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.
If you are a TV executive, using demand data to inform your decision-making is key. Here we take Dance India Dance as an example, highlighting how demand data can offer valuable insights to make informed decisions.
Firstly, using Parrot Analytics content valuation system, demand data can reveal the dollar value contribution of any title to any platform in any region. If you are looking to acquire new content, knowing how much a title is worth, how much of its value is being driven by demand for one of its stars, and what the baseline value of a title is, is all valuable information to have. For Dance India Dance, the show has good demand in India, its number one global market, with increased demand in early February 2024. However, the demand for the show has decreased by 83.3% during February in India.
Additionally, the demand for the show is compared to the average demand for a title in India, and the show is doing well with 3.0 times the audience demand of the average show in India over the last 30 days. This indicates that the show is popular, and content executives can be confident that there is an audience for the show. However, they should be aware that this show has higher demand than 99.3% of all reality titles in India, so trying to recreate the success of this show could be unwise.
Using demand to inform how to optimize pre-release marketing can also be very effective. Momentum, which measures the pace of growth, is good for Dance India Dance. This information can be used to inform the marketing strategy for the show, highlighting the current momentum to entice new viewers. On the other hand, there has been a recent decline in demand for the show, which highlights that promoting the show before it loses popularity is essential.
If you are a TV executive looking to expand your content globally, the travelability of a show is an important metric to examine. Unfortunately, this metric for Dance India Dance is poor, quantifying a show's international demand relative to its home market. Therefore, tailoring the marketing and advertising campaign to international markets is key to building up interest in the show overseas.
Demand can also help with decisions concerning supply and demand, by identifying opportunity markets for content distribution. By mapping local white spaces and understanding where a certain genre is popular, for example, TV executives can make informed decisions concerning which content to produce or acquire. If you are looking to acquire new content, knowing how much a show is worth on a global scale is very useful, and demand data enables TV executives to value content and quantify its platform-specific marginal revenue contribution.
In conclusion, demand data provides valuable information for TV executives in making informed decisions regarding content acquisition, production, and distribution, programming, and content valuation. Dance India Dance's performance can be used to highlight some of the key benefits of using demand data to inform decision-making, from content valuation to supply and demand analysis. By taking advantage of the insights offered by demand data, TV executives can make more informed decisions, optimize their marketing and advertising strategies, and increase their chances of success in an increasingly competitive global market.
This is Dance India Dance'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 Dance India Dance 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 India, 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 Zee TV 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 Dance India Dance, for example, can be assessed for a market e.g. India, which can then be benchmarked against genre averages (e.g. Competition Reality), using our globally standardized Demand Expressions® metric.
This page has been revised on March 28, 2024, 3:34 a.m. PST using tv demand datasets from Parrot Analytics for Dance India Dance in India. We provide our partners with smart content know-how to help them drive better and more informed content advertising strategies. Contact us today to find out more.