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.
The success of "Stargate SG-1" in March 2024 in the United Kingdom demonstrates the power of using demand data to make informed content decisions. The outstanding demand of 13.7 times the average over the last 30 days suggests that viewers in the United Kingdom have a significant appetite for this TV series. This strong demand can be attributed to a variety of factors, including the storyline, cast, and production value. Demand data provides an economic valuation system that enables entertainment executives to assess the value of a title and reveal its dollar value contribution to any platform, in any region. This allows for a more informed content valuation process when making acquisition and distribution decisions.
One example of how demand data can provide valuable insights for entertainment executives is by identifying audience preferences to optimize content production. Using the example of "Stargate SG-1", we can learn that fans of this show also enjoy titles such as "Rick And Morty", "The X-Files", and "The Mandalorian". Information like this can be used to guide content production. In this instance, the common thread between these titles is their sci-fi/fantasy genre, which appears to be resonating with viewers. Furthermore, demand data can help determine the best release strategy and pricing for a title by identifying spikes in demand as seen with "Stargate SG-1" in late March 2024, indicating a potential increase in viewer interest.
The Parrot Pulse for "Stargate SG-1" provides an independent measure of its global performance across six dimensions, including travelability, longevity, momentum, franchisability, and reach. Comparing this show's performance on a rolling year basis versus the last 30 days highlights the increasing popularity of this series. This trend can be used to inform programming decisions, indicating that "Stargate SG-1" may be a strategic asset for an SVOD platform.
Demand data can also be used for competitive benchmarking, mapping local whitespaces, and identifying under-monetized titles. For example, demand data reveals "Stargate SG-1" to be in the 99.4th percentile for drama titles in the United Kingdom, indicating that there may be an opportunity for other drama titles to compete against this series in terms of content and viewership. Similarly, demand data from different regions could inform decisions about expanding global SVOD, such as the fact that "Stargate SG-1" displays excellent travelability metrics.
In conclusion, the use of demand data can provide valuable insights for entertainment executives across many aspects of their decision-making process. Through demand data, it is possible to determine content valuation, recognize audience preferences, optimize content production, identify under-monetized titles, and inform programming decisions. Demand data is a powerful tool that can allow entertainment executives to make more informed content, acquisition, distribution, and programming decisions.
Stargate SG-1's travelability to the United Kingdom in the last 30 days is 62%, which means that the audience demand for Stargate SG-1 is 62% of the demand in its country of origin, United States. Click through to another market to discover how well Stargate SG-1 travels internationally.
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Acquire the best shows from partners such as syfy to fortify your competitive position in the United Kingdom. Contact us now to access audience taste clusters weeks ahead of a premiere, resulting in high impact campaigns for titles (e.g. Stargate SG-1), including those that have not even been released. Leverage a return-focused selection criteria for title acquisition by incorporating country-specific trend and market demand factors.
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Our TV audience measurement dataset is truly global. Discover how popular syfy‘s Stargate SG-1 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 Kingdom, 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 syfy 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 Stargate SG-1, for example, can be assessed for a market e.g. United Kingdom, which can then be benchmarked against genre averages (e.g. Sci-fi Drama), using our globally standardized Demand Expressions® metric.
This page has been modified on April 22, 2024, 2:01 p.m. PST using global television demand data from Parrot Analytics for Stargate SG-1 in the United Kingdom. We provide our partners with comprehensive TV industry capabilities to help them drive better and more informed content sales strategies. Contact us today to find out more.