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 and industry stakeholders can leverage demand data to make more informed content decisions and distribution decisions. Demand data can also assist with programming decisions by providing insights into audience behavior. One way to apply demand data is content valuation, which can help determine a series' worth, estimate the value of a content library, and assess a TV series' ability to drive subscriptions and mitigate churn. With specific reference to "Gossip Girl," let's explore how demand data can add value to industry decision-makers.
Demand data can determine content value by revealing the dollar-value contribution of any title to any platform in any region. Based on the demand metric for "Gossip Girl," it's clear that it has 3.3 times the audience demand of an average show in Italy over the last 30 days. Another way of putting it is that only 8.6% of all TV shows have this level of demand, and its demand has been increasing recently. This data can help OTT platforms and linear network executives determine their content acquisition strategy, negotiate new content deals, and evaluate and optimize existing content portfolios.
Demand data also informs scalable concept testing, allowing industry stakeholders to identify the most popular elements of existing content to avoid investment risk in future productions. For instance, the metadata for "Gossip Girl" shows in the top 10 global markets where it is most in-demand, it out-performs the demand of the average TV show (1x) in each of these markets. This suggests that the show has a broad appeal and that future productions that focus on similar elements, such as teenage drama infused with mystery, may attract significant demand in various markets globally.
Demand data is also useful in assessing a show's travelability. Gossip Girl has an outstanding travelability. This means that its international demand exceeds its home market for the show delivered an audience demand of 21% in Italy compared to its country of origin, the United States. This indicates to a distributor or OTT platform that a show may perform well in international markets.
With respect to content distribution, demand data helps content distributors assess global market gaps and opportunities. Based on the metadata of "Gossip Girl," the show is doing well in France, Germany, Ukraine, Canada, Brazil, the UK, and Spain. A content distribution company can use this data to determine where in the world the show is generating maximum revenue and consider distribution strategies accordingly.
Demand data can also impact SVOD platforms' programming decisions, specifically when it comes to determining which titles to acquire to retain and grow audiences. The metadata of "Gossip Girl" revealed that audience demand for the show has increased in Italy by 9.1% in March. This implies that the show is still attracting new viewers and could appeal to new subscribers. Providing actionable insights into data that will enhance the return on investment of a TV series from a marketing and programming perspective.
In conclusion, leveraging demand data can help industry stakeholders make informed content decisions, allowing them to reduce risks and increase their likelihood of delivering successful content. By analyzing "Gossip Girl's" demand metrics, it's clear that content valuation is improved through demand data. It also shows how global travelability, momentum, and franchisability can be used to confirm the potential success a show or franchise may hold in different markets.
Gossip Girl's travelability to Italy in the last 30 days is 26%, which means that the audience demand for Gossip Girl is 26% of the demand in its country of origin, United States. Click through to another market to discover how well Gossip Girl travels internationally.
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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 Italy, 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 the cw 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 Gossip Girl, for example, can be assessed for a market e.g. Italy, which can then be benchmarked against genre averages (e.g. Teen Drama), using our globally standardized Demand Expressions® metric.
This page has been adjusted on April 22, 2024, 2:03 p.m. PST using demand analytics from Parrot Analytics for Gossip Girl in Italy. We provide our partners with far-reaching television workflows to help them drive better and more informed content marketing strategies. Contact us today to find out more.