As an entertainment executive, demand data can be crucial in making informed decisions about content. Using the example of "9-1-1: Lone Star" for the month of August 2023 in the United States, we can showcase the potential insights that demand data can provide.
Content Valuation:
One popular use of demand data is content valuation, which can help determine how much a specific title is worth. Parrot Analytics content valuation system uses demand data to reveal the dollar value contribution of any title to any platform, in any region. By studying the demand of "9-1-1: Lone Star", executives can determine its value and contribution to their platform.
Programming Decisions:
Demand data can also inform programming decisions. By analyzing a show's performance on a rolling year basis compared to the last 30 days, executives can identify trends and determine whether the show is losing or gaining popularity. In the case of "9-1-1: Lone Star", its average demand has decreased over the last 30 days, indicating that it may not be performing as well as it previously did. Moreover, the detailed insights about the targeted demographic of the show's audiences from affinity analysis coud help executives plan programming more effectively.
Distribution Decisions:
Demand data can be used to identify the top global markets for a TV series. For instance, "9-1-1: Lone Star" outperforms the demand of the average TV show across all markets, especially in China, where demand is outstanding. By recognizing a show's most popular markets, executives can formulate distribution strategies that capitalize on growth potential.
Acquisition Decisions:
One common challenge faced by content distributors is identifying titles that would perform well on their platform. With demand data available, such as that for "9-1-1: Lone Star", acquisitions teams can identify shows that are highly demanded by audiences within specific markets or genres.
Marketing Strategy:
Demand data can assist in determining the timing and scope of marketing campaigns. In the case of "9-1-1: Lone Star", the demand spike in late August indicates an increase that executives could capitalize on marketing efforts to drive further growth. Furthermore, we could use the results of taste clusters to expand the show's audience alignment, advertising and ultimately increasing show's popularity.
In conclusion, demand data can help executives make more informed decisions about content, acquisitions, distribution, and marketing. By utilizing this data for analysis of a show's performance, executives can better position their platform amid ever-increasing competition for viewership and can save a substantial amount of capital on content budget.
