Date of Award
Thesis - SCU Access Only
Santa Clara : Santa Clara University
As more businesses have started embracing e-commerce, the personal relationships that existed between client and company have grown more distant and less informative. The feedback that is inherent in direct customer interaction was an integral part of shaping business trajectory. This information stream was lost with the decline of the brick-and-mortar business. To compensate, modern day businesses have seen the need to collect data about how customers use their product. The development of websites has improved over the last couple of years, and with a higher demand for usability data, various companies have come up with solutions that are able to help web developers improve their websites. One of the current solutions include Mixpanel, which does a great job gathering big data from event tracking, but it doesnt include an A/B testing feature. This feature is key for a company to compare the difference of their original website or application, to another that has been modified for improvement. There are many other solutions such as Google Analytics, Optimizely etc. that only offer one type of testing-either A/B testing or event tracking, and without having a combined source of tests we are unable to improve and modify a website or application to its fullest potential. Our idea is to combine both event driven analytics, similar to those employed by MixPanel, with A/B testing in order to get a provide our clients with a better insight into their customers usage patterns. Clients will be able to integrate our solution directly into their product, allowing them to leverage their existing framework. The data gathered from events will be entirely customized by the client, so that they can learn exactly what they want about their users. Analyzed data will be presented to the clients as clean, informative graphs via our website, which will allow for data specificity using the clients event information. Upon this functionality, we will build A/B comparison testing with a central randomized interface to divide users between the clients test UIs. In this way, our project will combine the best parts of A/B testing and event driven analytics to provide the best usability data possible to clients in their testing phase.
Evans, Matthew; Howles-Banerji, Michael; Narra, Aaraadhya; and Silva, Bryan, "NESH.co: A Web Analytics and Usability System" (2014). Computer Science and Engineering Senior Theses. 17.