Business and Technology Insights

Navigation Analytics using Clickstream Data

 
April 13, 2020

Nowadays, navigational analytics (NVGA) in real-time is used extensively across e-commerce, social media and content-based marketing and video streaming applications, providing curated options to improve the user experience across platforms. As a result of this improved analytics at user-level, these applications are able to increase market reach and revenue manifold. NVGA also helps to improve application performance, the most important factor for retaining users from switching to a different application. A recent Adobe Consumer content survey shows that likelihood of user switching to another website or mobile application is 33% for young users & 48% for above 50 yrs., if access time is long.

Similarly, enterprises applications generally use conventional navigation methods which provide less navigational maneuverability that results in performance issues. The solution to provide users with superior experience would be to leverage NVGA, which would collect, measure and analyze application usage in real-time and optimize the user navigation, thereby improving application performance and assisting in providing user-specific innovative solutions.

Challenges

Users and Applications, both follow legacy navigational paradigms such as HR Managers who frequently review leave request, would need to browse specific module, and traverse several menus to access the functionality; or buyers who would need to review current and previous orders before placing fresh order with supplier, resulting in increased clicks and resource usage.

Also, application performance degrades over time due to use of traditional technology, increase in user traffic and compliances, and less than optimal application page design and content, which affects the user experience. Such legacy application can be optimized using NVGA.

Clickstream Data Analysis

NVGA aims to optimize low-level applications operations by analyzing clickstream data using Big Data and Machine Learning technologies. Automatic real-time personalization designed in enterprise applications, increases quality of user interaction, by focusing on user-specific preferences and customization, which improves the user experience and efficiency, and reduces the time taken to complete an activity. Significant improvements can be achieved by an in-depth clickstream data analysis at server and website level to enhance user experience.

Smart Personalized Shortcuts enabled and implemented, at user level based on user’s usage trend and application clicks. For example, word cloud based on frequently or recently accessed or important sections to highlight the most appropriate ones customized for the user or user groups. Applications can enable widgets with direct workflow approval based on usage frequency of various functionalities.

Forecast of Clicks to predict and suggest the next click in real-time to assist a user, using recommendation engines. Such recommendations will not only improve user experience but also  help new users to get acquainted to the applications. Using series of clicks made by user, probable destination functionalities could be suggested and highlighted to fasten navigation. If a new finance user logs in the application, the user can be guided to the claims approval screen with most optimized navigational route using fewer clicks.

Application Enhancement through analysis based on user search and clicks to provide missing or required features would increase the application usability. Mobile application should include essential functions, without making it heavy which would be beneficial to more users. Similarly, new modules can be added in the application, if a significant user base switches to a different application to use related information. For example - courier tracking information can be made available within the application, HRMS system can add new modules for timesheet if multiple separate applications are used.

Dynamic Content can be presented to the user instead of static content, based on preferences and usage trend, using navigation history of user and user groups. In addition to the smart shortcuts, page content could be reorganized for quick and easy access. For example – certain sections can be placed at page top depending on user usage, ordering of menu items could be made user specific. Unsupervised machine learning techniques such as Clustering could be used to identify content to be reorganized on user basis using clickstream data.

Incomplete Activities can be analyzed based on the top pages where users abandon the application. This could be used for improvement in the specific page, where incomplete activity details such as draft or incomplete requests are stored and pre-fetched on subsequent login for activity completion.

Benefits

Navigation Analytics improves the user experience and application knowledge resulting in better understanding of the application and improved performance in usability that leads to user satisfaction. There has been an increased adoption rate for clickstream navigational analytics globally, which has led to increased revenue across business and geographies. Regionally, North America is leading due to presence of major service providers such as IBM, Microsoft, Oracle followed by Europe with innovations & patents, and Asia-Pacific due to increased e-businesses.

Early adoption of the navigational analytics in enterprise applications would provide a big push to the application performance by reducing the application clicks and assist in providing innovative solutions.

Anoop Kumar is a Senior Developer with nine years of experience in the Innovation and Product Engineering (IPE) - Analytics group with the Platform Solutions unit at TCS. His area of expertise includes solution design, development and implementation of various Embedded and Predictive Analytics use cases for home grown products CHROMATM and TAPTM. He has delivered several complex business solutions and demonstrated deep technical and domain expertise in multiple areas. He holds a bachelor’s degree in Information Technology from Shanmugha Arts, Science, Technology & Research Academy (SASTRA) Thanjavur, Tamil Nadu, India.