Website Visitor Analysis & Branding Quality Measurement Using Artificial Intelligence
DOI:
https://doi.org/10.54536/ajet.v3i3.3212Keywords:
Artificial Intelligence, Website Visitor Analysis & Branding Quality Measurement, Automated ToolsAbstract
This article discusses the use of classification of web visitors and determination of branding quality using AI to redesign digital marketing. AI in its various forms, such as machine learning, natural language processing, and computer vision, helps businesses to better understand their users’ behavior, better understand the context of supplied content, and improve user experience. The application of AI in the management of websites offers features such as Real-time monitoring, automated content tuning, and Analytics for predictions. Automated tools can analyze who is visiting the site, what kind of work they are doing in terms of SEO, and how to assist with creating high-quality content. Also, AI helps with mass and targeted promotions like recommended products and services, variable rates of prices, etc. AI can help unlock significant benefits for businesses, across the board and lead to enhanced engagement in the digital space and thus gives a competitive advantage in the market. The article also discusses investment in training and education for consumers to ensure them remain relevant with emerging technologies in AI and the market. By way of illustration and analysis, the article clearly outlines how the incorporation of AI in organizational functions can bring about operational efficiencies and cost savings, as well as result in remarkable improvements in branding and marketing strategies. The article was first completed in 2021 and later I have modified the article with latest updates till date 2024.
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Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in human behavior, 114, 106548. https://doi.org/10.1016/j.chb.2020.106548
Chaitanya, K., Saha, G. C., Saha, H., Acharya, S., & Singla, M. (2023). The impact of artificial intelligence and machine learning in digital marketing strategies. European Economic Letters (EEL), 13(3), 982-992.https://doi.org/10.52783/eel.v13i3.393
Chen, J. S., Le, T. T. Y., & Florence, D. (2021). Usability and responsiveness of artificial intelligence chatbot on online customer experience in e-retailing. International Journal of Retail & Distribution Management, 49(11), 1512-1531. https://doi.org/10.1108/IJRDM-08-2020-0312
Chintalapati, S., & Pandey, S. K. (2022). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38-68.
Chui, M., Issler, M., Roberts, R., & Yee, L. (2023). Technology trends outlook 2023.
Cui, Y. G., van Esch, P., & Phelan, S. (2024). How to build a competitive advantage for your brand using generative AI. Business Horizons. https://doi.org/10.1016/j.bushor.2024.04.011
Dadas, A. B. (2024). Potential of Digitalization for the Utilization of Artificial Intelligence Models for Uplifting Traditional Marketing Methods: A New Sustainable Growth. In Driving Decentralization and Disruption With Digital Technologies (pp. 267-277). IGI Global.https://doi.org/10.1051/e3sconf/202448303014
De Bruyn, A., Viswanathan, V., Beh, Y. S., Brock, J. K. U., & Von Wangenheim, F. (2020). Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing, 51(1), 91-105.https://doi.org/10.1016/j.intmar.2020.04.007
Elsayed F. A. Artificial Intelligence for marketing plan: the case for e-marketing companies. https://doi.org/10.21272/mmi.2021.1-07
Giglio, S., Pantano, E., Bilotta, E., & Melewar, T. C. (2020). Branding luxury hotels: Evidence from the analysis of consumers’“big” visual data on TripAdvisor. Journal of business research, 119, 495-501. https://doi.org/10.1016/j.jbusres.2019.10.053
Gołąb-Andrzejak, E. (2023). AI-powered digital transformation: Tools, benefits and challenges for marketers–case study of LPP. Procedia computer science, 219, 397-404. https://doi.org/10.1016/j.procs.2023.01.305
Gupta, R., Nair, K., Mishra, M., Ibrahim, B., & Bhardwaj, S. (2024). Adoption and impacts of generative artificial intelligence: Theoretical underpinnings and research agenda. International Journal of Information Management Data Insights, 4(1), 100232. https://doi.org/10.1016/j.jjimei.2024.100232
Hicham, N., Nassera, H., & Karim, S. (2023). Strategic framework for leveraging artificial intelligence in future marketing decision-making. Journal of Intelligent Management Decision, 2(3), 139-150.https://doi.org/10.56578/jimd020304
Hollebeek, L. D., Menidjel, C., Sarstedt, M., Jansson, J., & Urbonavicius, S. (2024). Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further research. Psychology & Marketing, 41(4), 880-898. https://doi.org/10.1002/mar.21957
Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50. https://doi.org/10.1007/s11747-020-00749-9
Jain, V., Wadhwani, K., & Eastman, J. K. (2024). Artificial intelligence consumer behavior: A hybrid review and research agenda. Journal of Consumer Behaviour, 23(2), 676-697.https://doi.org/10.1002/cb.2233
Kanimozhi, V., & Jacob, T. P. (2019, April). Artificial intelligence based network intrusion detection with hyper-parameter optimization tuning on the realistic cyber dataset CSE-CIC-IDS2018 using cloud computing. In 2019 international conference on communication and signal processing (ICCSP) (pp. 0033-0036). IEEE.
Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263-267. https://doi.org/10.2501/JAR-2018-035
Kirkby, A., Baumgarth, C., & Henseler, J. (2023). To disclose or not disclose, is no longer the question–effect of AI-disclosed brand voice on brand authenticity and attitude. Journal of Product & Brand Management, 32(7), 1108-1122.
Klumpp, M. (2018). Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements. International Journal of Logistics Research and Applications, 21(3), 224-242. https://doi.org/10.1080/13675567.2017.1384451
Kopalle, P. K., Gangwar, M., Kaplan, A., Ramachandran, D., Reinartz, W., & Rindfleisch, A. (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities. International Journal of Research in Marketing, 39(2), 522-540. https://doi.org/10.1016/j.ijresmar.2021.11.002
Kumar, I., Rawat, J., Mohd, N., & Husain, S. (2021). Opportunities of artificial intelligence and machine learning in the food industry. Journal of Food Quality, 2021(1), 4535567. https://doi.org/10.1155/2021/4535567
Kunduru, A. R. (2023). Artificial intelligence usage in cloud application performance improvement. Central Asian Journal of Mathematical Theory and Computer Sciences, 4(8), 42-47. https://doi.org/10.34010/injiiscom.v5i1
Lies, J. (2019). Marketing intelligence and big data: Digital marketing techniques on their way to becoming social engineering techniques in marketing. https://doi.org/10.9781/ijimai.2019.05.002
Mer, A. (2023). Artificial intelligence in human resource management: Recent trends and research agenda. Digital Transformation, Strategic Resilience, Cyber Security and Risk Management, 111, 31-56. https://doi.org/10.1108/S1569-37592023000111B003
Mustak, M., Salminen, J., Plé, L., & Wirtz, J. (2021). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research, 124, 389-404. https://doi.org/10.1016/j.jbusres.2020.10.044
Nalbant, K. G., & Aydın, S. (2023). Development and transformation in digital marketing and branding with artificial intelligence and digital technologies dynamics in the Metaverse universe. Journal of Metaverse, 3(1), 9-18. https://doi.org/10.57019/jmv.1148015
Pandey, N. (2023). Future of employer branding in the era of bard, ChatGPT, metaverse and artificial intelligence. NHRD Network Journal, 16(3), 258-268.https://doi.org/10.1177/26314541231170434
Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of business & industrial marketing, 34(7), 1410-1419.https://doi.org/10.1108/JBIM-10-2018-0295
Prentice, C., Dominique Lopes, S., & Wang, X. (2020). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing & Management, 29(7), 739-756. https://doi.org/10.1080/19368623.2020.1722304
Rana, J., Gaur, L., Singh, G., Awan, U., & Rasheed, M. I. (2022). Reinforcing customer journey through artificial intelligence: a review and research agenda. International Journal of Emerging Markets, 17(7), 1738-1758. https://doi.org/10.1108/IJOEM-08-2021-1214
Shpak, N., Rebilas, R., Kulyniak, I., Shulyar, R., & Horbal, N. (2023). Trends in Digital Marketing Research: Bibliometric Analysis. In COLINS (3) (pp. 449-465). https://doi.org/10.1057/s41270-021-00116-9
Suraña‐Sánchez, C., & Aramendia‐Muneta, M. E. (2024). Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda. International Journal of Consumer Studies, 48(2), e13027. https://doi.org/10.1111/ijcs.13027
Swain, S., Jebarajakirthy, C., Sharma, B. K., Maseeh, H. I., Agrawal, A., Shah, J., & Saha, R. (2024). Place branding: A systematic literature review and future research agenda. Journal of Travel Research, 63(3), 535-564. https://doi.org/ 10.1177/00472875231168620
Tekic, Z., & Füller, J. (2023). Managing innovation in the era of AI. Technology in Society, 73, 102254. https://doi.org/ 10.1016/j.techsoc.2023.102254
Ullah, Z., Al-Turjman, F., Mostarda, L., & Gagliardi, R. (2020). Applications of artificial intelligence and machine learning in smart cities. Computer Communications, 154, 313-323. https://doi.org/10.1016/j.comcom.2020.02.069
Varsha, P. S., Akter, S., Kumar, A., Gochhait, S., & Patagundi, B. (2021). The impact of artificial intelligence on branding: a bibliometric analysis (1982-2019). Journal of Global Information Management (JGIM), 29(4), 221-246. https://doi.org/10.4018/JGIM.20210701.oa10
Wang, D., Guerra, A., Wittke, F., Lang, J. C., Bakker, K., Lee, A. W., ... & Chen, Y. H. (2023). Real-time monitoring of infectious disease outbreaks with a combination of Google Trends search results and the moving epidemic method: A respiratory syncytial virus case study. Tropical Medicine and Infectious Disease, 8(2), 75.
Yu, L., Härdle, W. K., Borke, L., & Benschop, T. (2023). An AI approach to measuring financial risk. The Singapore Economic Review, 68(05), 1529-1549.
Yüksel, N., Börklü, H. R., Sezer, H. K., & Canyurt, O. E. (2023). Review of artificial intelligence applications in engineering design perspective. Engineering Applications of Artificial Intelligence, 118, 105697.https://doi.org/10.1016/j.engappai.2022.105697
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Copyright (c) 2024 Sasibhushan-Rao Chanthati
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