About the Model: How SV(M) measures streaming data

About the Model: How SV(M) measures streaming data

Luminate Film & TV Streaming Viewership (M) models streaming consumption data. 


Our streaming viewership model breaks new ground. In a fragmented entertainment landscape with no comprehensive source for first-party OTT viewing data, we’ve applied our expertise in data science to the challenge of streaming measurement.


In brief: SV(M) collects a proprietary, multi-source combination of data. Then, we apply a linear optimization model to calculate streaming viewership. We leverage Luminate Film & TV’s library of entertainment metadata to enhance our modeling and build a database of streaming titles. Our methodology allows us to lead the industry in reporting streaming ratings and publishing film and TV charts


Read on to learn more about our data, our model and the methodology that brings it together.




Back to How SV(M) Works 



What we track: Streaming viewership

SV(M) measures U.S.viewership for streaming TV shows and movies. Our metric is minutes watched per title: the total amount of time that viewers in our dataset spent streaming a movie, TV season or episode on an OTT streamer.


Minutes/Hours watched

Our standard unit of viewing time is minutes watched. SV(M) permits users to toggle between Minutes and Hours as the display metric. (Hours watched = minutes watched divided by 60).


Total views

In addition to time watched, SV(M) estimates the number of views for some titles* by dividing minutes watched by the runtime.


*While this formula is relatively simple for movies, it’s still an average or estimate given that not all views cover the entire runtime. TV episode and season view counts are not currently supported due to the challenge in accounting for varying episode lengths.



Chart rankings

SV(M) publishes weekly charts that rank the Top 50 Movies and TV Shows based on minutes watched. Our charts help set a benchmark for streaming platform “ratings” as the industry continues to evolve. 


Read more: Charts: Streaming film and TV rankings




Title metadata 

In addition to viewership data, we track metadata—i.e. director/showrunner, production companies, release date, runtime and other identifying information—for the thousands of titles on the SV(M) platform.


We draw metadata from Luminate Film & TV’s best-in-class industry reference database, which combines proprietary internal data and primary research with licensed data, open source datasets and data sharing partnerships with studios and distributors.


Read more: Title Dashboards: Film and TV data at a glance







How we track it: Streaming data collection 

SV(M) incorporates multiple data sources into our consumption modeling: ACR panel reporting, proprietary web traffic and search data, internal Luminate metadata, and information sourced from vendors and partners across the entertainment industry. 



Automated Content Recognition (ACR) 

Our most important source of consumption data is Automatic Content Recognition (ACR) data collected from a normalized U.S. national panel of 2.5 million smart TVs.


ACR technology can identify the content being played on a smart TV or connected device (Apple TV, Roku, etc.) by analyzing the audio and video on screen. It works automatically to collect viewing information while keeping individual viewers anonymous. 



Streaming platforms

ACR technology is platform-agnostic. The ACR panel data we receive includes viewing activity on all major U.S. on-demand streaming providers. SV(M) viewership data covers the 10 largest streamers by audience share, plus dozens of other OTT and FAST channels.


SV(M) compiles aggregate viewership data and metadata for top streaming providers. 


Read more: Streamers: Provider data at a glance







How we measure it: The SV(M) Consumption Model

SV(M) automatically processes incoming data and matches it to titles in our database. Then, we implement a linear optimization model to calculate consumption. 



ID Unification

SV(M) automatically identifies content and matches entities in our dataset with Luminate Film & TV metadata. ID unification attaches metadata to each title in the SV(M) database and groups entities together (like TV seasons and episodes). This process builds our database and helps ensure that reported viewership data is correctly attributed to each movie, TV show and episode.



Consumption modeling 

After ingesting and processing our dataset, we use mathematical modeling to predict and optimize viewership figures. The SV(M) model extrapolates total viewership from ACR panel data while correcting for anomalies, biases and gaps in reporting. The model is designed to normalize and address disparities in reported viewership. In some cases, it applies different weights to different sources.


We validate modeled figures against carefully selected reference data (see below). 



Alternative signals and weighting

The SV(M) model augments and balances ACR panel data with alternative signals related to audience engagement—many of which are proprietary to Luminate.


We track page view and search behavior from 378 million monthly active users across the Penske Media Corporation (PMC) portfolio, which includes Variety, The Hollywood Reporter, Deadline, IndieWire, Rolling Stone, Billboard, the Golden Globes, SXSW and dozens of other brands. We also collect web traffic, search, and reported viewership from publicly available sources. 


We compare the above with actual reported consumption and, if needed, rebalance our model to reduce disparities. We re-train and adjust the model about once a month. 







More to know




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