As a TV executive, you might be interested in making informed content decisions, acquisition decisions, or distribution decisions. This is where demand data from platforms like Parrot Analytics can be helpful in providing insights that can help with your decision-making process. Here are some examples of how demand data for "Luther" can provide insights to assist with strategic decision-making:
1. Content Valuation: Using demand data from platforms such as Parrot Analytics, you can determine the value of "Luther" and how much to spend on content. The demand data for "Luther" over the last 30 days, indicates that it has been 6 times more in-demand than the average show in the United States. This provides insight into the economic valuation of the series, and can help you to make better-informed decisions on content acquisition, programming, and distribution.
2. Subscriber Retention/ Acquisition: If you want to retain or attract audiences, you can leverage demand data to help you achieve your goals. You can examine audience demand and use it to answer questions like "what genre/type of content is resonating with my current audience"? Insights into audience preferences that can be accessed through demand data could be critical when deciding which titles to buy if you want to keep your current audience happy. Alternatively, if you are trying to grow your audience, demand data can be used to help you identify shows that are in-demand and have broad reach. For instance, given "Luther's" outstanding global performance, growing the show to new territories could be a good option for audience acquisition.
3. Travelability and Franchisability: If you are interested in taking your content to international markets and monetizing them, demand data can provide insights into the show's potential for travelability and franchisability. For example, the demand for "Luther" in the United States was 95% of the demand in its country of origin, the United Kingdom, showing that it could be successful in other English-speaking markets. Furthermore, "Luther" has good potential for franchisability, which means that the intelligence garnered from demand data for the title could provide insight into not only which titles to develop into a franchise but also which spin-offs would be well-received by audiences.
4. Optimal Release Strategy and Pricing: Demand data for "Luther" can provide insights into when, where, and how to release an upcoming premiere to generate the greatest impact. For instance, given the series' spike in demand in late December 2023, its release could potentially be timed towards the end of the year to maximize the momentum and capitalize on the audience interest that has grown around it.
5. Content Discovery and Recommendations: Finally, leveraging demand data for the show can provide unads insight into show affinity clusters. This allows for proactive engagement with audiences that appreciate certain shows, recommending content for them accordingly and allowing for tailored content recommendations based on their viewing preferences. Given that "Luther" fans tend to enjoy shows such as "Game of Thrones" and "Star Trek: Picard," recommending these could lead to viewer acquisition or retention for the platform.
In conclusion, demand data for a title like "Luther" can provide executives with several insights that aid strategic decision-making. These insights range from content valuation, content discovery and recommendations, subscriber retention and acquisition, content monetization as well as insights into optimal release strategies, audience preference, spin-off potential, and more, leading to better decision-making by the executives.
