Dish TV to Introduce Return Path Data Technology to Gather User Viewing Patterns in Real Time

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Dish TV, one of the largest DTH service operator in India today announced that it's in the final stages of deploying return path data technology in its Hybrid Set Top Boxes. Till date, Dish TV has deployed around 3 Million Hybrid Set Top Boxes in the market. Upon implementation of the return path data technology, Dish TV would be able to gather real-time and accurate data on viewing patterns of the customer, across all the regions of the country.

dishtv-path-data-technology




Data collected through this technology will essentially be used by Dish TV for its own usage, to understand TV consumption patterns on its platform. Currently, BARC data is the measurement matrix for acquiring channels for the DTH platform. The data which Dish TV will learn through the return path technology will bring the clear picture about the real choice of the customers in various regions of the country.

Furthermore, Dish TV will also make this data available to Marketing Agencies and also to large corporate houses which will enable them to judge the customer viewership choice accurately and decide on the Advertisement spend on the channels.

Dish TV has been known for such innovative technologies in the broadcasting and distribution landscape, and the implementation of path data technology will be yet another endeavour to help the industry make better business decisions in this increasingly competitive landscape.

However, Dish TV did not reveal when it's going to deploy the new technology though but expect it to arrive in the next couple of weeks or less than a month from now.

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Chakri is a go-to guy for your next smartphone recommendation. Back in his engineering days, he used to play with smartphones by installing custom ROMs and that passion got him into the tech industry. He still goes nuts about a smartphone knocking his door for review. Currently managing everything at Telecom Talk, Chakri is trying to master PUBG Mobile in his free time.

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