Post-digitisation, viewership data has not thrown up any major surprises. It is, however, too early to reach any conclusions because viewers are still getting to know their set-top boxes. Soon they will begin to explore the delights hidden in that box. That is when television will change from supply-push to demand-pull and the real picture will emerge
Indias television audience measurement currency, TAM Ratings in popular parlance, took an extended holiday through the last calendar quarter of 2012. The break, occasioned by the mandatory analog sunset in the four top metropolitan markets, was designed to ensure that short-term volatilities in viewership behaviour expected to arise on account of change in the domestic set-up did not trigger precipitate actions in media buying. That period has now passed and the ratings are back to business as usual.
What appears to have taken a lot of people by surprise is this: There doesnt seem to be a lot of difference in the absolute and relative pictures, before and after the digital shift. Users are perplexed. Shouldnt such a dramatic shift cause a disruptive change in viewing behaviour? Or is somebody hiding something?
We will look at two distinct areas to find answers to these two questions.
Firstly, lets look at the statistics underlying the television ratings process. Television audience measurement starts with the Establishment Survey. This survey, administered to a random sample of the population that the ratings are meant to measure, produces a cross sectional snapshot of television consumption behaviour. It asks questions such as: How many households in the population? How many television homes? What mode delivers signals to the TV: analog or digital? If digital is access DTH, digital cable, IPTV or something else? Taken together with basic classification, or taxonomy, questions, it builds a fine-grained image of the population whose viewership we propose to study.
The next stage involves establishing market priorities and rank ordering geographies based on these priorities. These rank orders transform into weightages and sampling proportions that will determine the allocation of the proposed metered sample. The higher the market priority and the more diverse the underlying population, the more intensively it will be sampled, to tease out its texture. A culturally diverse Vadodara, for example, would likely need more intensive sampling than a relatively more homogenous Ahmedabad. The next statistical phenomenon is the well-known Paretos Principle. Viewing tends to concentrate around a few big channels and shows with the rest