Streaming Insights: Analyzing Viewership Trends and User Engagement Across Genres and Regions
In today’s rapidly evolving entertainment landscape, understanding consumer behavior and preferences is crucial for stakeholders such as market researchers, content creators, and streaming platforms. Our motivating question is: “How do viewer engagement and preferences for drama television vary across different streaming platforms and regions?” This question is particularly relevant for stakeholders who need to make informed decisions about content acquisition, production strategies, marketing efforts, and platform optimization.
Stakeholders
For platform owners like Netflix, HBO, and Hulu, the answer to this question can guide strategic decisions about which shows and movies to add to their libraries in specific regions. For example, if a drama series is highly popular in the US, platform owners might consider adding it to their libraries in neighboring regions like Canada or Mexico, anticipating similar viewer preferences. This targeted content acquisition can help attract and retain viewers in those regions.
Content creators can use these insights to develop shows and movies that align with the preferences of audiences in different regions, increasing the likelihood of their success. By understanding which themes, genres, and storylines are most engaging to viewers in specific areas, content creators can tailor their productions to meet these preferences.
Marketers can design promotional campaigns that effectively reach target demographics and maximize engagement. For instance, if the analysis reveals a growing interest in a particular genre in a specific region, marketers can create targeted campaigns to promote relevant content, thereby increasing viewership and subscription rates.
Giulia’s domain knowledge highlights the importance of this analysis. Having family in both the Netherlands and Belgium, she has observed firsthand how Netflix’s content offerings can vary significantly from one country to another, even within a short drive. This variability can disrupt the viewing experience for users who travel between regions. Streaming platforms can ensure a more consistent and satisfying user experience by understanding regional preferences.
In summary, the actionable insight for stakeholders is to consider adding popular TV shows and movies to specific regions based on viewer preferences. This data-driven approach can enhance content offerings, improve user satisfaction, and optimize marketing strategies, ultimately leading to better engagement and retention across different regions.
Ideal Data
Ideal data for this research would include a range of metrics crucial for understanding consumer behavior and preferences within the drama genre across streaming platforms and regions. This includes viewer engagement metrics like viewership numbers, duration of viewing, and user engagement indicators such as likes and comments. Additionally, data on top-rated drama titles including critical ratings, user reviews, and demographic information such as age, gender, and location of the audience would be invaluable. Content attributes such as genre subcategories, themes, cast members, and production quality, along with platform-specific data like subscriber numbers, retention rates, and platform usage patterns, offer deeper insights into audience preferences and platform performance. Geographical data on regional viewership trends, cultural influences, and language preferences would provide context for understanding regional variations in content preferences. Time-series data would further illuminate long-term trends and seasonal variations in viewer behavior. By synthesizing and analyzing these diverse datasets, researchers and stakeholders can derive actionable insights for content creation, marketing strategies, and platform optimizations tailored to meet viewer demands and enhance audience engagement within the drama genre across the global streaming landscape.
Methods
Data Collected
Using the Watchmode API, we gathered data on popular drama titles across streaming platforms like Netflix, HBO, and Hulu in regions such as the US, Great Britain, and Australia. By utilizing the /v1/list-titles/ endpoint and specifying parameters like genre (Drama), region (US, GB, AU), streaming platforms (Netflix, HBO, Hulu), and sorting by popularity, we retrieved a list of the top 5 drama titles from each region and platform combination. Subsequently, we used the /title/details endpoint to obtain information such as critic scores, user ratings, relevance percentiles, and streaming platform details for these titles. This data collection process allowed us to gather comprehensive insights into viewer preferences, critic reception, and platform performance within the drama genre across different regions and streaming platforms. Due to the manner of the API, we had to use two different endpoints as stated above. In the first endpoint (v1/list-titles), we can specify what region, drama, and genre we want the titles returned to be. we could also sort my most popular titles. With this in mind, we specified the genre to be drama, and the region to be either, the US(United States), AU(Australia), or GB(Great Britain). There were numerous regions to choose from so we decided that these three regions would be good enough. Another reason why we had to limit ourselves to three regions would be that we had a limit on the amount of API calls we could make. The same reason was also why we had to choose three streaming platforms to use to conduct our analysis. The three streaming platforms we chose were Netflix, Hulu, and HBO Max as almost everyone either has one or the other or all. Most people either have a Netflix or an HBO Max account, or both and they are also the most popular platforms generally used. This will be discussed further in the limitations section. Below is a screenshot of what the API call looked like as it’s better to see what use words:
This is the result we got when we specified the region to be the US and the streaming platform to be Hulu:
After this was done, we took each title id and looked it up in the second API endpoint(i.e./title/details) which is the one that will return the critic score, relevance percentile, and user rating of each title. Now these are the metrics we need for our analysis.
This is what our API call was like:
We then repeated this process three times for the two other regions and streaming platforms. For the Australian region, we chose to use Netflix as very few streaming platforms available in the API to use for Australia.
