LMRPID-397439
Page 63
9th November 2022
Customer Behavior Analysis and Personalized Marketing Strategies for E-commerce Platforms in Bangladesh
Researcher- Umama Khanom Antara | LGMID-27199320190101722
Reviewed by:
1. Dr. Anthony
2. DH Sakib
3. Taskin Karim
Paper preview
1. Abstract
2. Introduction
3. Literature Review
4. Methodology
5. Findings
6. Conclusion
7. References
Abstract
E-commerce in Bangladesh has quickly expanded, presenting both new opportunities and difficulties for companies looking to prosper in this competitive sector. E-commerce platforms must be aware of and adapt to their customers’ changing preferences and behaviors to stay competitive. The purpose of this thesis, “Customer Behaviour Analysis and Personalised Marketing Strategies for E-commerce Platforms in Bangladesh,” is to respond to this need by analyzing customer behavior patterns and suggesting personalized marketing strategies specifically adapted to the context of the Bangladeshi e-commerce market. The first step in the research is to thoroughly evaluate the body of knowledge regarding e-commerce, customer behavior analysis, and personalized marketing. Understanding the theoretical framework and methodology employed in the ensuing empirical research is based on this literature review. The empirical portion of the study entails the gathering and analysis of data from several Bangladeshi e-commerce platforms. Transaction histories, website interactions, and consumer demographic data are all examples of data sources. To find significant patterns and trends in customer behaviour, advanced data analytics approaches like machine learning algorithms and data mining are used. These observations provide information on customer preferences, purchasing patterns, and the variables affecting those decisions. The examination of consumer behavior’s key findings shows that Bangladeshi e-commerce clients have a variety of shopping preferences. They are heavily influenced by elements like product category, cost, and promotional offers while making purchases. The report also reveals diverse client segments with various demands and interests, highlighting the significance of personalized marketing tactics. The thesis designs personalized marketing tactics suitable for the Bangladeshi e-commerce market using the knowledge gathered from customer behavior analysis. These methods cover various topics, such as email marketing campaigns, product recommendations, and user experience improvements. Machine learning models are used to generate personalized product recommendations based on unique consumer profiles and previous purchase information. Segmentation and customized messaging optimize email marketing efforts to increase client engagement and retention. The study also examines how user experience design might improve consumer satisfaction and loyalty. Developing an applicable framework for Bangladeshi e-commerce platforms to use in implementing personalized marketing tactics is one of the main accomplishments of this thesis. The framework provides detailed instructions for acquiring and examining client data, choosing the best data analytics tools, and successfully implementing personalized marketing campaigns. The study also discusses ethical issues related to data security and privacy. It highlights the significance of gaining consumers’ informed consent for data collecting and ensuring adherence to pertinent data protection laws.Overall, “Customer Behaviour Analysis and Personalised Marketing Strategies for E-commerce Platforms in Bangladesh” offers insightful information about the workings of the Bangladeshi e-commerce business. E-commerce platforms in Bangladesh may improve consumer satisfaction, generate sales, and maintain a competitive edge in this emerging industry by utilizing powerful data analytics and personalized marketing tactics. The research described in this thesis adds to the body of knowledge on e-commerce and provides useful advice for companies wishing to prosper in the changing environment of Bangladeshi e-commerce. The strategies and insights provided in this thesis establish a platform upon which businesses can build and adapt to suit the ever-changing demands and preferences of their customers in Bangladesh’s thriving e-commerce ecosystem as the e-commerce industry continues to expand.
References
Anderson, C. A., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
Chaffey, D., & Ellis-Chadwick, F. (2019). Digital marketing: Strategy, implementation, and practice. Pearson UK.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
Kotler, P., & Armstrong, G. (2018). Principles of marketing (17th ed.). Pearson.
Kumar, V. (2016). Customer relationship management: Concept, strategy, and tools. Springer.
Lee, D., & Park, J. (2018). Data mining in social media. Springer.
Li, X., Wang, D., Li, Y., & Zhang, J. (2015). Customer segmentation and strategy development based on customer lifetime value: A case study. Expert Systems with Applications, 42(4), 1668-1680.
Malhotra, N. K., & Birks, D. F. (2017). Marketing research: An applied approach. Pearson Education Limited.
Ramanathan, R. (2011). An empirical analysis of the impact of e-commerce on international trade. International Journal of Electronic Commerce, 16(4), 41-62.
Schmitt, B. (2018). Customer experience management: A revolutionary approach to connecting with your customers. John Wiley & Sons.
Sheth, J. N., & Parvatiyar, A. (2000). Handbook of relationship marketing. Sage.
Solomon, M. R., Dahl, D. W., White, K., Zaichkowsky, J. L., & Polegato, R. (2016). Consumer behavior: Buying, having, and being (12th ed.). Pearson.
Wang, Z., Hu, Y., Zheng, X., Zhao, X., & Li, S. (2019). Personalized product recommendation based on deep learning. Information Sciences, 493, 355-371.
Keywords
E-commerce, Customer Behavior, Personalized Marketing, Data Analytics, Bangladesh
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