Blog

How to Aggregate and Normalize Data from OTT Platforms

02.03.2023 | Ray Gilmartin
 

Content sellers licensing television and film assets to Over-The-Top (OTT) video streaming providers receive periodic reports from their distribution partners with the latest data on content performance, earnings, and royalty payments.

Content sellers can analyze this data to determine which media assets are generating the most revenue, which types of content are resonating with audiences, and how to optimize content production, marketing, and distribution investments.

But there’s a unique challenge for content sellers licensing video assets to more than one OTT platform: data normalization. Because each OTT provider offers slightly different data, uses a different syntax, and publishes reports in a different format, data from multiple OTT platforms must be aggregated and normalized. At that point, content sellers have a complete view of earnings, net royalty payments, and content performance across channels.

Historically, content sellers have normalized OTT platform data with labor-intensive manual processes, often using painstakingly managed excel spreadsheets. As the distribution landscape grows in complexity though, media finance teams need a more efficient way to aggregate and normalize data in order to manage their OTT data.

Here we explore the contents and value of OTT platform data, data normalization challenges and benefits for content sellers, and the best way for content sellers to aggregate and normalize data from OTT platforms.

 

What data comes from OTT platforms?

The reports that content sellers receive from OTT platforms contain several kinds of data, including OTT content metadata, content performance data, earnings data, and payments data.

 

OTT content metadata

OTT content metadata provides descriptive information about a piece of video content. It includes information like the title of a video asset, its genre, cast and crew members, maturity rating, release date, and running time. Well-organized metadata allows content sellers to run queries and answer questions like:

  • Which genres of content drive the most streaming minutes?
  • Which OTT platforms are best for retro or nostalgic content?
  • How does the length of a video asset impact viewer retention?

 

Content performance data

Content performance data conveys information about how much or how frequently a content seller’s video assets were streamed on an OTT platform in a given time period. OTT streaming companies may provide information on the number of unique streams, total minutes streamed for each title, and viewer retention (how many users who started streaming watched the full video).

 

Earnings data

OTT streaming companies report to content sellers on the earnings they generate through the OTT platform. For SVOD distribution, earnings are typically calculated by determining Total Minutes Streamed and multiplying by an agreed royalty rate. For ad-supported and transactional distribution, earnings are usually based on either a share of DTR/EST revenue from TVOD platform monetization or advertising revenue from AVOD/FAST platform monetization.

 

Payments data

OTT streaming companies make payments to content sellers 30-90 days after the end of a month in which revenue was generated. Payments data from OTT providers indicates what payments have been issued and may include other details like tax withholdings, adjustments, net earnings, and foreign exchange rates (when the distributor and content seller operate in different currencies).

 

What is data normalization?

Data normalization is the process of organizing data (e.g. by applying standardized format, labeling, and syntax) so that it appears similar across all records and fields.

The goal of data normalization for content sellers is to impose a consistent, standardized format and syntax for distributor data. This allows distributor reports to be aggregated into one table that acts as a single source of truth for analyzing content performance and earnings data by title, by genre, or across distribution channels.

 

Why is messy OTT data a problem?

Distributor reports like those pictured below are generated by OTT companies to provide content sellers with information about earnings from TVOD sales.

TVOD Report Examples
Sample TVOD distributor reports

 

Each row in these reports relates to a single TVOD transaction that generated revenue for the content seller, while each column provides a unique element of information about the transaction – from basic details like the distributor studio and name of the video asset, to specifics like the activity date and purchase price.

These two reports come from different OTT providers, and though they convey much of the same information, you’ll notice that the ordering of columns, labeling syntax, and data formats are quite different.

For example, both reports indicate the purchase price of each transaction, but the relevant column (Column L) in #1 TVOD Report is labeled “Retail Price” while the relevant column (Column M) in #2 TVOD Report is labeled “MSRP”. Similarly, the column indicating the date of the transaction is labeled “Activity Date” (Column I) in #1 TVOD Report and “EVENT_DT” (Column A) in #2 TVOD Report.

These differences may appear small, but they create a significant challenge for content sellers when it comes to aggregating this data to enable different types of analytics.

