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 today face many complex questions when it comes to producing, distributing, or programming content for their target audience. Questions about content valuation, the value of a content library, franchise and spin-off potential, brand partnerships, and genre trends are just a few among many. Thankfully, demand data provides key insights on content popularity and audience preferences. In this article, we will examine how demand data can be used to help executives make informed content decisions using Rebelde Way in Argentina for October 2023 as an example.
Demand data reveals a lot about the strength of a particular show's popularity. For instance, the demand for Rebelde Way was outstanding in Argentina for the last 30 days, with 8.2 times the audience demand of the average show in the country. This high demand can be used to estimate the content valuation of the show and assess the value of the content library to a platform over time. Additionally, executives can leverage demand data to make informed decisions about the exclusivity of the show on their platform. A high level of demand for a show gives executives the confidence to invest more in content creation or acquisition.
The demand data can also inform executives of the popularity of Rebelde Way compared to other shows in Argentina and globally. The show was higher in demand than the vast majority of romance titles in Argentina, ranking at the 99.8th percentile for the genre. Executives can leverage this information to benchmark their show's demand against other titles on the market, adjust programming for similar genres, and plan their pre-release marketing campaigns.
Moreover, audience demand plays a crucial role in deciding the acquisition of a new series or renewing an existing one. In the case of Rebelde Way, its rank dropped 33 spots in October, and audience demand decreased by 6.5% in Argentina during that month. Executives can use this information to assess the show's suitability for their lineup, record advertising performance, and determine the optimal release strategy for the content.
The demand data can also indicate the potential growth of Rebelde Way'S global audience. Comparing the show's performance on a 1-year rolling basis vs. the last 30 days, we noticed a 1.9% increase in peak demand. The show's average demand on a rolling year basis was 7.3 times the average title compared to 8.2 times the title average for the last 30 days. This shows that Rebelde Way has increased in popularity significantly in recent times.
Finally, examining the top ten global markets where "Rebelde Way" is most in-demand over the last 30 days revealed that Argentina is a highly popular market for the show, followed by Ecuador, Paraguay, Uruguay, and Peru, among others. This information can help distribution companies value the show's international appeal and estimate its travelability. Additionally, it helps content distributors locate whitespace opportunities and decide the most optimal content pricing for each geographic market.
In conclusion, demand data enables executives to make informed decisions about valuing content, programming, renewals and regional content pricing by providing insights on popularity trends, the value of a content library, audience preferences, and franchise and spin-off potential. With the help of demand data, executives can ensure a higher return on content investment, optimize their marketing campaigns, and improve subscriber acquisition and retention.
This is Rebelde Way'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 Rebelde Way travels internationally.
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Our TV audience measurement dataset is truly global. Discover how popular Canal 9‘s Rebelde Way 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 Argentina, 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 Canal 9 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 Rebelde Way, for example, can be assessed for a market e.g. Argentina, which can then be benchmarked against genre averages (e.g. Teen Drama), using our globally standardized Demand Expressions® metric.
This page has been modified on April 22, 2024, 2:03 p.m. PST using global television demand datasets from Parrot Analytics for Rebelde Way in Argentina. We provide our partners with deep television workflows to help them drive better and more informed content licensing strategies. Contact us today to find out more.
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