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.
For entertainment executives looking to make informed content, acquisition, distribution, or programming decisions, demand data is critical. It provides insight into the popularity of a TV show in a specific market, season, or time frame. Using demand data for the Indian TV drama "Rishta Likhenge Hum Naya," we can provide insights into how this information can be used to inform strategic decisions.
One of the primary applications of demand data is content valuation. It helps answer questions regarding the dollar value contribution of a title and how it contributes to the platform's revenue. In the case of "Rishta Likhenge Hum Naya," we can see that it has 2.2 times the audience demand of the average show in India over the last 30 days. This is an excellent indication of how popular the show is compared to other content in the market.
Another use of demand data is for acquisition decisions. With the insight that only 8.6% of all TV shows have the level of demand that "Rishta Likhenge Hum Naya" has, entertainment executives can determine the viability of acquiring the show. Additionally, examining the top 10 global markets where the show has been most in-demand over the last 30 days can help platforms assess whether they should acquire the rights to distribute the show in those markets.
Content distribution also benefits from demand data insights. Understanding where the show is most popular can help entertainment companies decide where to invest in distributing their content. For example, "Rishta Likhenge Hum Naya" is most in-demand in India, suggesting that the show's creators focus on advertising and outreach there to sustain audience engagement.
Moreover, programming decisions can be informed by demand data. Understanding the show's rank in its genre, the audience it appeals to, and how its demand compares to other titles can be exceedingly useful in determining its potential for sustaining an audience. For example, this show ranks in the 97.7th percentile in the romance genre in India in March, which means it has higher demand than 97.7% of all romance titles in the market. However, the data also shows that the demand for the show has decreased by 78.3% in March 2024. This decrease in demand suggests that the creators should examine factors affecting its popularity.
Finally, demand data can inform long-term strategic decisions regarding future content investment. By examining the show's travelability and longevity, entertainment executives can decide how suitable it is for their global expansion plans. In the case of "Rishta Likhenge Hum Naya," the show's franchisability is poor, and its reach is just okay. This data is an indication that the show might not be as profitable or sustainable in the long run, despite its current high demand in some markets.
In conclusion, the demand data for "Rishta Likhenge Hum Naya" shows how executives of media and entertainment companies can use insights to make more informed content, acquisition, distribution, and programming decisions. The show has high demand in India and some global markets, but it has also experienced a recent decrease in popularity. Entertainment executives can use the data to assess the show's commercial viability and its potential for sustaining and growing its audience.
This is Rishta Likhenge Hum Naya'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 Rishta Likhenge Hum Naya 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 Sony Entertainment Television (India) 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 Rishta Likhenge Hum Naya, for example, can be assessed for a market e.g. India, which can then be benchmarked against genre averages (e.g. Mystery Drama), using our globally standardized Demand Expressions® metric.
This page has been altered on April 22, 2024, 2 p.m. PST using global tv demand content analytics from Parrot Analytics for Rishta Likhenge Hum Naya in India. We provide our partners with valuable TV series workflows to help them drive better and more informed content acquisition strategies. Contact us today to find out more.