A data-driven content seller would like to aggregate all of its distributor reports into a single table containing all content performance data for all titles across all platforms. However, the existing variation in formatting, syntax, and labels between the reports would result in a disorganized mess of data with inconsistent syntax, conflicting data formats, and numerous duplicate columns. This table would be impossible to efficiently query and essentially useless for analytics applications.

Because messy OTT data can’t be efficiently queried and analyzed, content sellers must standardize and organize the data using data normalization techniques to support content performance and financial analytics applications.

 

How do content sellers aggregate and normalize OTT data reports?

 

Using manual data entry

Some content sellers are still aggregating and normalizing data from distributor partners using manual data entry techniques.

These content sellers employ data entry teams who take the distribution reports they receive each month, standardize all of the data formatting/syntax by hand, and manually aggregate the data so it can be analyzed to support business decision-making.

Normalizing data manually can work for content sellers with just one or two distributor partners – but as the number of channels and reports increases, manual data normalization quickly becomes prohibitively time-consuming and error-prone.

 

Using spreadsheets

Another common way of normalizing data from distributor reports is to create a master spreadsheet (typically using Microsoft Excel or Google Sheets) with numerous, complex formulas to transform distributor data into a consistent format, standardize the report syntax, map the data into the correct columns, and ultimately consolidate the data into the master spreadsheet.

This process does provide some time-saving automation, but it’s still error-prone, fragile, and hugely labor-intensive for content sellers. It takes plenty of up-front effort to integrate even one new report into the master spreadsheet, and any changes to the format or syntax of a distributor report can break your excel formulas and degrade the quality of the data.

 

Using specialized data intelligence software

Data-driven content sellers in 2023 are using data intelligence software tools like Revedia Digital to automate the process of aggregating and normalizing data from OTT distributors.

With Revedia Digital, content sellers can add a Distributor Configuration for each of their OTT distribution partners. Each Distributor Configuration indicates the total number of columns in OTT data reports from that distributor. Content sellers can map the specific columns in each distributor report to a desired column in Revedia Digital’s internal content performance database.

Revedia Distributor Configuration
A sample distributor configuration within Revedia Digital featuring a list of data columns.

 

Once the column mapping is complete, Revedia Digital can normalize data from that distributor and integrate it into a centralized database whenever a new report is uploaded into the system. Through its broad set of API and custom integrations, Revedia Digital seamlessly automates this exchange of performance data with OTT distribution platforms.

As data from distributor reports is ingested, aggregated, and normalized, Revedia Digital becomes a content seller’s single source of truth for content performance, earnings, and payment data from OTT data platforms. Revedia Digital’s analytics engine automatically generates visualizations of content performance and earnings that reflect the status of the content seller’s business in real-time.

Revedia Digital Dashboard
After ingesting and normalizing OTT distributor data, Revedia Digital’s built-in analytics engine reveals valuable insights into content performance, earnings, and cash flow.

 

What are the benefits of normalizing OTT data?

If content sellers want a better understanding of how much revenue they’re generating across platforms, which OTT distributors and assets are driving the most revenue, or which genres are the most popular across OTT platforms, they need to import and aggregate OTT distributor data from multiple sources into a single source of truth.

When that happens, data normalization ensures that the data is properly organized and ready to be used for analytics.

Increasingly, content sellers are utilizing modern data intelligence software solutions like Revedia Digital to automate the data normalization process. This saves time, reduces wasted effort, ensures accuracy, and delivers faster insights that help optimize content production, OTT licensing negotiations, and distribution strategy decisions.

 

Normalize your OTT data with Revedia Digital

Revedia Digital gives content sellers the ability to automate data normalization from multiple OTT data platforms and accelerate insights into content performance, earnings, and payments.

Additionally, our platform is designed to leverage continuously developing artificial intelligence capabilities to detect hidden anomalies and forecast future OTT revenue and ROI.

With Revedia Digital, content sellers can:

  • Easily ingest and normalize data from multiple sources,
  • Establish a single source of truth for content performance and financial data,
  • Reveal the best ways to mitigate losses and maximize content revenue,
  • Inform licensing negotiations to make stronger content and distribution strategy decisions,
  • And more…

Discover all of Revedia Digital’s capabilities in this on-demand webinar.

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