Though the implementation of artificial intelligence within e-commerce continues to develop rapidly, there are four primary areas in which it deeply affects the experiences of customers. These areas include personalized recommendations, the search for potential customers, sales processes with the use of a virtual assistant, and improved search results. The introduction of vast customization in relation to recommendations is not new to firms that operate e-retail (Sharma, 2021). Prior methods have utilized viewing history, bestseller data, and additional general aggregation parameters in order to provide customers with viable suggestions. However, a truly successful recommendation model focuses on the preference and interests of the customer. AI is able to understand the preferences of clients through other data available which is usually large and cannot be manually assessed (Vanneschi et al., 2018). The browsing behavior of clients is observed and analyzed by AI more rapidly and efficiently, allowing recommendations to be more accurate and accessible.
Client behavior can even be analyzed using more novel and developing technologies such as facial and voice recognition. AI may recognize the behaviors of customers in stores and which products they do not purchase but spend time observing or considering (Policarpo et al., 2021). Such data, as well as much of the unused client data that firms accumulate, can then be utilized to provide customers with products that they are more likely to purchase (Khrais, 2020). Virtual assistants are elevated by AI as they introduce diverse problem-solving solutions and adaptability to the needs of the client that are not available through traditional approaches. A similar effect can be observed in relation to search results. Consumers are often unable to utilize search engines to facilitate a particular request without the introduction of numerous keywords (Soni, 2020). However, AI provides a human-like understanding of the client’s search requests through prior data and customer behavior.
References
Khrais, L. T. (2020). Role of artificial intelligence in shaping consumer demand in e-commerce. Future Internet, 12(12), 226.
Policarpo, L. M., Silveira, E. D., Righi, R. R., Stoffel, R. A., Costo, C. A., Barbosa, J. L. V., Scorsatto, R., & Arcot, T. (2021). Machine learning through the lens of e-commerce initiatives: An up-to-date systematic literature review. Computer Science Review, 41(1), 100414.
Sharma, D. (2021). Artificial intelligence in finance: Trends and applications. Apple Academic Press.
Soni, V. D. (2020). Emerging roles of artificial intelligence in ecommerce. International Journal of Trend in Scientific Research and Development, 4(5), 223-225.
Vanneschi, L., Horn, D. M., Castelli, M., & Popovic, A. (2018). An artificial intelligence system for predicting customer default in e-commerce. Expert Systems with Applications, 104(1), 1-21.