Article in SiliconIndia Magazine
June 10, 2014
Flytxt makes into the Top 10 Mobile Media Marketing Companies list by SiliconIndia Magazine. Flytxt has been identified as a specialized vendor in Big Data Analytics enabled mobile marketing and advertising for Telecom industry , with its two products NEON and QREDA.
Article in TeleAnalysis by Naveen Chandra, Senior Product Manager, Flytxt
June 9, 2014
Customer journey has never been so dynamic in Telecom world. Communication Service Providers (CSP) have millions of subscribers, hundreds of products and billions of events and contexts to deal with every day. Now how can CSPs ensure superior customer experience to each of their millions of subscribers through their whole life cycle? How can CSPs consistently create moments of happiness for customers? CSPs have lot more data coming in and that too in real-time with the advancements in communication technologies and explosion of connected devices. Can they leverage this data to create that fulfilling customer experience?
Article in Telecom Ramblings by Pravin Vijay, Director-Marketing, Flytxt
May 26, 2014
The definition of data archaeology is now around retrieving data and information from data sources having unknown or alien formats. This definition is going to get extended in this era of ‘big data’. A new stream will emerge, where unearthing insights and realizing the value from ‘invisible’ and ‘unknown’ data could be the span of study and focus. We can probably call this stream- ‘insight archaeology’. The role of data insight archaeologists is going to be critical for Telcos, as they focus on ensuring sustained economic value generation from data, which is now mostly in unstructured and semi structured form.
Article in The Hindu BusinessLine
May 13, 2014
Flytxt predicts the results of general elections India 2014 for Kerala & Delhi, based on analysis of available public data using a mathematical model developed in-house. Since election outcome is an aggregated preference of voters, a possible method of predicting the result is to estimate voting preference through statistical models. “Here, our attempt is to make use of similar predictive models in the Indian context to predict election outcomes in advance by using our expertise in data sciences and mathematical modelling,” says Jobin Wilson, architect at research and development at Flytxt.