Flytxt offers #mADmart, a one of its kind multi-operator anchored #advertising market place that connects brands and advertising agencies to mobile subscribers. The unique advertising market place follows a two-sides business model delivering new revenue stream for CSPs on one side and providing full suit of mobile media inventory and related services to brands and advertisers on the other side.
CSPs are operating in a competitive and dynamic environment. In order to sustain their growth and market share in a highly competitive world, they need to leverage the full potential of their assets of network and subscriber data. #BigData analytics will enable quick experimentation with large volume of variety data, replace human decisioning, create transparency across business operations, enable micro segmentation and bring in innovative business models, products and pricing.
A telecom operator is a ‘natural’ #BigData factory. Huge volume of data is generated each second as part of its business-as-usual processes and what is more – all this data is generated, captured and available in real-time and digital form by default.
Exit polls, or combinations of exit polls, have been traditionally used to predict the results of elections. In the absence of exit polls, an interesting question is whether the results of an election can be predicted through mathematical models using publicly available data, including social media sources such as Twitter.
QREDA is a comprehensive Insight Monetization platform designed to enable CSPs to create new revenue streams by leveraging subscriber insights. #QREDA converts Personally Identifiable Information (PII) to Non-PII, ensuring subscriber privacy and allowing CSPs to extend subscriber insights and touch points to third parties through a Preference, Permission and Privacy (PPP) model.
#BigData Analytics generates highly useful insights for Communication Service Providers. However, you need human intelligence and domain know-how to make sensible interpretation of machine generated insights and to take timely and most appropriate decisions for maximizing the value generated. Man-machine collaboration is an approach of leveraging CSP data combining sophisticated machine learning enabled Big Data Analytics and cognitive reasoning power of domain experts.