For Great Britain, we decided to use HBO Max as its streaming platform as HBO is very famous in Great Britain and widely used.
Our project utilized several of the core concepts taught in the course. These methods included:
API Usage
Our project was integrated with the Watchmode API to fetch details about movie or TV show titles, such as user ratings, relevance percentiles, and critic scores. It uses an API key for authentication and makes asynchronous requests to the API endpoints using async/await syntax allowing for efficient and responsive data retrieval. Our rationale was to show effective usage of API concepts taught in the course.
Data Retrieval and Processing
We used data-searching methods to find a reputable and effective source in Watchmode API. After receiving the data from the API, we processed only relevant information to our project. We also added error handling to manage potential errors during API calls and allow for efficient code even during failures.
Data Visualization
The project utilized HTML tables to visually present the retrieved data in an organized and structured format. Each table displayed details such as movie or TV show titles, user ratings, relevance percentiles, and critic scores. By presenting this information in a tabular format, users could easily compare and analyze viewership trends across different genres, regions, and streaming platforms. While the visualization approach was relatively simple, it effectively conveyed the key information extracted from the Watchmode API in a user-friendly manner.
Data Analysis
To answer our motivating question, we conducted a comprehensive analysis of viewer engagement and preferences across different streaming platforms and regions, focusing on how these insights can inform strategic decisions for stakeholders. Our data retrieval process involved using the Watchmode API to gather detailed information on popular drama titles. We first utilized the /v1/list-titles/ endpoint to obtain a list of top-rated drama titles from Netflix, HBO, and Hulu in the US, Great Britain, and Australia. This endpoint allowed us to specify parameters such as genre, region, and streaming platform, and sort the results by popularity. Once we had the title IDs, we used the /title/details endpoint to fetch additional details for each title, including critic scores, user ratings, relevance percentiles, and streaming platform information. This two-step process ensured that we collected comprehensive data on each title’s performance and viewer reception.
For the analysis, we focused on key metrics such as user ratings, critic scores, and relevance percentiles to identify trends and correlations. By comparing these metrics across different regions and platforms, we uncovered patterns in viewer preferences and engagement. This analysis is particularly useful for stakeholders, such as content creators, platform owners, and marketers, as it provides actionable insights into which shows or movies are popular in specific regions like the US. Understanding these trends allows stakeholders to make informed decisions about content acquisition and distribution. For instance, if a particular drama series is highly popular in the US, stakeholders might consider adding it to neighboring regions like Canada or Mexico, anticipating similar viewer preferences and thereby maximizing engagement and retention.
Analyzing the top 5 most popular drama titles on Hulu in the United States provides valuable insights into viewer preferences and critical reception. These titles encompass a range of user ratings, relevance percentiles, and critic scores. “Shōgun” emerges as a standout performer with an impressive user rating of 8.6, a relevance percentile close to 100%, and a strong critic score of 92, indicating widespread popularity and critical acclaim. Similarly, “The Handmaid’s Tale” maintains a solid presence with an 8.2 user rating, a high relevance percentile, and a respectable critic score of 82. On the other hand, “The Kardashians” garners lower scores both in user ratings (4.8) and critic rating (33), reflecting a potentially polarizing reception or a niche audience appeal. “The Orville” and “Runaways” fall in between, with decent user ratings but slightly lower critic scores compared to the top contenders. Overall, the data underscores the importance of considering both user feedback and critical assessments to gauge the success and reception of drama titles on Hulu.
“Stranger Things” and “Lucifer” lead the pack with strong user ratings of 8.6 and 8, respectively, along with high relevance percentiles and decent critic scores. These titles indicate a broad appeal and engagement among Australian viewers. “You” and “Bridgerton” share similar user ratings of 7.6, yet “Bridgerton” stands out with an exceptionally high relevance percentile of 99.992, suggesting a significant cultural impact and viewer interest. “GLOW” maintains a solid position with a 7.8 user rating and a respectable critic score of 88, showcasing consistent viewer satisfaction and critical reception. These top drama titles on Netflix in Australia demonstrate a blend of audience appeal, relevance, and critical acclaim, reflecting the diverse preferences and engagement levels within the Australian streaming market.
“Game of Thrones” and “The Wire” stand out with exceptionally high user ratings of 9.7 and 9.5, respectively, indicating a strong fan base and widespread acclaim. These two titles also boast high relevance percentiles, further emphasizing their impact and relevance among British viewers. “The Leftovers” and “Westworld” maintain solid user ratings of 8.2 and 8.3, respectively, with respectable relevance percentiles and critic scores. “True Blood” rounds out the list with a decent user rating of 7.7 and a moderate critic score of 69. These top drama titles on HBO in Great Britain reflect a diverse range of viewer preferences, with some shows achieving exceptional ratings and others offering consistent viewer satisfaction and critical acclaim.
