The Demand Distribution curve illustrates how a TV show’s popularity compares to the demand benchmark, which is a measure of the average demand across all titles. The curve is divided into performance buckets, ranging from “Below Average” to “Exceptional”. A show falls into one of these performance buckets depending on how many times more or less demand it has compared to the demand benchmark.
The show’s performance is market-specific, e.g. the same show can be in the “Average” range in the United States and in the “Good” range in France.
As an example, if a show has 9 times more demand than the demand benchmark, it falls in the “Outstanding” performance range; only 2.7% of all shows in the market reach this high level of demand.
As a TV executive working for an OTT platform, demand data can be beneficial in making informed content decisions and acquisition decisions. Demand data can also be useful for distribution and programming decisions. Let's take the example of the Indian music reality show, "Sa Re Ga Ma Pa," to understand how the use of demand data can aid in these decisions.
Content Valuation:
Using the demand data of the show, we can determine its value in India. "Sa Re Ga Ma Pa" has 2.6 times the audience demand of the average show in India, indicating that it is performing well. It is among the top 8.6% of all TV shows in India. However, comparing the demand of the show on a yearly basis vs. the last 30 days shows a decrease in popularity, which needs to be considered in content valuation.
Programming Decisions:
By examining the top 10 global markets where "Sa Re Ga Ma Pa" is most in-demand over the last 30 days, we can find that the show outperforms the demand of the average TV show in each of these markets. Furthermore, the pulse data indicates that the show has excellent momentum and longevity. The fact that the show's momentum is outstanding means that it is on the rise as more people continue expressing demand. Such data can help in making programming decisions, where we can continue to air the show and/or acquire more seasons as the demand for the program grows.
Acquisition Decisions:
Studying the demand of fans who like "Sa Re Ga Ma Pa" can enable us to make informed acquisition decisions. Knowing what else appeals to the fans of the show helps us understand why they are drawn to the show and which other content we should acquire that fits their interests.
Distribution Decisions:
As per the Parrot Pulse for "Sa Re Ga Ma Pa," its travelability is weak, indicating that it does not have much international demand apart from its home market. Therefore, if we consider distributing the show to other countries, we need to take this factor into account.
Subscriber Retention and Acquisition:
Demand data can be used in subscriber retention and acquisition decisions by identifying which titles will keep existing subscribers happy and which titles will attract new subscribers. By understanding the taste clusters of current audiences, we can have a better idea of other content that they might enjoy. We can acquire or produce such content to keep subscribers engaged. Similarly, we can take the help of demand data to make acquisition decisions that will help us grow our audience.
Optimal Release Strategy:
The demand spike in late April 2024 for "Sa Re Ga Ma Pa" for India highlights the importance of having insight into demand data for an optimal release strategy. Using such data, we can determine the best time to release the show for maximum viewership.
In conclusion, demand data can help entertainment executives make informed content, acquisition, distribution, and programming decisions. Using demand data, we can quantify the value of any title, assess a TV series' ability to drive subscriptions and mitigate churn, and estimate cannibalization of audiences if a title is available on multiple services. Furthermore, using the demand data for "Sa Re Ga Ma Pa," we can see how the show's demand is changing over time and also in different markets, which enables us to make sound strategic decisions.
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Our TV audience measurement dataset is truly global. Discover how popular Zee TV‘s Sa Re Ga Ma Pa is in any of the following selected markets. Need data for other markets? Find out more about DEMAND360LITE.
Parrot Analytics is the leading global content demand analytics company for the multi-platform business of television. With the world’s largest TV audience demand dataset, the company currently tracks more than 1.5B daily expressions of demand in 100 languages, not only in India, but also in 100+ other markets around the world to reveal the television content that consumers watch (viewership) and give their attention to the most.
Parrot Analytics' television demand data highlights the global TV content monetization opportunities for Zee TV and thousands of TV studios, linear networks, broadcasters, pay TV providers and OTT / SVOD platforms.
Unlike TV ratings, our DemandRank TV rating system ensures that important demand signals are weighted more heavily than others: The more consumer effort required; the more importance is attached to each signal. Once all the signals are weighted and combined, the audience demand for Sa Re Ga Ma Pa, for example, can be assessed for a market e.g. India, which can then be benchmarked against genre averages (e.g. Competition Reality), using our globally standardized Demand Expressions® metric.
This page has been adjusted on April 22, 2024, 2:04 p.m. PST using global demand analytics from Parrot Analytics for Sa Re Ga Ma Pa in India. We provide our partners with comprehensive content analyses to help them drive better and more informed content advertising strategies. Contact us today to find out more.