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A number of frameworks have been prescribed for online retailers, but still there exists little consensus regarding the amount of information and the level of customization needed to optimize customers' satisfaction and their purchase intention, and thereby increase sales performance. Against this backdrop, this study aims to contribute to the current practical and theoretical discussions regarding the most effective ways to design and implement online retailers' website features by empirically examining the interplay between information content and website personalization, and their individual and interactive impact on performance. By applying Structural Equation Modeling analysis to a sample of the top US retailers' websites, we find that simply providing a large number of information content features to online customers is not enough for companies looking to motivate customers to purchase. However, information that is targeted to an individual customer influences customer satisfaction and purchase intention; customer satisfaction, in turn, serves as a driver to the retailer's online sales performance.

Enhancing Online Performance through Website Content and Personalization.