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, you are constantly looking for ways to make more informed content decisions. That's where demand data comes in. By analyzing audience demand for popular TV shows like "Soy Luna," you can gain valuable insights into what works and what doesn't in the world of entertainment.
One way demand data can be used to help make content decisions is through content valuation. By using demand data, you can determine how much your show is worth, how much of your show's value is being driven by demand for one of its stars, what the baseline value of your show is, and how your show is performing as an acquisition-driving or churn-reducing title. According to Parrot Analytics demand data for "Soy Luna" in France during March 2024, the show has a good demand with 7.9 times the audience demand of the average show in France over the last 30 days. It is ranked at the 98.7th percentile in the family genre that means that it has higher demand than 98.7% of all family titles in France. This demand data can be used to estimate the show's value on a content platform.
Demand data can also help with decisions concerning supply and demand. You can use demand data to discover which type(s) of content exhibit the opportunity to acquire or produce. By examining the top 10 global markets where "Soy Luna" is most in-demand over the last 30 days, we can learn that it outperforms the demand of the average TV show (1x) in each of these markets: Argentina is the show's number one market globally, followed by Brazil where demand is outstanding. Using demand data to discover the show's popularity in different markets, marketing, and monetization strategies can be optimized.
Demand data can help with decisions involving programming. Knowing how well your show is performing in different markets can help you decide which titles to buy if you want to keep your current audience happy or which titles to buy if you want to grow your audience. By understanding the affinity analysis, you can know the best talent and brand to partner with to expand your audience. For instance, "Soy Luna" achieved the peak rank of #268 in France, and it moved up in its rank by 34 spots during March in France.
Demand data can also be used to help with distribution decisions. By understanding the show's travelability, you can quantify international demand relative to the home market, and this can help you determine which platforms to target for distribution of your content. For instance, the travelability of "Soy Luna" is rated good across all platforms.
Demand data can also uncover under-monetized titles. Using the demand data, you can find new opportunity markets for content distribution. You can also use demand data to uncover which content can rely on its sustained demand and therefore require less marketing spend. For example, "Soy Luna" has good momentum and good franchisability, indicating that the show has spin-off potential.
In conclusion, as a TV executive, using demand data can help you make more informed decisions about content, acquisition, distribution, and programming. The audience demand for "Soy Luna" in France during March 2024 is a good example of how demand data can provide insights into the performance of a TV show. The above questions provide a roadmap for extracting insights from demand data to make more informed content decisions. By leveraging demand data, you can increase the chances of producing successful TV shows and drive more revenue to the platform or the show.
Soy Luna's travelability to France in the last 30 days is 65%, which means that the audience demand for Soy Luna is 65% of the demand in its country of origin, Argentina. Click through to another market to discover how well Soy Luna travels internationally.
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Our TV audience measurement dataset is truly global. Discover how popular Disney Channel‘s Soy Luna 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 Disney Channel 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 Soy Luna, for example, can be assessed for a market e.g. France, which can then be benchmarked against genre averages (e.g. Teen Sitcom), using our globally standardized Demand Expressions® metric.
This page has been renewed on April 19, 2024, 2:02 p.m. PST using television demand content from Parrot Analytics for Soy Luna in France. We provide our partners with smart television industry capabilities to help them drive better and more informed content advertising strategies. Contact us today to find out more.