As an entertainment executive, you want to make the best content decisions in order to drive engagement, attract new subscribers, retain current ones, and maximize your revenue. One tool that can help you do this is demand data, which can be especially valuable in content valuation.
Let us take the example of "Hunted (AU)" and see how demand data can be used to make more informed content decisions. The show has good demand in France and is 3.7 times more in demand than the average show over the last 30 days. This could be an indicator of its popularity and potential for success in that market. However, the show has dropped in rank by 4874 spots during January in France. This indicates a decreasing trend in demand, highlighting the importance of regular content analysis to determine whether a show's popularity is rising or falling. In this case, it would be helpful to examine why the demand is decreasing and identify any patterns in the data.
Another way to use demand data is to identify other shows that fans of "Hunted (AU)" also like. This can help with programming decisions and content acquisition. The data shows that fans of "Hunted (AU)" also like "Survivor," "The Great British Bake Off," and "The Traitors (NZ)," among others. This information can be used to inform recommendations for similar content that could attract viewers.
Demand data can also be used to assess a show's travelability, which quantifies a show's international demand relative to its home market. In the case of "Hunted (AU)", its travelability is poor, indicating a lack of interest in the show globally. This information can be used to decide whether to invest in marketing the show to a wider international audience or whether to focus on markets where demand is higher.
Demand data can also measure momentum, the pace of growth, and longevity, which measures how well audience demand is maintained over time. In the case of "Hunted (AU)," momentum is good and the show has experienced increased popularity over the last 30 days, which could be attributed to effective marketing campaigns or an increase in word-of-mouth recommendations. However, the show's longevity is poor, suggesting that its audience may not be sustained over time and that the show may not have long-term appeal.
Another useful feature of demand data is its ability to inform the selection of IP for franchises or spin-offs. In the case of "Hunted (AU)," its franchisability is poor, indicating that it may not have the potential for spin-offs or franchises. However, this information can be used to make strategic decisions around investing in developing new franchises or spin-offs.
Finally, demand data can inform targeting for distribution, benchmarking against competitors, pre-release marketing optimization, and optimal pricing and release strategies. By utilizing demand data effectively, entertainment executives can make informed content, acquisition, and distribution decisions that will help drive engagement and maximize revenue.
