Optimizing Personalized Marketing Strategies with NLP and Machine Learning on Customer Review Data
DOI:
https://doi.org/10.48047/CU/54/01/151-159Keywords:
Personalized Marketing Strategies, , Natural Language Processing (NLP), Machine Learning Techniques, Customer Review Analysis, Data MiningAbstract
Due to the expansion of the online market, many startups and small businesses are venturing into this field; however, systematic entry strategies and effective marketing execution remain significant challenges. These businesses often face difficulties in formulating plans to effectively deliver and sell products to consumers due to limited resources and budgets. In this context, developing systematic and effective digital marketing strategies utilizing customer reviews can play a crucial role in their success. This study aims to approach this issue based on customer reviews, which serve as vital sources of firsthand satisfaction and product pros and cons. Through analysis of these reviews, the study identifies key insights affecting new product design development and digital marketing strategy formulation. Utilizing customer reviews of VR headsets sold on amazon.com, the study extracts and analyzes key keywords to understand their correlations and consumer insights, including purchasing behavior. The findings highlight the importance of factors such as relevance to spouses, happiness derived from the product, discomfort, and design in purchase decisions. Particularly, opportunities exist to develop marketing strategies tailored to specific times or situations, such as gifting to spouses. This research is expected to contribute to establishing practical digital marketing execution plans for expanding product sales, thereby enhancing competitiveness and fostering closer connections with consumers in the market.
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