A leading telecom operator in India wanted a robust personalization framework in Value Added Services (VAS) that could adapt to the changing tastes of its users, thereby improving the following:
Iken Personics brought in an intelligent middle-ware in the VAS ecosystem to provide personalized content on SIVR rather than same contents pitched to all. Since users find relevant content as per their taste, it provides faster content discovery and long tail monetization. Following trends of disruption through self serving mode, personalization was introduced on new interfaces such as WAP & USSD.
Rethinking Business Intelligence (Operational Analytics)
As against traditional analytics (which does mass segmentation), Mooga takes the concept of analytics beyond data and reporting. It works on an N=1 level. The Operational Analytics framework allows for actionable insights in Real-time and Automated fashion.
Advanced Adaptive Technology
It is a powerful state-of-the-art recommendation, matching, discovery and personalization framework which supports many kinds of products, structured contents and generic transactions seamlessly and uniformly. It is based on social (collaborative) filtering, item (content and contextual) filtering, intelligent matching and users' tastes. This framework works in real-time and is completely programmable, configurable and customizable based on products, contents and required functionality.
AI based Matching Solution
Mooga matching solution backed by AI techniques compares requirements (criteria) v/s products, services, or contents (like electronic gadgets, cars, resumes, customer profiles etc.) intelligently. It helps to find out cluster having homogeneous (logically similar) products/contents/profiles based on input specification (product / profile).
Approach to address BI
The traditional approaches are more reliant on data warehousing where as Mooga uses transactional databases.