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, one of the most valuable factors you can consider in making informed content decisions is audience demand data. Using Parrot Analytics' demand data for "Monsters At Work" in the United States, we can provide insights into how demand data can be leveraged to help with content valuation, acquisition decisions, distribution decisions, and programming decisions.
Firstly, content valuation is vital when deciding how much to spend on content, and with its strong demand data, "Monsters At Work" can be considered a strategic asset for a streaming platform. Parrot Analytics content valuation system is based on demand data, which enables an economic valuation system powered by global content demand and supply. This system reveals the dollar value contribution of any title, to any platform, in any region, allowing executives to determine the ROI a specific title will bring for any given platform.
Additionally, you can use demand data to value the content you intend to acquire or distribute. By leveraging demand data, you can calculate the platform-specific marginal revenue contribution of a title, and how it drives engagement across the rest of your catalog. You can also estimate cannibalization of audiences if a title is available on multiple services and assess the value of exclusivity. In the case of "Monsters At Work," it has a strong demand globally, making it a valuable asset for distribution in international markets.
Demand data can also be leveraged for making programming decisions. First, looking at the genre, "Monsters At Work" ranks at the 87.0th percentile in the comedy genre, indicating that it has higher demand than 87.0% of all comedy titles in the United States. This is a vital factor to consider when determining which TV shows will help to acquire or retain subscribers. Additionally, examining demand data for the show in comparison with other titles on the platform can inform programming decisions.
Further, "Monsters At Work" audience demand has recently shown an increase in the United States, indicating that the content is resonating with US audiences. Our analysis also reveals that other shows that fans of "Monsters At Work" also like are "In The Dark," "The Simpsons," "Rick And Morty," and "Loki." This data can be used to inform programming decisions, such as identifying trending genres to develop new content or acquiring popular titles that may attract new subscribers.
Lastly, demand data, when analyzed over time, can be useful in determining the financial success of a show. For "Monsters At Work," examining its demand performance on a rolling year basis versus the last 30 days reveals insights into how popular the show is with audiences. The show's average demand on a rolling year basis was 2.9 times the average title compared to 3.0 times the title average for the last 30 days - this indicates the show has increased popularity over time.
In conclusion, audience demand data is a powerful tool that entertainment executives can use to inform their content decisions. In the case of "Monsters At Work," our analysis reveals that it has a good level of demand in the United States and is outperforming the average TV show in each of its top 10 global markets. Leveraging this data can help executives make informed decisions around content valuation, acquisition, distribution, and programming, ultimately leading to more successful outcomes for their businesses.
This is Monsters At Work'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 Monsters At Work travels internationally.
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Our TV audience measurement dataset is truly global. Discover how popular Disney+‘s Monsters At Work 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 the United States, 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 Disney+ 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 Monsters At Work, for example, can be assessed for a market e.g. United States, which can then be benchmarked against genre averages (e.g. Animated Sitcom), using our globally standardized Demand Expressions® metric.
This page has been reconstructed on March 29, 2024, 2:01 a.m. PST using global tv demand content analytics from Parrot Analytics for Monsters At Work in the United States. We provide our partners with meaningful subscription-video-on-demand analyses to help them drive better and more informed content sales strategies. Contact us today to find out more.