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 can use demand data to make more informed decisions about content, acquisition, distribution, and programming. For instance, let us take the example of the TV series "Ugly Betty," which can help the executives to understand how they can use demand data to inform their decisions.
First, content valuation can use demand data to understand how much a title is worth. In the case of "Ugly Betty," it has a demand that is good compared to the average show in France. It ranks at 2.0 times the audience demand of the average show in France over the last 30 days, and 8.6% of all TV shows have this level of demand. Therefore, such demand data can help executives determine the worth of a show and the revenue contribution of a specific title.
Secondly, executives can use demand data to make more informed acquisition decisions. For instance, they can use "Ugly Betty" audience data to assess its ability to mitigate churn and drive subscriptions. Also, they can use the demand data to determine if the show is appropriate for a specific platform or network. For example, in France, the show had a demand of 2.0 times the average title, ranking at #1039 in the market. However, the demand for the show has decreased by 58.5% during January. Such information can assist executives to decide whether to acquire or renew the series for their platform or network.
Thirdly, it can help executives with programming decisions. For example, they can use the demand data on "Ugly Betty" to identify the target audience for the show. They can also use affinity analysis to identify the best talent or brand to feature with the program to expand the audience acquisition or retention. Additionally, executives can use such demand data to assess the optimal release strategy and pricing. For instance, in France, the demand for the show spiked in late January 2024, indicating that such a period is an excellent time to release related TV content.
Fourthly, executives can use demand data to inform distribution decisions. For instance, they can use the travelability dimension to assess how much global appeal the title has compared to other titles. They can use demand data to quantify how much the show is worth and decide if to sell it to another streaming platform. For instance, the demand for "Ugly Betty" in France was 27% of the demand in the United States, its country of origin.
Finally, executives can use demand data to inform the performance of a TV show over time. For instance, they can compare the performance of "Ugly Betty" on a 1-year rolling basis with the last 30 days and gain insightful insights. In the last 30 days, the demand for the show has increased by 40.8% compared to the previous year. Moreover, they can understand the global markets where the show is most demanded, compare such data, and make vital decisions.
In conclusion, by leveraging demand data, entertainment executives can make informed decisions on content valuation, acquisition, distribution, programming, performance, and more. Executives can use such data to determine how much their content is worth, acquire or renew TV series, assess the target audience and optimal release strategy, assess global markets, and determine if a title fits for a platform or network. Therefore, they can use demand data to remain competitive and relevant in the entertainment industry.
Ugly Betty's travelability to France in the last 30 days is 29%, which means that the audience demand for Ugly Betty is 29% of the demand in its country of origin, United States. Click through to another market to discover how well Ugly Betty travels internationally.
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Our TV audience measurement dataset is truly global. Discover how popular abc‘s Ugly Betty 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 abc 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 Ugly Betty, for example, can be assessed for a market e.g. France, which can then be benchmarked against genre averages (e.g. Soap Opera), using our globally standardized Demand Expressions® metric.
This page has been recreated on April 18, 2024, 2:03 p.m. PST using global tv demand datasets from Parrot Analytics for Ugly Betty in France. We provide our partners with deep media industry know-how to help them drive better and more informed content distribution strategies. Contact us today to find out more.