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 industry executive, there are many decisions that have to be made every day, such as how much to spend on content, what content to acquire, what genre to focus on, how to optimize a marketing campaign, how to retain and acquire subscribers, among others. Using the example of "Star Academy" in France, we can see how demand data can be used to make more informed content decisions.
One way demand data can be used is to inform content valuation. With the ability to determine how a title drives engagement across a platform's catalog and estimate the ROI, it is possible to make data-driven decisions about what content to invest in. In the case of "Star Academy," it achieved the peak rank of #2 in France and has 29.1 times the audience demand of the average show in France over the last 30 days. This high demand level reveals the title's economic value and indicates why it should be considered a strategic asset for a streaming platform. Additionally, the show's high longevity and momentum ratings suggest there may be a strong demand for the series among consumers in different markets, making it a valuable asset for content distribution.
Demand data can also inform decisions related to supply and demand. For example, it can help content executives identify the type(s) of content that present opportunities for acquisition or production. In the case of "Star Academy," the show has excellent demand levels in France. This data could suggest that investing in another reality singing show could be beneficial if it's well-executed.
Another use of demand data is as a tool for competitive benchmarking. By comparing "Star Academy" to other titles available on the market, it becomes possible to identify areas where it is doing well and where it could improve.
Demand data, particularly as seen through the Parrot Pulse, can also be used to inform decisions about programming by providing insight into the show's momentum and reach. In the case of "Star Academy," the information provided suggests there is some potential for spin-offs, although the show's current reach and franchisability needs improvement.
Finally, demand data can help with subscriber retention and acquisition. By analyzing what titles perform well relative to a platform's catalog and what titles attract new subscribers, executives can make informed decisions about what to acquire or produce. Additionally, as the demand for "Star Academy" decreased by 49.8% in France during March 2024, this data might suggest that the platform should look for new content options to satisfy the changing viewer demands.
In conclusion, demand data is valuable to executive decision-making in the TV industry. The data can inform decisions regarding content valuation, supply and demand, programming, and even subscriber retention and acquisition strategies. As demonstrated by the case of "Star Academy," the insights gained through demand data can be used to make informed, data-driven decisions that can lead to better business outcomes.
This is Star Academy'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 Star Academy travels internationally.
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Our TV audience measurement dataset is truly global. Discover how popular TF1‘s Star Academy 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 France, 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 TF1 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 Star Academy, for example, can be assessed for a market e.g. France, which can then be benchmarked against genre averages (e.g. Competition Reality), using our globally standardized Demand Expressions® metric.
This page has been updated on April 22, 2024, 2:02 p.m. PST using tv demand content analytics from Parrot Analytics for Star Academy in France. We provide our partners with essential TV industry expertise to help them drive better and more informed content investment strategies. Contact us today to find out more.