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.
For executives working in the entertainment industry, data plays a vital role in decision-making, especially when dealing with new content acquisitions, programming decisions, or distribution decisions. Demand data can provide insights into a show's performance in various regions, how it compares to other titles in the genre, and how the demand has changed over a period. In this article, we'll explore how demand data for the Turkish show "Kara Sevda" can help us to make informed content decisions.
Content Valuation:
Content valuation helps to determine the worth of a specific title or content library and its potential contribution to a platform. Demand data-based valuation can answer questions like how much a show is worth, how much value does a star bring to the show, and what is the baseline value of a title. For example, we know that the demand for "Kara Sevda" is good as it has 7.4 times the audience demand of an average TV show in Turkey for the last 30 days. Comparing the demand for the show over the last 90 days, the demand has decreased, indicating a drop in popularity. Combining the show's peak demand of 13.5 times the average over the course of the entire year and 9.0 times the average in the last 30 days, their actual content value can be gauged and evaluated.
Programming Decisions:
Demand data-based insights can be helpful in programming decisions. It can help to identify what is trendy or popular, what genres are resonating with the audience, and what types of content are being consumed in which markets. For example, we know that "Kara Sevda" ranks at the 99.4th percentile in the comedy genre, which means that it has higher demand than 99.4% of all comedy titles in Turkey. We also know that other shows that fans of "Kara Sevda" like are "The Late Show With Stephen Colbert," "The Daily Show," and "Better Call Saul." By understanding what types of content viewers are interested in, executives can strategically select and commission the programs in their portfolio.
Acquisition Decisions:
Demand data can also be used to make informed acquisition decisions. It can provide insights into the market's potential, the audience size, and the type of content that is most in demand. This can include understanding how a show is performing on a global scale, its travelability, longevity, franchisability, and reach. For example, we know that "Kara Sevda" outperforms the average TV show in the top 10 global markets where it's most in-demand. Turkish viewers are most interested in the show, and the demand is good, but countries like Russia and Hungary also have high levels of interest in the show.
Distribution Decisions:
Demand data can also help executives make informed distribution decisions. By understanding the demand for a show on different platforms, regions and audiences, executives can strategically decide where to distribute their content for maximum visibility and engagement. For example, if the demand for "Kara Sevda" is good in Russia, executives can consider broadcasting the show in Russia.
In conclusion, demand data provides valuable insights into the performance of a show and can help executives make informed content decisions. From content valuation to programming decisions, acquisition decisions to distribution decisions, demand data provides a crucial aspect of decision-making that can make or break content performance. By analyzing data and understanding audience behavior, executives can use demand insights to optimize their content strategies and maximize the potential of their content.
This is Kara Sevda's home market and therefore its travelability is 100%; the travelability of a TV show's market of origin is always 100%. Click through to another market to discover how well Kara Sevda travels internationally.
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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 Turkey, 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 Star 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 Kara Sevda, for example, can be assessed for a market e.g. Turkey, which can then be benchmarked against genre averages (e.g. Romantic Drama), using our globally standardized Demand Expressions® metric.
This page has been renewed on April 22, 2024, 2:01 p.m. PST using demand analytics from Parrot Analytics for Kara Sevda in Turkey. We provide our partners with valuable SVOD capabilities to help them drive better and more informed content investment strategies. Contact us today to find out more.