It’s been a little over a year that Broadcast Audience Research Council (BARC) has resumed ratings for news channels. The industry body has done everything in its capacity to make the ratings more transparent, accurate and fair, be it in terms of increasing the number of panel homes or implementing the reporting of audience estimates on a four week rolling average basis. In an exclusive chat with Storyboard18, Shashi Sinha, chairman of BARC India talks about the importance of measurement, BARC initiatives, the body’s future plans and more.
Excerpts.
BARC has recently added 25000 odd panel homes. How will the expansion of panel homes enhance the accuracy of audience measurement for television viewership?
The government has clear guidelines that say that panel size shall be increased by 10,000 every year until it reaches the figure of 50,000. We are in sync with that and now we have a 55000 homes panel. Increasing number of panel homes does a couple of things.
To start with BARC is a very robust currency but there are certain smaller segments like the news genre where the sample is very small so the chances of variations are very high and increasing the panel homes reduces that.
This kind of sample size reduces infiltrations of any sort.
A lot of people do not know about another rule that the guidelines from the ministry highlights. The rule says 25 percent of the panel homes shall be rotated every year. The rotation is to be done in such a manner that older panel homes are removed first while maintaining the representativeness of the panel. This rotation is expected to be achieved in a staggered manner by rotating panel homes every month.
All of this helps in better and fairer measurement of data.
BARC ratings for the news genre were temporarily absent in late 2020; however, they were reinstated with the implementation of a rolling average system. How did BARC contribute to reestablishing credibility in news ratings through this process?
The implementation of the rolling average effectively reduces uncertainty. Looking at this from a broader perspective, I’m not only speaking as the BARC chairman but also as a media buyer. Every system is bound to have some errors, but the overarching trends persist, making it a reliable tool. These insights serve as valuable aid for marketers when determining advertising spends and placements. Thus, I believe that in any field, and in life as a whole, having a standardized metric is crucial. It fosters transparency, instills a healthy sense of competition, and motivates continuous improvement for both your brand and the end-users.
Could you provide us with an update on the progress of the cross-media measurement system that ISA mentioned they were working on with BARC?
Many are unaware that BARC has maintained a digital plus television panel for the past six to seven years. However, digital platforms also demand extensive measurement. The BARC ecosystem possesses the necessary capabilities, yet it requires stakeholders to reach consensus on various parameters, such as timing and methodology for measurement. When one platform presents data in a specific manner, it’s crucial for others to align and adopt the same system or format. This standardization holds significance in the measurement of any data. I am optimistic that this harmonization will be achieved in the near future.
What’s next for BARC? How do you plan to make the system better for broadcasters and advertisers?
It is already a very robust system for broadcasters and advertisers. But we are also working on a host of other things. We’re currently engaged in developing a captivating new baseline that promises interesting insights for marketers. Not everyone seeks pan-India data. Our intention is to release data aligned with this new baseline in the latter part of the year, and subsequently integrate it as a regular feature. This dataset will encompass a broader range of segments, including analyses like the distinctions between free and paid users. Our ongoing efforts include many such enhancements that would ultimately enable marketers to discern patterns within more specific segments.