access_boolean | |
| owner | DE-863 DE-BY-FWS |
| owner_facet | DE-863 DE-BY-FWS |
| physical | 29 PDFs (xxv, 490 pages) Also available in print. |
| psigel | ZDB-98-IGB |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | IGI Global, |
| record_format | marc |
| spelling | AI-driven marketing research and data analytics Reason Masengu, Option Takunda Chiwaridzo, Mercy Dube, Benson Ruzive, editors. Artificial intelligence-driven marketing research and data analytics Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, c2024 29 PDFs (xxv, 490 pages) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Preface -- Chapter 1. A Comparative Methodology of Supervised Machine Learning Algorithms for Predicting Customer Churn Using Neuromarketing Techniques -- Chapter 2. AI Voice Assistant for Smartphones With NLP Techniques -- Chapter 3. AI-Driven Marketing Success Stories: A Case Note of Industry Pioneers -- Chapter 4. Artificial Intelligence (AI) Algorithms in Nigeria's Integrated Marketing Communications -- Chapter 5. Artificial Intelligence and Data Analytics: A Narrative Review of Zimbabwe's SME Market -- Chapter 6. Artificial Intelligence-Driven Advertising and Customer Targeting: Precision Marketing Strategies in Zimbabwe -- Chapter 7. Central Load Balancing Policy Over Virtual Machines on Cloud -- Chapter 8. Customer Lifetime Value Prediction Using Survival Analysis -- Chapter 9. Enhancing Engagement With Personalized Recommendations With AI-Powered Recommender Systems -- Chapter 10. Exploring the Relationship Between CRM Tools, AI, and Big Data: A Systematic Review -- Chapter 11. Forecasting Demand Using Recurrent Neural Networks (RNN) -- Chapter 12. Introduction to AI in Marketing Research: The Evolution of Marketing in the Digital Age -- Chapter 13. Item Selection Using K-Means and Cosine Similarity -- Chapter 14. Machine Learning and Sentiment Analysis: Analysing Customer Feedback -- Chapter 15. Privacy-Preserving Computing in the Healthcare Using Federated Learning -- Chapter 16. Quality of Online Customer Service at a Telecommunication Company in Zimbabwe During the COVID-19 Pandemic -- Chapter 17. Redesigning Consumer Engagement Through Metaverse Strategies: Blockchain and Web 3.0 Technologies -- Chapter 18. Security and Privacy Challenges in Digital Marketing -- Chapter 19. TABST: A Next-Gen AI Model Unveiling Personalized Recommendations and Targeted Marketing -- Chapter 20. The Metaverse Marketing Revolution: How Virtual Worlds Are Redefining Digital Advertising and Paving the Way for Corporate Success -- Chapter 21. Unleashing Entrepreneurial Potential: The Transformative Impact of Artificial Intelligence -- Chapter 22. Utilising Big Data Analytics for Enhancing Retail Sales Forecasting and Supply Chain Management -- Compilation of References -- About the Contributors -- Index. Restricted to subscribers or individual electronic text purchasers. "The surge in technological advancements, coupled with the exponential growth of data, has left marketers grappling with the need for a paradigm shift. The once-established methods of consumer engagement are now overshadowed by the complexities of the digital age, demanding a profound understanding of artificial intelligence (AI) and data analytics. The gap between academic knowledge and practical applications in the field of marketing has widened, leaving industry professionals, educators, and students seeking a comprehensive resource to navigate the intricacies of this transformative era.AI-Driven Marketing Research and Data Analytics is a groundbreaking book that serves as a beacon for marketers, educators, and industry leaders alike. With a keen focus on the symbiotic relationship between AI, data analytics, and marketing research, this book bridges the gap between theory and practice. It not only explores the historical evolution of marketing but also provides an innovative examination of how AI and data analytics are reshaping the landscape. Through real-time case studies, ethical considerations, and in-depth insights, the book offers a holistic solution to the challenges faced by marketing professionals in the digital age."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 04/30/2024). Artificial intelligence. Data mining. Marketing research Technological innovations. A/B Testing and Optimization. AI and Augmented Reality (AR) in Marketing. Artificial Intelligence Algorithms. Artificial Intelligence Driven Marketing Campaigns. Artificial Intelligence in Marketing Research. Attribution Modeling for Fraud Detection. Bias and Fairness in Marketing Data and Algorithms. Big Data Marketing Implications. Blockchain and Web 3.0 Marketing. Chatbots and Artificial Intelligence Powered Customer Support. Churn Prediction Modeling for Customer Retention. Consumer Behavior Analysis Artificial Intelligence. Convolutional and Recurrent Neural Networks. Customer