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BARC India and DEN Networks join hands for RPD to boost TV viewership measurement

13-October-2017
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BARC India and DEN Networks join hands for RPD to boost TV viewership measurement

TV viewership measurement in India is set to get a boost. In a major development, BARC India has partnered with cable distribution giant DEN Networks for measuring TV viewership using Return Path Data (RPD) via its digital set top boxes (STBs).

As part of this partnership, BARC India will fetch data from STBs of DEN Networks. DEN networks will also use this data for subscriber management, packaging opportunities and to drive advertising revenue on their in-house channels.

BARC India will use a portion of DEN Networks subscriber base to augment its TV measurement service. The large pool of panel households will also help address the issue of panel home tampering.  

BARC India had recently upped its panel home size to 30,000. These RPD partnerships will enable BARC India to capture viewership from an exponentially larger panel. 

“Collecting viewership data using RPD is a global practice. However, for BARC India it will be another global-first as we integrate this as part of the currency. Our partnership with DEN is the first step towards using RPD for TV viewership measurement,” said Romil Ramgarhia, CBO, BARC India.

BARC India, which is looking at partnering with more Cable and DTH operators for RPD, believes that this approach will allow expansion of panel households to over 150,000 in the near future.

“Currently most Cable/DTH operators in India do not have information on how their subscribers consume content. With more interactive services being launched, this will be a very valuable information for the platform owners. This partnership is a win-win for both and will benefit the larger ecosystem,” added Ramgarhia. 

SN Sharma, CEO, DEN Networks said, “Data gathering and analytics is becoming increasingly relevant in a vast and heterogeneous society like India. With this partnership, we have taken the first steps towards world class data analytics of subscriber viewing patterns which will help us to serve our customers in a far more effective way and enabling us to offer personalized services.”

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