These insights can guide marketing strategies and promotional efforts, ensuring that campaigns are tailored to regional preferences. By leveraging data on popular genres and titles, streaming platforms can deliver personalized recommendations to users, increasing user satisfaction and retention. Overall, our analysis equips stakeholders with the knowledge to strategically expand their content offerings and optimize their platform’s performance across different regions, fostering a more targeted and effective approach to content distribution and viewer engagement.
Answers For Stakeholders
The analysis provides stakeholders in the streaming industry with valuable insights into viewership trends across different regions and platforms, enabling informed decision-making in several key areas:
Content Acquisition Strategy
By identifying popular genres and titles in specific regions and platforms, stakeholders can optimize their content acquisition strategy. For example, if the analysis reveals a high demand for action movies in the US on Netflix, stakeholders can prioritize licensing agreements for action-oriented content to meet viewer preferences.
Licensing and Distribution Decisions
Understanding viewer preferences can help stakeholders make data-driven decisions about licensing and distributing content. By aligning content offerings with audience preferences, stakeholders can maximize engagement and retention. For instance, if the analysis indicates a growing interest in foreign dramas in Australia on Netflix, stakeholders may consider acquiring more international content for that market.
Content Curation and Recommendation Algorithms
Insights from the analysis can enhance content curation and recommendation algorithms. By leveraging data on popular genres and titles, streaming platforms can deliver personalized recommendations to users, increasing user satisfaction and retention. For example, if the analysis highlights a trend of documentary series popularity in the UK on Hulu, the platform can prioritize recommending similar content to users in that region.
Marketing and Promotion Strategies
Stakeholders can tailor marketing and promotion strategies based on regional and platform-specific viewer preferences. By targeting promotions towards trending genres and titles, stakeholders can effectively attract and retain subscribers. For instance, if the analysis identifies a surge in sci-fi movie interest in Germany on HBO, stakeholders can launch targeted marketing campaigns to promote relevant content to German audiences.
Investment in Original Content
Insights into viewer preferences can guide investment decisions in original content production. By identifying underserved genres and emerging trends, stakeholders can allocate resources strategically to develop original content that resonates with target audiences. For example, if the analysis reveals a growing demand for true crime documentaries in Canada on Hulu, stakeholders may consider investing in original productions within that genre to capture audience interest.
Expansion into New Markets
The analysis can inform expansion strategies into new markets by providing insights into local viewer preferences and competitive landscapes. By understanding regional preferences and content gaps, stakeholders can tailor their content offerings and marketing strategies to effectively penetrate new markets. For instance, if the analysis highlights a lack of sports documentaries in Spain on Netflix, stakeholders may see an opportunity to introduce such content to tap into a niche market segment.
While the analysis provides valuable insights into viewership trends and user engagement across genres and regions, there are still several limitations that may impact the robustness and generalizability of the findings.
Data Limitations
The analysis relies on data collected from the Watch mode API, which may have limitations in terms of coverage, accuracy, and completeness. The restricted access to the API and the need to create multiple accounts to access more data may have introduced biases or limitations in the dataset. Additionally, the API’s segmented structure may have hindered the gathering of a comprehensive picture of viewership trends and user engagement.
Sampling Bias
The selection of titles for analysis, as well as the choice of genres and regions, may introduce sampling bias. The analysis may not capture the full diversity of content available on streaming platforms, leading to potentially skewed conclusions about viewer preferences and engagement.
Ethical Considerations
There are ethical considerations related to user privacy and data usage, especially when analyzing user engagement metrics and preferences. Ensuring the anonymization of user data and obtaining appropriate consent for data collection is essential to maintain ethical standards in research and analysis.
Reliability of Ratings
User ratings collected from the API may vary in reliability and accuracy. Factors such as fake ratings, biased reviews, and differences in rating scales across regions can affect the validity of the rating data used in the analysis.
Generalizability
The insights derived from the analysis may not be fully generalizable to all streaming platforms, as the findings are based on data from a single API. Different platforms may have unique user demographics, content libraries, and engagement patterns that could influence viewership trends and user preferences differently.
Conclusion
In conclusion, our project provides valuable insights into viewership trends and user engagement across different genres and regions in the streaming industry. By leveraging data from the Watch mode API, we were able to analyze popular drama titles on streaming platforms like Netflix, HBO, and Hulu in regions such as the US, Great Britain, and Australia. Our analysis revealed actionable insights for stakeholders in content acquisition, licensing decisions, content curation, marketing strategies, investment in original content, and expansion into new markets. However, it’s important to acknowledge the limitations of our project, including data restrictions, sampling bias, reliability of ratings, etc. Moving forward, addressing these limitations and exploring additional data sources will be crucial for enhancing the robustness and reliability of future analyses in the streaming industry. Overall, our project underscores the importance of data-driven decision-making in optimizing content offerings, improving user satisfaction, and driving growth in the increasingly competitive streaming landscape.
Appendix
Link to GitHub: https://github.com/elmantador45/414---Final-Project.git
