Hyper personalization in Apps with Dynamic Experience

Most of the current web and mobile apps, have analytics driven content update to bring personalization. Apps are designed to follow a specific screen flow to complete an activity. The screen design is done with a workflow in mind, that satisfies a business requirement. Hence personalization is limited to content personalization. Experience personalization even if present is limited to selective hide and show of UI elements based on rules and personas. So in essence planning of the UI and flow is static, without true dynamic adaptation based on unique behavioral patterns of user.


Dynamic adaptation of frontend experience is not being done to improve efficiency of end user to perform a routine operation. The current experience design is to have “One static application”, to cater to many customers who are unique in their pattern of using the application. This results in reduced efficiency and sub-optimal experience, when the app is unable to adapt to user. This problem can be addressed by creating an application that adapts itself to specific context and user needs offering hyper personalization.


Dynamic user experience for True Hyper Personalization, needs to focuses on a single app that adapts itself to specific user needs and changes based on user behavior by collating and processing the analytics data to perform a computational real time experience design. Experience change is based on Usage pattern (Rearrange dashboard and items in dashboard, and create shortcuts based on browse like frequent visit, order placed, price choice, etc.), Experience pattern (Continue from where user left with switch of device, load template for weekly shopping, user rearrange app look-n-feel etc.), Location pattern (Load capabilities, change look-n-feel, and load relevant content based on location), Context pattern (Proactive alerts like price drop, offers on items of interest, etc.), Domain pattern (like season/ daily weather conditions for products displayed, role based like prime vs regular customer on offers, etc. for retail app) and Learning (based on machine learning analysis of user activity over a period of time).


Dynamic Component loading is possible in most of the web, hybrid and native app frameworks. Hence more applications that provide unique experience to each customer is expected to be available as more focus is given on Hyper Personalized experience.

Author Details

Jithesh Sathyan

Jithesh Sathyan is a Principal Technology Architect at Infosys. He is the sole inventor of first granted US patent of Infosys. He is inventor of several granted and filed patents. He has more than thirty research publications in popular journals, standardizing and external forums. He has also authored several books. Jithesh has rich experience leading Digital technology track (from strategy to steady state), for several digital transformation initiatives in multiple domains, for clients across the globe. He leads Cloud and Emerging Technologies track in Digital Technology Council and is the Chairperson of TechCohere (Tech focus Group) in Infosys Thiruvananthapuram DC.

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