Decision Intelligence in Business: A Tool for Quick and Accurate Marketing Analysis

Authors

  • Upendar Rao Thaduri ACE Developer, iMINDS Technology Systems, Inc., Pittsburgh, PA 15243, USA

DOI:

https://doi.org/10.18034/abr.v10i3.670

Keywords:

Artificial Intelligence, Decision Making, Efficiency, Accuracy, Innovation, Business Intelligence, Big Data

Abstract

The term "artificial intelligence" (AI) refers to a technology recently becoming a disruptive innovation with far-reaching ramifications for many industries, including business. AI has revolutionized decision-making processes in recent years by providing organizations with enhanced analytical capabilities. These capabilities allow organizations to extract essential insights from large volumes of data, enabling AI to modernize decision-making processes. The implementation of AI in business could result in the industry being forced to rely on marketing strategies that are more efficient, less expensive, and more accurate. An increase in audience reaction and constructing a powerful online brand capable of competing with others are possibilities for an entrepreneur who implements AI-based marketing methods in their company. In addition to marketing, it can completely revamp an existing firm by introducing novel ideas. In addition, it offers answers to complex challenges, which contributes to the significant expansion of the firm. The study's primary objective is to evaluate how artificial intelligence (AI) and decision-making are utilized in business. Additionally, the researchers attempted to investigate how AI is being used to improve decision-making processes and how it is transforming business models. According to the study, applying artificial intelligence in business decisions can have a big transformative effect, providing significant efficiency, accuracy, and innovation benefits. Systems that AI powers allow businesses to process and analyze vast amounts of data rapidly, making decisions more quickly and with greater insight.

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References

Ballamudi, V. K. R. (2016). Utilization of Machine Learning in a Responsible Manner in the Healthcare Sector. Malaysian Journal of Medical and Biological Research, 3(2), 117-122. https://mjmbr.my/index.php/mjmbr/article/view/677

Ballamudi, V. K. R. (2019a). Artificial Intelligence: Implication on Management. Global Disclosure of Economics and Business, 8(2), 105-118. https://doi.org/10.18034/gdeb.v8i2.540 DOI: https://doi.org/10.18034/gdeb.v8i2.540

Ballamudi, V. K. R. (2019b). Road Accident Analysis and Prediction using Machine Learning Algorithmic Approaches. Asian Journal of Humanity, Art and Literature, 6(2), 185-192. https://doi.org/10.18034/ajhal.v6i2.529 DOI: https://doi.org/10.18034/ajhal.v6i2.529

Ballamudi, V. K. R. (2019c). Hybrid Automata: An Algorithmic Approach Behavioral Hybrid Systems. Asia Pacific Journal of Energy and Environment, 6(2), 83-90. https://doi.org/10.18034/apjee.v6i2.541 DOI: https://doi.org/10.18034/apjee.v6i2.541

Ballamudi, V. K. R., & Desamsetti, H. (2017). Security and Privacy in Cloud Computing: Challenges and Opportunities. American Journal of Trade and Policy, 4(3), 129–136. https://doi.org/10.18034/ajtp.v4i3.667 DOI: https://doi.org/10.18034/ajtp.v4i3.667

Bodepudi, A., Reddy, M., Gutlapalli, S. S., & Mandapuram, M. (2019). Voice Recognition Systems in the Cloud Networks: Has It Reached Its Full Potential?. Asian Journal of Applied Science and Engineering, 8(1), 51–60. https://doi.org/10.18034/ajase.v8i1.12 DOI: https://doi.org/10.18034/ajase.v8i1.12

Buttigieg, S. C., Pace, A., Rathert, C. (2017). Hospital Performance Dashboards: A Literature Review, Journal of Health Organization and Management, 31(3), 385-406. https://doi.org/10.1108/JHOM-04-2017-0088 DOI: https://doi.org/10.1108/JHOM-04-2017-0088

Cavalcante, R., Brasileiro, R. C., Souza, V. L. F., Nobrega, J. P., Oliveira, A. L. I. (2016). Computational Intelligence and Financial Markets: A Survey and Future Directions. Expert Systems with Applications, 55, 194–211. https://doi.org/10.1016/j.eswa.2016.02.006 DOI: https://doi.org/10.1016/j.eswa.2016.02.006

Chen, H., Chiang, R. H. L., Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503 DOI: https://doi.org/10.2307/41703503

Chen, S., Thaduri, U. R., & Ballamudi, V. K. R. (2019). Front-End Development in React: An Overview. Engineering International, 7(2), 117–126. https://doi.org/10.18034/ei.v7i2.662 DOI: https://doi.org/10.18034/ei.v7i2.662

Dekkati, S., & Thaduri, U. R. (2017). Innovative Method for the Prediction of Software Defects Based on Class Imbalance Datasets. Technology & Management Review, 2, 1–5. Retrieved from https://upright.pub/index.php/tmr/article/view/78

