Guest Column: Paradox in TV Media Planning (Personal Bias Vs Scientific Numbers)-- Debadutta Mishra

Is it right to supersede one’s personal experience over an established and a high sample based system? Are the existing systems and tools not capable of capturing the viewership trend for a secluded audience group, points out Debadutta Mishra, Media Director at Zenith.

On one fine Monday morning we (Media Planners) were betting on viewership ratings for some popular TV shows in English genre. ‘Game of Thrones’ was a safe choice though. We have seen youth following ‘Game of Thrones’ like bible for years. We could safely predict a rating of more than 0.5 TVR, similar to Roadies or Splitsvilla. However, when we saw the BARC ratings, the actual numbers were 100 times fraction of what we predicted. In fact, this is a long lasting trend for all English entertainment shows in India and raises apprehensions on existing media planning tools.

There are two opposite principles in media planning. One theory believes in numbers and takes the scientific way to optimize media campaigns. GRPs, SOVs, Reach & TVRs are the parameters to judge the effectiveness of the media campaign. TAM, BARC, RAM, IRS, TGI are the only weapons to decide whether the parameters are met or not. A major chunk of traditional advertising is dependent on Scientific Media Planning.

Now comes the second theory of media planning, which emerged with the evolution of English /Infotainment & Lifestyle genres. The followers of this new theory don’t believe in numbers to evaluate the so called niche genre. They rather use their personal experience or their peer’s assessment to judge these genres. They believe that their TG (Most of the times Audience from upper section of society) are under-represented through the scientific media tools such as IRS, TAM/ BARC and hence those can’t be used for judgements. Their theory is validated by the fact that all scientific tools, with few exceptions, throw poor viewership numbers for niche genre all the time.

So, now comes the real question. Is it right to supersede one’s personal experience over an established and a high sample based system? Are the existing systems and tools not capable of capturing the viewership trend for a secluded audience group? We will try to find out an answer to this question.

Indian Media Measurement system is considered to be one of the World’s most sophisticated & high sample statistical models. Indian Readership Survey is World’s largest continuous readership survey, with more than 2.5 lakh sample size. TAM used to deliver viewership number based on a panel with more than 10,000 households. Currently BARC is measuring TV Viewership based on 22,000 sample household for about 155 Mn household in India. In statistical language the sample is good enough to predict result for the population with 95% Confidence level and with a margin of error less than 1%. So the common perception that the sample size of TAM/BARC is low is wrong. In fact the sample size is more than descent to be used for extrapolation of viewership on Indian population.

In a sampling method, there is always a possibility of inaccuracy which we call “margin of error”. But the margin of error cannot be consistently skewed in favour or against a particular genre. If we analyse the relative viewership trend for all individual genres, they have been consistent during TAM for years. The same trend is continuing, with few exceptions in BARC. Yes there are few genres which have evolved over years in viewership numbers such as Infotainment & English Movies. But the trend is not sporadic, rather continuous. The genre share for all niche channels such as English Entertainment, Lifestyle channels have been consistently low for all these years. There are Sample panel changes that happened almost every year in TAM. And BARC is completely a new system with a new sample base. So such consistency in viewership during such a long period of time and through different system indicates the integrity & strength of the existing system.

Now comes the real question- If the current system is so robust and efficient, why is there mistrust for scientific media tools amongst Media Planners, Brand Managers particularly in niche genres? Why is there a big difference between our Notion & Viewership numbers? Why we can’t digest the fact that some of the top IMDB rated US shows deliver the lowest ratings such as 0.001 TVR throughout seasons. The answer is “Our social circle, reference points, colleagues don’t represent the universe or any NCCS fraction of the universe in any manner”. Our reference point sample size is so low that by using our personal experiences we are bound to become biased. When we are talking about NCCS A TG, we are talking about 11 Crore people. Hence TAM/BARC’s sample size is much better than our sample for reference, which cannot be more than few hundreds.

Does it mean that niche channels do not have any significance in media planning? No it doesn’t. The problem is with defining TG for the brand. Most of the times the TG is defined in terms of broad demographic factors such as Socio-Economic Classification, Gender, Age Group, Geographies etc. An advertiser needs to further fragment a TG based on his/her behavioural aspects, Psychographic aspects & media consumption habits, through a more detailed personalised research, other than existing media tools. A premium four-wheeler brand should not say that its TG is NCCS A1 Male. There are 90 lakh people in India who qualify his criteria. Not everyone would like to afford a car worth Rs 40 lakh. The brand has to define other qualitative aspects of its TG to do a refined media planning, and yes the existing tools such as BARC doesn’t allow us to filter our TG on such qualitative aspects. But that doesn’t necessarily give us (Media Planners) a free hand to use our personal judgement to evaluate or select a genre/channel.  Even a small survey of 100 relevant samples may throw a very different picture than our preconceived notion.

We have seen niche genres building brand and creating premium imagery in many cases. But doing the same by a scientific mean will surely yield better results for a brand.

(Ideas expressed are the author’s personal views)

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