Last week TV news channels decided to opt for “Monthly TV ratings” instead of current format of weekly rating citing the reason that news reporting can’t be linked to popularity. Although the reason given is very apt and I agree to it, but the solution is completely
useless illogical. How in the world Advertisers are suppose to advertise on N.E.W.S channels based on monthly viewership data, when the viewership is so highly dependent upon important events (most dynamic)?
Also, there is this other type of issue with News channels- When there is a breaking event (and viewership goes high), they can’t ethically show more ads! Hence the problem is very complex.
Problem 1: Advertisers need a comprehensive rating system for News channels? But how?
First, my view on hundred of news channels sprouted off lately-
Ideally, news should never be heavily commoditized, and should remain in control of Govt. Even if it’s privatized there should be strong regulations which channels need to follow. If not, News channels would control both the content as well as advertisements (yes, a monopolistic situation)!
So what should advertisers do to tackle this problem. Is there any solution? Well, I can’t talk about a perfect solution but let’s discuss in details as to what advertisers need.
Talking about News channels, their content can be divided into following categories:
- General News broadcast (like 8PM prime, 7AM live, sports etc)
- Prime time debates.
- Talk shows.
- Special shows (Citizen Journalist, Tech Toyz, aapke taare)
- Entertainment shows (Total Recall, Rajeev Masand ki Pasand)
- Last but not the least- “Breaking News”.
In case there is no genuine breaking news, 70-80% slots are taken by points 1,2 and 3. Since there is so much competition for point 1 type category, the viewership for “general news broadcast” shows can’t be easily defined.
For point 2 and 3, the viewership totally depends upon the topic of debate or the people involved in the discussions/talk shows (which is so dynamic). Hence, for such shows there should be a daily inventory to buy ads and advertisers should also be given details about the schedule of programs with topics and personality names.
This will give advertisers an opportunity to advertise based on their knowledge of present data and not based on assumptions of historic data.
Buying ad slots for News channels should be based on some knowledge combined with past viewership data. Historical data alone, makes no sense for categories defined under points 1,2 and 3.
For points 4 and 5 traditional system of one week viewership is fine. Ads for such shows can be bought based on historical data set. But for News channels such shows only cover 20-25% of total shows.
During any major event/breaking news type of situation advertisers should get options of “short ad breaks” (very similar to live events like cricket/tennis matches). This again can never depend upon historical data. For e.g. during “Anna movement”, TRPs of almost ALL News channels jumped to at least 2 times.
So what’s the point of TRP during such events as every advertiser knows that they can’t buy ad slots based on those TRPs after the event is over.
Problem 2: Viewers demographics should be defined based on programs, not channels.
Here is a sample of TRP ratings for past week for 3 Channel genres viz. Business, Infotainment and Lifestlye. [source- exchange4media.com]:
1. Business (TG: CS 25+): (top 5 unique shows)
2. Lifestyle (TG: CS 4+): (top 5 unique shows)
3. Infotainment (TG: CS 15+): (top 5 unique shows)
I analyzed one particular show “Tech Toyz”, it being very popular among youth and also being number 2 show on Business Genre as given by TAM ratings (above).
As per TAM ratings TG (Target Group) of Business Channels is age 25+, for Lifestyle channels TG is (almost everyone) 4+ and for Infotainment it’s 15+.
Based on above 3 tables any advertiser whose TG is- male, 15-25, students will only look for Discovery channel, ignoring Business genre completely as the data doesn’t even tracks students <25 years of age and also ignoring lifestyle genre thinking it majorly targets female/women.
On iDubba, we have been tracking user response for various programs for past 6 months (or more) now. We multi-tag all the shows and “Tech Toyz” comes under- Business, Infotainment and lifestyle (all 3) genres. I thought it would be interesting to compare iDubba’s data with the above mentioned data.
1. Let’s see past 6 months activity data on iDubba and take out TOP 5 shows from these 3 genres i.e. business, lifestyle and infotainment. (You might argue about the time frame but here I’m not trying to justify iDubba’s ratings but the demographics of users)
Here are TOP 5 shows on iDubba based on past 6 months records and 3 genres described above-
||CNBC TV 18
|Worst Case scenario
|How Stuff Works
Now let’s check user demographics of users who watch/like/comment on Top 2 shows i.e. Gadget Guru and Tech Toyz–
Our data clearly suggests that students in 19-25 range mostly watch both of these shows, irrespective of them being shown on Business and Lifestyle channels.
It’s also a fact that most of the users on iDubba (around 50%) are from age group 19-25 but the important point here is that those users like more of Tech Toyz and Gadget gurus than Man Vs Wilds. Which is an important aspect of all the above analysis.
Based on above details an advertiser should clearly target Gadget Guru and Tech Toyz along with other Discovery shows to target its TG (19-25, male, student).
Advertisers in today’s dynamic world should also have tools to quickly find out similar shows based on target audience. For e.g. an Amazon type collaborative filtering algorithm should easily guide an advertiser about other similar programs liked by same target audience. This definitely can’t be done using traditional meter concept. We need something revolutionary.
In future, I see this whole industry getting more mature and technologically advanced! Technology (specially internet, mobile and social) will enable broadcasters gather user reactions about programs almost real-time and will help advertisers make quick and more accurate marketing decisions.
Any advertisers out there? What do you think?