Dekkati, S., Lal, K., & Desamsetti, H. (2019). React Native for Android: Cross-Platform Mobile Application Development. Global Disclosure of Economics and Business, 8(2), 153-164. https://doi.org/10.18034/gdeb.v8i2.696 DOI: https://doi.org/10.18034/gdeb.v8i2.696

Dekkati, S., Thaduri, U. R., & Lal, K. (2016). Business Value of Digitization: Curse or Blessing?. Global Disclosure of Economics and Business, 5(2), 133-138. https://doi.org/10.18034/gdeb.v5i2.702 DOI: https://doi.org/10.18034/gdeb.v5i2.702

Deming, C., Dekkati, S., & Desamsetti, H. (2018). Exploratory Data Analysis and Visualization for Business Analytics. Asian Journal of Applied Science and Engineering, 7(1), 93–100. https://doi.org/10.18034/ajase.v7i1.53 DOI: https://doi.org/10.18034/ajase.v7i1.53

Desamsetti, H. (2016a). A Fused Homomorphic Encryption Technique to Increase Secure Data Storage in Cloud Based Systems. The International Journal of Science & Technoledge, 4(10), 151-155.

Desamsetti, H. (2016b). Issues with the Cloud Computing Technology. International Research Journal of Engineering and Technology (IRJET), 3(5), 321-323.

Desamsetti, H. (2018). Internet of Things (IoT) Technology for Use as Part of the Development of Smart Home Systems. International Journal of Reciprocal Symmetry and Theoretical Physics, 5, 14–21. https://upright.pub/index.php/ijrstp/article/view/89

Desamsetti, H., & Lal, K. (2019). Being a Realistic Master: Creating Props and Environments Design for AAA Games. Asian Journal of Humanity, Art and Literature, 6(2), 193-202. https://doi.org/10.18034/ajhal.v6i2.701 DOI: https://doi.org/10.18034/ajhal.v6i2.701

Desamsetti, H., & Mandapuram, M. (2017). A Review of Meta-Model Designed for the Model-Based Testing Technique. Engineering International, 5(2), 107–110. https://doi.org/10.18034/ei.v5i2.661 DOI: https://doi.org/10.18034/ei.v5i2.661

Gutlapalli, S. S. (2016a). An Examination of Nanotechnology’s Role as an Integral Part of Electronics. ABC Research Alert, 4(3), 21–27. https://doi.org/10.18034/ra.v4i3.651 DOI: https://doi.org/10.18034/ra.v4i3.651

Gutlapalli, S. S. (2016b). Commercial Applications of Blockchain and Distributed Ledger Technology. Engineering International, 4(2), 89–94. https://doi.org/10.18034/ei.v4i2.653 DOI: https://doi.org/10.18034/ei.v4i2.653

Gutlapalli, S. S. (2017a). Analysis of Multimodal Data Using Deep Learning and Machine Learning. Asian Journal of Humanity, Art and Literature, 4(2), 171–176. https://doi.org/10.18034/ajhal.v4i2.658 DOI: https://doi.org/10.18034/ajhal.v4i2.658

Gutlapalli, S. S. (2017b). The Role of Deep Learning in the Fourth Industrial Revolution: A Digital Transformation Approach. Asian Accounting and Auditing Advancement, 8(1), 52–56. Retrieved from https://4ajournal.com/article/view/77

Gutlapalli, S. S. (2017c). An Early Cautionary Scan of the Security Risks of the Internet of Things. Asian Journal of Applied Science and Engineering, 6, 163–168. Retrieved from https://ajase.net/article/view/14

Gutlapalli, S. S., Mandapuram, M., Reddy, M., & Bodepudi, A. (2019). Evaluation of Hospital Information Systems (HIS) in terms of their Suitability for Tasks. Malaysian Journal of Medical and Biological Research, 6(2), 143–150. https://mjmbr.my/index.php/mjmbr/article/view/661 DOI: https://doi.org/10.18034/mjmbr.v6i2.661

Karimova, F. (2016). A survey of e-commerce recommender systems. European Scientific Journal, 12(34), 75–89. https://doi.org/10.19044/esj.2016.v12n34p75 DOI: https://doi.org/10.19044/esj.2016.v12n34p75

Kumar, S. B., Ravi, V. (2016). A Survey of the Applications of Text Mining in Financial Domain. Knowledge-Based Systems, 114, 128– 147. https://doi.org/10.1016/j.knosys.2016.10.003 DOI: https://doi.org/10.1016/j.knosys.2016.10.003

Lal, K. (2015). How Does Cloud Infrastructure Work?. Asia Pacific Journal of Energy and Environment, 2(2), 61-64. https://doi.org/10.18034/apjee.v2i2.697 DOI: https://doi.org/10.18034/apjee.v2i2.697

Lal, K. (2016). Impact of Multi-Cloud Infrastructure on Business Organizations to Use Cloud Platforms to Fulfill Their Cloud Needs. American Journal of Trade and Policy, 3(3), 121–126. https://doi.org/10.18034/ajtp.v3i3.663 DOI: https://doi.org/10.18034/ajtp.v3i3.663

