One commonly adopted practice in classifying retail and institutional orders is based on order size. Due to the increasing use of small orders by institutional investors, size-based classification can lead to an error rate over 20%. To improve the accuracy of the order size algorithm, we study the order patterns and uncover a higher tendency of retail investors trading in multiples of 500 shares. We modify the original order size algorithm by incorporating the feature of share roundedness. The modified algorithm substantially improves the accuracy of identifying retail and institutional investors in China. Order imbalances derived from the modified algorithm better predict future stock returns.