Predicting future brand value: The role of machine learning monitoring
Data-driven strategies have become essential for brand valuation optimization in today’s rapidly evolving virtual economy, where organizations face increasing pressure to gain real-time, accurate insights to maintain a competitive edge. The purpose of the study examine the impact of machine learning...
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| Format: | Article |
| Language: | English |
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LLC "CPC "Business Perspectives"
2025-06-01
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| Series: | Innovative Marketing |
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| Online Access: | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22274/IM_2025_02_Adwan.pdf |
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| _version_ | 1849715398698598400 |
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| author | Ahmad Al Adwan Ghaiath Altrjman Lu’ay Al-Mu’ani |
| author_facet | Ahmad Al Adwan Ghaiath Altrjman Lu’ay Al-Mu’ani |
| author_sort | Ahmad Al Adwan |
| collection | DOAJ |
| description | Data-driven strategies have become essential for brand valuation optimization in today’s rapidly evolving virtual economy, where organizations face increasing pressure to gain real-time, accurate insights to maintain a competitive edge. The purpose of the study examine the impact of machine learning in monitoring key market factors to predict future brand value, addressing the growing need among industry professionals for tools that enhance strategic decision-making. From April to September 2024, a purposive sample of 350 upper-level brand managers and sales marketing directors from various Jordanian companies targeted due to their direct involvement in brand evaluation and marketing strategy. 229 completed and valid responses were collected through a self-administered questionnaire. The data analyzed using AMOS software and Structural Equation Modeling (SEM) to test the research hypotheses. Results indicated that all proposed factors significantly influenced the prediction of future brand value, with purchase frequency (β = 2.681), industry trend monitoring (β = 2.228), consumer behavior (β = 0.353), and social media metrics (β = 0.345) showing statistically significant effects (p < 0.05). These findings demonstrate the effectiveness of machine learning in identifying predictive patterns relevant to brand performance and provide a practical framework for leveraging digital tools to enhance brand valuation strategies. The study concludes that integrating machine learning with key performance monitoring enables organizations to make more informed, timely, and impactful branding decisions in a dynamic digital landscape.
AcknowledgmentWe would like to thank the Business School at Al Ahliyya Amman University, Jordan. Specifically, many thanks go to the Department of E-marketing and Digital Communications. |
| format | Article |
| id | doaj-art-8e01e107d01f480ba013ad8a8021e35d |
| institution | DOAJ |
| issn | 1814-2427 1816-6326 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | LLC "CPC "Business Perspectives" |
| record_format | Article |
| series | Innovative Marketing |
| spelling | doaj-art-8e01e107d01f480ba013ad8a8021e35d2025-08-20T03:13:25ZengLLC "CPC "Business Perspectives"Innovative Marketing1814-24271816-63262025-06-0121218319610.21511/im.21(2).2025.1522274Predicting future brand value: The role of machine learning monitoringAhmad Al Adwan0https://orcid.org/0000-0003-0451-0182Ghaiath Altrjman1https://orcid.org/0009-0004-7947-5988Lu’ay Al-Mu’ani2https://orcid.org/0000-0002-3916-8033Associate Professor, Head of Marketing Department, Al-Ahliyya Amman UniversityPh.D., Associate Professor, Business School, Department of Marketing, Al-Ahliyya Amman University, JordanAssociate Professor, Business School, Department of E-marketing and Digital Communications, Al-Ahliyya Amman University, JordanData-driven strategies have become essential for brand valuation optimization in today’s rapidly evolving virtual economy, where organizations face increasing pressure to gain real-time, accurate insights to maintain a competitive edge. The purpose of the study examine the impact of machine learning in monitoring key market factors to predict future brand value, addressing the growing need among industry professionals for tools that enhance strategic decision-making. From April to September 2024, a purposive sample of 350 upper-level brand managers and sales marketing directors from various Jordanian companies targeted due to their direct involvement in brand evaluation and marketing strategy. 229 completed and valid responses were collected through a self-administered questionnaire. The data analyzed using AMOS software and Structural Equation Modeling (SEM) to test the research hypotheses. Results indicated that all proposed factors significantly influenced the prediction of future brand value, with purchase frequency (β = 2.681), industry trend monitoring (β = 2.228), consumer behavior (β = 0.353), and social media metrics (β = 0.345) showing statistically significant effects (p < 0.05). These findings demonstrate the effectiveness of machine learning in identifying predictive patterns relevant to brand performance and provide a practical framework for leveraging digital tools to enhance brand valuation strategies. The study concludes that integrating machine learning with key performance monitoring enables organizations to make more informed, timely, and impactful branding decisions in a dynamic digital landscape. AcknowledgmentWe would like to thank the Business School at Al Ahliyya Amman University, Jordan. Specifically, many thanks go to the Department of E-marketing and Digital Communications.https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22274/IM_2025_02_Adwan.pdfbrand sustainabilityconsumer behaviordigital toolsJordanmarket trendsmonitoring |
| spellingShingle | Ahmad Al Adwan Ghaiath Altrjman Lu’ay Al-Mu’ani Predicting future brand value: The role of machine learning monitoring Innovative Marketing brand sustainability consumer behavior digital tools Jordan market trends monitoring |
| title | Predicting future brand value: The role of machine learning monitoring |
| title_full | Predicting future brand value: The role of machine learning monitoring |
| title_fullStr | Predicting future brand value: The role of machine learning monitoring |
| title_full_unstemmed | Predicting future brand value: The role of machine learning monitoring |
| title_short | Predicting future brand value: The role of machine learning monitoring |
| title_sort | predicting future brand value the role of machine learning monitoring |
| topic | brand sustainability consumer behavior digital tools Jordan market trends monitoring |
| url | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22274/IM_2025_02_Adwan.pdf |
| work_keys_str_mv | AT ahmadaladwan predictingfuturebrandvaluetheroleofmachinelearningmonitoring AT ghaiathaltrjman predictingfuturebrandvaluetheroleofmachinelearningmonitoring AT luayalmuani predictingfuturebrandvaluetheroleofmachinelearningmonitoring |