Lal, K., & Ballamudi, V. K. R. (2017). Unlock Data’s Full Potential with Segment: A Cloud Data Integration Approach. Technology & Management Review, 2(1), 6–12. https://upright.pub/index.php/tmr/article/view/80

Lal, K., Ballamudi, V. K. R., & Thaduri, U. R. (2018). Exploiting the Potential of Artificial Intelligence in Decision Support Systems. ABC Journal of Advanced Research, 7(2), 131-138. https://doi.org/10.18034/abcjar.v7i2.695 DOI: https://doi.org/10.18034/abcjar.v7i2.695

Maknickiene, N., Maknickas, A. (2013). Financial Market Prediction System with Evolino Neural Network and Delphi Method. Journal of Business Economics and Management, 14(2), 403–413. https://doi.org/10.3846/16111699.2012.729532 DOI: https://doi.org/10.3846/16111699.2012.729532

Mandapuram, M. (2016). Applications of Blockchain and Distributed Ledger Technology (DLT) in Commercial Settings. Asian Accounting and Auditing Advancement, 7(1), 50–57. https://4ajournal.com/article/view/76

Mandapuram, M. (2017a). Application of Artificial Intelligence in Contemporary Business: An Analysis for Content Management System Optimization. Asian Business Review, 7(3), 117–122. https://doi.org/10.18034/abr.v7i3.650 DOI: https://doi.org/10.18034/abr.v7i3.650

Mandapuram, M. (2017b). Security Risk Analysis of the Internet of Things: An Early Cautionary Scan. ABC Research Alert, 5(3), 49–55. https://doi.org/10.18034/ra.v5i3.650 DOI: https://doi.org/10.18034/ra.v5i3.650

Mandapuram, M., & Hosen, M. F. (2018). The Object-Oriented Database Management System versus the Relational Database Management System: A Comparison. Global Disclosure of Economics and Business, 7(2), 89–96. https://doi.org/10.18034/gdeb.v7i2.657 DOI: https://doi.org/10.18034/gdeb.v7i2.657

Mandapuram, M., Gutlapalli, S. S., Bodepudi, A., & Reddy, M. (2018). Investigating the Prospects of Generative Artificial Intelligence. Asian Journal of Humanity, Art and Literature, 5(2), 167–174. https://doi.org/10.18034/ajhal.v5i2.659 DOI: https://doi.org/10.18034/ajhal.v5i2.659

Sheta, F. A., Ahmed, S. E. M., Faris, H. (2015). A Comparison Between Regression, Artificial Neural Networks and Support Vector Machines for Predicting Stock Market Index. International Journal of Advanced Research in Artificial Intelligence, 4(7). https://doi.org/10.14569/IJARAI.2015.040710 DOI: https://doi.org/10.14569/IJARAI.2015.040710

Stalidis, G., Karapistolis, D., Vafeiadis, A. (2015). Marketing Decision Support Using Artificial Intelligence and Knowledge Modeling: Application to Tourist Destination Management. Procedia – Social and Behavioral Sciences, 175, 106–113. https://doi.org/10.1016/j.sbspro.2015.01.1180 DOI: https://doi.org/10.1016/j.sbspro.2015.01.1180

Thaduri, U. R. (2017). Business Security Threat Overview Using IT and Business Intelligence. Global Disclosure of Economics and Business, 6(2), 123-132. https://doi.org/10.18034/gdeb.v6i2.703 DOI: https://doi.org/10.18034/gdeb.v6i2.703

Thaduri, U. R. (2018). Business Insights of Artificial Intelligence and the Future of Humans. American Journal of Trade and Policy, 5(3), 143–150. https://doi.org/10.18034/ajtp.v5i3.669 DOI: https://doi.org/10.18034/ajtp.v5i3.669

Thaduri, U. R. (2019). Android & iOS Health Apps for Track Physical Activity and Healthcare. Malaysian Journal of Medical and Biological Research, 6(2), 151-156. https://mjmbr.my/index.php/mjmbr/article/view/678

Thaduri, U. R., Ballamudi, V. K. R., Dekkati, S., & Mandapuram, M. (2016). Making the Cloud Adoption Decisions: Gaining Advantages from Taking an Integrated Approach. International Journal of Reciprocal Symmetry and Theoretical Physics, 3, 11–16. https://upright.pub/index.php/ijrstp/article/view/77

Thodupunori, S. R., & Gutlapalli, S. S. (2018). Overview of LeOra Software: A Statistical Tool for Decision Makers. Technology & Management Review, 3(1), 7–11.

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Published

2020-12-31

How to Cite

Thaduri, U. R. (2020). Decision Intelligence in Business: A Tool for Quick and Accurate Marketing Analysis. Asian Business Review, 10(3), 193–200. https://doi.org/10.18034/abr.v10i3.670