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.
Entertainment executives are constantly seeking ways to maximize their investments in content, whether it involves strategic decisions around programming, acquisition, distribution, or content valuation. In order to do this, they need access to comprehensive data that can inform their decision-making process. One powerful tool for achieving this is demand data.
Take for example the case of "Cuando Me Enamoro", a TV series that started airing in 2011. By analyzing the show's audience demand in March 2024 in the United States, we can gain valuable insights to inform decisions around content valuation, as well as acquisition and programming choices.
One important question that can be addressed through demand data is the value of a content library. In the case of "Cuando Me Enamoro", we can evaluate whether it is worth investing in the show based on its demand data. In the United States, the show has a demand that is 2.9 times the average for all TV shows in the country, indicating that it is appealing to a significant audience. This also suggests that "Cuando Me Enamoro" possesses some inherent cultural value that attracts a loyal following.
Demand data can also help answer more specific questions around programming decisions. For instance, it is important to understand whether audiences will engage with a show over time or lose interest. In this case, we can see that demand for "Cuando Me Enamoro" has been decreasing over the past 90 days, though it saw a spike in mid-March. This information is essential in gauging whether a show like "Cuando Me Enamoro" is likely to drive subscription growth on a platform or increase engagement with subscribers. In the longer term, the show has maintained audience demand reasonably well, so may continue to deliver returns over time.
Demand data is also valuable for assessing the performance of a show relative to other titles in its genre or country of origin. Based on the analysis of "Cuando Me Enamoro", it is performing well in the romance genre in the United States, where it ranks in the 94.3rd percentile of all titles. However, it should be noted that travelability is low, which indicates that the show may struggle to break through in markets outside of its country of origin (Mexico).
Another important question that demand data can answer is around acquisition decisions: what type(s) of content exhibit opportunity to acquire or produce? Based on the demand information provided about "Cuando Me Enamoro", it stands out as a show that has a dedicated following in multiple countries, including Mexico (where it reached an outstanding audience demand of 4.4x). This makes it a candidate for acquisition if the goal is to appeal to a diverse audience that spans multiple markets.
Finally, demand data is crucial in making distribution decisions for content. Executives need to know how appealing a given show is in specific markets in order to optimize its release strategy and pricing. In the case of "Cuando Me Enamoro", it has high demand in the United States, Brazil, Colombia, Argentina, Ecuador, Spain, Venezuela, and Peru. This information is critical for determining which platforms to target for distribution and how to tailor the marketing strategy for the best possible reach.
In conclusion, by leveraging demand data, entertainment executives have the power to make more informed content, acquisition, distribution, and programming decisions. On the example of "Cuando Me Enamoro", we see how demand data can help assess the value of a content library, evaluate a show's performance over time, understand its audience appeal by genre or country of origin, and make informed acquisition and distribution decisions. All of which is instrumental in maximizing investment returns on content and keeping audiences engaged.
Cuando Me Enamoro's travelability to the United States in the last 30 days is 35%, which means that the audience demand for Cuando Me Enamoro is 35% of the demand in its country of origin, Mexico. Click through to another market to discover how well Cuando Me Enamoro travels internationally.
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Our TV audience measurement dataset is truly global. Discover how popular Las Estrellas‘s Cuando Me Enamoro 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 Las Estrellas 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 Cuando Me Enamoro, for example, can be assessed for a market e.g. United States, which can then be benchmarked against genre averages (e.g. Soap Opera), using our globally standardized Demand Expressions® metric.
This page has been refreshed on April 22, 2024, 2:03 p.m. PST using demand datasets from Parrot Analytics for Cuando Me Enamoro in the United States. We provide our partners with valuable SVOD workflows to help them drive better and more informed content acquisition strategies. Contact us today to find out more.
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