Explained: How the raw-level data will benefit advertisers and broadcasters

The landmark decision by the Ministry of Information and Broadcasting ordering BARC India to share raw-level data with broadcasters is loaded with a host of benefits for both advertisers and broadcasters

Niraj Sharma
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Explained: How the raw-level data will benefit advertisers and broadcasters

As broadcasters await access to raw-level data from BARC India after the I&B Ministry’s order, explains how it will impact broadcasters and advertisers alike.

In an era when the whole world is moving towards first-party data, it is a landmark decision by the I&B Ministry if BARC India can clean up data and give it to their subscribers properly in the letter and spirit.

Globally, especially in developed markets across Europe, measurement companies like Kantar release only raw-level data. This is the global norm in developed economies.

It was only in India where BARC had so many problems behind releasing RLD for reasons known to everyone.

While the move has the potential to increase the queries from broadcasters complaining about the difference between raw data and final TRPs, it is set to redefine television media planning and buying for advertisers and FPC modelling for broadcasters among other benefits.

Benefits for advertisers:

1. Advertisers can look at the impact of advertising if they merge this raw-level data with their sales data.

2. For agencies, RLD opens up a big revenue source by offering good consulting for clients. It opens a stream for data analytics where they can buy RLD and package them for their clients.

Accenture and Deloitte are among the top advertising agencies largely riding on their data capabilities.

All agencies are looking at harnessing data and giving their clients insights basis that.

3. The behavioural pattern of the audience will be decided on a household level. Effectively, a day in the life of a household will become more clear instead of just a hypothesis. Currently, an advertiser is looking at the overall number.

4. In the future, there is a possibility that television could develop cohort-building capabilities.

If an advertiser wants to target a TG having affinity for certain programming or content, it can target that cohort. An advertiser can also target audiences who come to a certain channel in a breaking news scenario.

This way advertisers can buy a vastly defined audience.

Effectively, RLD will enable advertisers to target the audience at a completely different level. It has the potential to turn television into a medium with programmatic capabilities.

5. This will also enable the advertiser to know where the audience goes after watching certain content.

Suppose advertisers know that the audience is moving from Sports channels to news to watch the summary of a World Cup match, they can target that audience at much less cost.

The advertisers who were buying sports shows on news channels in anticipation of catching the sports audience will now have data points and proof of what they are buying.

6. Advertisers will have insights into the quality of the audience.

The RLD opens immense opportunities for advertisers who will be able to detect and discard any unwanted and rapid spike on certain programming of a certain channel.

In effect, an advertiser will be able to weed out whatever intervention or malpractices bring to the table.

7. RLD will enable advertisers to access and target core viewers across genres.

If a channel is trying to ride on external intervention, RLD will tell advertisers about the non-core audience.

The RLD will clearly tell the advertisers and broadcasters alike about the first tune-in on a household level, thus segregating core viewers from those coming through any external intervention.

8. RLD will save a lot of advertisers’ money spent on spillover audiences.

If an advertiser finds out that a news channel is sitting beside a movie channel on Freedish and gaining viewership because of that, why would it pay 5-10X amount to the news channel for targeting the same audience?

For example, an advertiser has Rs 100 to buy the free audience. Suppose it is spending Rs 20 on a movie channel and the remaining Rs 80 on a news channel sitting next to that movie channel delivering spillover audience.

If the advertiser has the data point defining the spillover audience, it will rather spend that remaining Rs 80 on another channel having a core audience.

Benefits for broadcasters:

1. Broadcasters can marry their digital data to the RLD to see the brand’s overall impact across platforms and screens.

2. Broadcasters will be able to analyse and point out the platform-specific viewership trends across pay and free platforms.

It will enable broadcasters to schedule the programming basis the specific behaviour of audiences on different platforms. They will be able to target pay and free households separately through programming.

3. RLD will also tell the common audience between the two genres. For example, a music or news broadcaster would know the common audience it shares with a GEC channel or the entire genre.

4. The RLD on a household level will prove to be a boon for sharp audience targeting for broadcasters as they will know where to deploy their promos.

5. Besides better scheduling, RLD will help a broadcaster understand its core audiences coming frequently on its platform, say 10 times in a week. This will enable a broadcaster to develop a cohort to measure the audience coming to the channel five or ten times a week.

6. A broadcaster can also look at audiences who spent a specific watch time on the channel and make a separate targeting group.

7. A broadcaster can ignore and isolate audiences who have come on a channel because of external interventions. It can remove such numbers and see the rest of the data. Even as this will not change anything in the final numbers, a broadcaster will know the reason behind its success or failure over its competition.

BARC advertisers viewers I&B ministry broadcasters RLD FPC modelling Behavioural pattern Household level External interventions cohort-building capabilities