This study integrates theories of task complexity and cognitive stopping rule to understand how complexity of information environment impacts uncertainty, effectiveness and efficiency of consumers’ decision process. Using the reviews provided by an online retailer, we develop an e-commerce environment with three levels of complexity: high with raw textual reviews, medium with attribute-level review summaries and low with web personalization strategy based on attribute preferences extracted from online reviews. In a controlled lab experiment, users took buying decisions under different levels of complexity. Our analyses of clickstream data showed that users’ effectiveness and efficiency were the highest in review based personalized environment. However, between groups who received summarized and textual reviews, the latter demonstrated apparently higher effectiveness and efficiency in decision making, which went against our anticipation. Further investigation showed that users simplified decision process when exposed to raw reviews. These results further inform reviews-based personalization strategy in e-commerce.