Lifetime Value Prediction with Survival Analysis. Data Analytics in Marketing Research. Data Anonymization Techniques. Data Collection and Management. Data Privacy and Ethical Considerations. Deep Learning and ARIMA Models. Ethical Considerations and Challenges. Evolution of Digital Marketing. Forecasting Demand Using Time Series Models. Future of Marketing in the Metaverse and Web 3.0 Environments. Handling Censorship and Dynamic Predictors. Key Performance Indicators (KPIs) in AI Marketing. Machine Learning for Predictive Analytics. Machine-learning Algorithms for Bid Optimization. Marketing Attribution Models. Measuring Returns on Investments (ROI) and Performance. Metaverse Brand Presence and Engagement. Neural Networks and Deep-learning Models for Marketing Analytics. Personalization and Customer Experience. Predictive Analytics for Targeted Campaigns. Real-time Bid Optimization for Programmatic Advertising. Real-time Fraud Monitoring. Regulatory Frameworks and Compliance. Sentiment Analysis and Social Media Listening. Voice Search and Visual Search. Electronic books. Chiwaridzo, Option Takunda 1990- editor. Dube, Mercy, editor. Masengu, Reason 1982- editor. Ruzive, Benson, editor. IGI Global, publisher. Print version: 9798369321652 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-2165-2 Volltext |
| spellingShingle | AI-driven marketing research and data analytics Preface -- Chapter 1. A Comparative Methodology of Supervised Machine Learning Algorithms for Predicting Customer Churn Using Neuromarketing Techniques -- Chapter 2. AI Voice Assistant for Smartphones With NLP Techniques -- Chapter 3. AI-Driven Marketing Success Stories: A Case Note of Industry Pioneers -- Chapter 4. Artificial Intelligence (AI) Algorithms in Nigeria's Integrated Marketing Communications -- Chapter 5. Artificial Intelligence and Data Analytics: A Narrative Review of Zimbabwe's SME Market -- Chapter 6. Artificial Intelligence-Driven Advertising and Customer Targeting: Precision Marketing Strategies in Zimbabwe -- Chapter 7. Central Load Balancing Policy Over Virtual Machines on Cloud -- Chapter 8. Customer Lifetime Value Prediction Using Survival Analysis -- Chapter 9. Enhancing Engagement With Personalized Recommendations With AI-Powered Recommender Systems -- Chapter 10. Exploring the Relationship Between CRM Tools, AI, and Big Data: A Systematic Review -- Chapter 11. Forecasting Demand Using Recurrent Neural Networks (RNN) -- Chapter 12. Introduction to AI in Marketing Research: The Evolution of Marketing in the Digital Age -- Chapter 13. Item Selection Using K-Means and Cosine Similarity -- Chapter 14. Machine Learning and Sentiment Analysis: Analysing Customer Feedback -- Chapter 15. Privacy-Preserving Computing in the Healthcare Using Federated Learning -- Chapter 16. Quality of Online Customer Service at a Telecommunication Company in Zimbabwe During the COVID-19 Pandemic -- Chapter 17. Redesigning Consumer Engagement Through Metaverse Strategies: Blockchain and Web 3.0 Technologies -- Chapter 18. Security and Privacy Challenges in Digital Marketing -- Chapter 19. TABST: A Next-Gen AI Model Unveiling Personalized Recommendations and Targeted Marketing -- Chapter 20. The Metaverse Marketing Revolution: How Virtual Worlds Are Redefining Digital Advertising and Paving the Way for Corporate Success -- Chapter 21. Unleashing Entrepreneurial Potential: The Transformative Impact of Artificial Intelligence -- Chapter 22. Utilising Big Data Analytics for Enhancing Retail Sales Forecasting and Supply Chain Management -- Compilation of References -- About the Contributors -- Index. Artificial intelligence. Data mining. Marketing research Technological innovations. |
| title | AI-driven marketing research and data analytics |
| title_alt | Artificial intelligence-driven marketing research and data analytics |
| title_auth | AI-driven marketing research and data analytics |
| title_exact_search | AI-driven marketing research and data analytics |
| title_full | AI-driven marketing research and data analytics Reason Masengu, Option Takunda Chiwaridzo, Mercy Dube, Benson Ruzive, editors. |
| title_fullStr | AI-driven marketing research and data analytics Reason Masengu, Option Takunda Chiwaridzo, Mercy Dube, Benson Ruzive, editors. |
| title_full_unstemmed | AI-driven marketing research and data analytics Reason Masengu, Option Takunda Chiwaridzo, Mercy Dube, Benson Ruzive, editors. |
| title_short | AI-driven marketing research and data analytics |
| title_sort | ai driven marketing research and data analytics |
| topic | Artificial intelligence. Data mining. Marketing research Technological innovations. |
| topic_facet | Artificial intelligence. Data mining. Marketing research Technological innovations. Electronic books. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-2165-2 |
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