The purpose of this study is to get an idea of what impact different elements and information has on a product page in order for the user to be inclined to purchase the product. Furthermore this research will look into the possible differences and/or similarities between genders. The data that was used in this study was obtained through a descriptive research design, specifically a survey involving structured direct observations and semi-structured interviews. This research found that the elements that were deemed the most essential in order for participants to purchase a product were the different pictures of the product and different colour alternatives. Many behavioural similarities between genders were found along with some differences. Differences such as the time it takes to decide whether or not to make a purchase was discovered. This study offers valid insights in the interactions between users and product pages with the additional focus on the differences between genders. Some limitations for this study was the fact that the sample group was relatively small, the testing was only conducted on one website, and all of the participants identified as either men and women, hence not including binary, pangender, transgender etc.

This work outlines a possible technique for identifying webpages that contain product  specifications. Using support vector machines a product web page classifier was constructed and tested with various settings. The final result for this classifier ended up being 0.958 in precision and 0.796 in recall for product pages. The scores imply that the method could be considered a valid technique in real world web classification tasks if additional features and more data were made available.