Fahad Nizam Siddiqui

Enhancing product and UX for user acceptance by automated feedback using UAM

In the modern business world everything is either a product or service. The need to improve the product has been the most important and challenging task. It has always been a target to make a product which is useful, easy, valuable and as pleasing as possible for the user. To reach this target, feedback from the user has been the most valuable asset.  Collecting this valuable feedback has been the most difficult part. This feedback collection process, either by structured or unstructured channels, makes the entire system quite costly as a lot of effort and time is spent for it. To streamline this collection overhead process, we need a way to automatically collect any form of feedback from the users. This feedback can be in the form of their actions and their behavior while using the product or service. Then by monitoring the users' actions, using web analytics tools, we can try to take a step in the direction of making this whole collection process a lot easier. 

This thesis tests this idea for product and UX enhancement using automated feedback based on user's actions and usage behavior. The users activity on a web portal has been stored using a web analytics tool. Then this data has been used to build features based on clickstream analysis and data aggregation. These two features, "Suggestions" and "User's Journey", were then put to test on the web portal to evaluate if the features built from this data have any impact on the product and the overall user experience. The feature based on aggregation (Suggestions on the Dashboard) showed not so positive results when First Click Testing was applied on it to measure time based metrics. On the other hand the feature based on clickstream analysis (User's Journey) showed very promising findings and led to enhancing the product in a positive way.