Data gathering architecture for clickstream data mining on online shop

Online buying and selling activities in Indonesia continue to develop every year. In 2018 there were approximately 106.96 million users of online-based transactions and the number is predicted to continue to grow. This is caused by a shift from conventional shopping method to online shopping method, as online shopping method is more practical. At present, online shops are starting to analyze the data of online sales and purchases, generated from the websites, for the purpose of compiling a sales strategy. One type of data that can be analyzed is customer behavior data. This data can be recorded based on customer browsing activities when they are doing online shopping, resulting in clickstream data. In this study, a data collection architecture for online shops will be proposed, which will provide a module for recording clickstream data for online shops' users. This module will be designed on web and mobile applications, considering that currently customers can also access online shops through mobile commerce applications on smartphones that are used. The clickstream data that has been collected, will be processed further for the purpose of making decisions related to the sales strategy, such as to identify potential customers and determine recommendations for customers.