Usage Data Management Process Use Case: Media Streaming Platform
This article aims to simplify the usage data management processes with a specific focus on a movie streaming platform use case.
Edwin Ryan Poquiz
Reading time: 2 minutes
After explaining the functional features of our data management platform in simple terms in a previous article, this article continues the effort to simplify usage data management processes. This time, it focuses on a specific use case.
Here’s the use case in a nutshell:
- CULTflicks is a video streaming service that specializes in showcasing “bad” movies.
- It has encountered difficulties in a crowded market and losing customers due to economic challenges.
- To address this, the company has introduced a pay-per-view time tier to entice and keep customers.
Data Collection, Enrichment, and Aggregation
1. Data Collection
The platform collects basic information about viewers on CULTflicks.
2. Data Enrichment
Viewer details are added to the data, along with information about the movies they watch.
3. Data Processing
The platform checks viewer and movie rights and processes the data.
4. Calculating Viewer Engagement
The platform calculates how much of a movie a viewer has watched.
5. Data Aggregation
The data is cleaned up, verified, and combined by the platform.
6. Viewer Classification
Viewers are grouped as light, standard, or heavy users based on their viewing habits.
Usage Data Management Functions Used
Script Function: Customizes data processing using JavaScript.
Map Function: Allows for choosing and creation of data fields, and applying of formulas.
Data Aggregator Function: Marges records from different sources.
Field Organizer Function: Allows the renaming, formating, and matching of data fields for output systems.
No Operation Function: Removes any unwanted records and doesn’t process them any further.
Route Function: Sorts movies based on their viewing completion status.
Billing System and User Communications Flow
1. Based on how much a viewer watches films, the Script function sorts them into light, standard, or heavy viewers, and spots those who might stop using the service.
2. The fields are properly labeled and prepared for the billing system to generate invoices.
3. A “golden revenue record,” aka THE one record that has gone through all the checkpoints and transformations and represents reality is created and sent to the billing system.
4. Each viewer gets an invoice and a message based on their viewing level. For example, a light user who might stop using the service would receive a friendly message with a special offer, a standard user would receive a simple “Thank you” message, while a heavy user might receive more movie recommendations.
Revenue Sharing Flow:
1. Viewing events are sorted based on whether they were completed or not and grouped by movie title to calculate payments for content providers.
2. The data is prepared and formated for an ERP system that determines how much money should be paid for settlements by mapping the relevant field.
Analytics and Product Curation Flow
1. Combined data is created to find out which movie titles are popular and which ones aren’t for analysis and content selection purposes.
2. Movies that aren’t watched completely are counted and sent to external analytics.
Bonus Benefits
By using the same data, CULTflicks is able to customize billing and email communication to make every interaction unique and efficient.
The same data also helps them pick the most relevant movies in their catalog, making sure that their viewers are getting exactly what they want, and it also helps them choose their content providers and the content they… uhh… provide.
Read the full use case
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