E-commerce is booming. Currently, there are over a 2.14 billion people worldwide that shop online and there are approximately between 12 to 14 million online shops in 2021 [1]. This raises the question how to attract customers to your online company by differentiating yourself amongst all those other choices that customers have nowadays.
Take the case of Netflix. It is clear Netflix has come up with an innovative business model by selling unlimited subscription fees and by doing so providing customers all over the world direct access to a wide variety of films and series. However, one of the key success factors and trivial for the dominance of Netflix in the entertainment industry is the personalized experience by using recommendations algorithms [2]. It allows Netflix to offer multiple products, namely one product for each customer [3].
Personalization cannot only be applied in the online entertainment industry, but in many other online industries and thus in the fashion E-commerce. For this particular industry it’s not a mere possibility, it is an important key success factor. Personalization is the way to attract customers to your online shopping platform and even more important lock them in. In the world of E-commerce there are many choices for customers. Furthermore, customers are able to search very easily across different platforms and switching costs are low [4].
In fashion e-commerce personalization by using algorithms is not yet exploited fully, despite the fact that it provides big opportunities for companies such as Amazon and Zalando. Recommendations can be used in many forms. One of the most basic forms is to simply show recommendations based on the browsing history of the customer. Research has shown that when 24 million of these recommendations were implemented on a platform, another 1.6 million clicks were made. Another form might be that the homepage of each individual could be altered based on previous searches [5].
In conclusion, personalization enhances the customer shopping experience. Therefore, it should be implanted in the long-term strategy of fashion E-commerce companies.
References:
[1] https://digitalintheround.com/how-many-online-stores-are-there
[2] Amatriain, X. & Basilico, J. (2015). Recommender Systems in Industry: A Netflix Case Study. Recommender Systems handbook. P.385-419.
Retrieved from: https://link.springer.com/chapter/10.1007/978-1-4899-7637-6_11
[3] https://research.netflix.com/business-area/personalization-and-search
[4] Hwangbo, H., Sok Kim, Y. & Jin Cha, K. (2018). Recommendation system development for fashion retail e-commerce. Electronic Commerce Research and Applications. P. 94-101, 28.
Retrieved from https://www.sciencedirect.com/science/article/pii/S1567422318300152
[5] https://www.shopify.com/enterprise/ecommerce-fashion-industry
