How to Recommend by Online Lifestyle Tagging (OLT)

Abstract

With the rapid development of the Internet, the online shopping market expands constantly. Inspired by fierce competition and complex and diverse consumer demand, personalized recommendation has become an effective marketing tool for e-commerce enterprises. However, the existing recommendation methods based on online consumer behavior or preferences are characterized by poor accuracy and low efficiency. The paper mainly conducts three studies, the study1 proves that seven online lifestyles, which are "Comfortable, Entertainment, Luxury, Tradition & Conservation, Rational, Fashion Sense, and Social Activities", affect Chinese consumers' purchase. However, the different online lifestyles have different effects on purchase, thus the response rates of recommending. The study2 proposes a new personalized recommendation method "online lifestyle tagging (OLT)" based on online lifestyle and user behavior tags to identify online lifestyles. In the study3, the efficiency of OLT is tested and verified using data collected from enterprises, it suggests that OLT has a significantly higher response rate than traditional behavior-based methods. This study demonstrates that OLT improves the accuracy and efficiency of personalized recommendation, and thus contributes to the theory of personalized recommendation and marketing methods based on lifestyle.