Sequential analysis and clustering to investigate users’ online shopping behaviors based on need-states

•A sequential search pattern analysis and clustering approach is proposed to analyze consumers’ search behavior throughout the entire shopping process from the perspective of need-states.•We adopt maximal repeat patterns and lag sequential analysis to analyze the sequence of search paths and significant search patterns.•We identify four groups of consumers who browse for information, adopt recommendations, consult reviews, and conduct searches with different levels of need-states.•Each group employs its own particular web features to facilitate the shopping process.