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Release Versionย Actively Maintainedย Snowplow Personal and Academic License

Snowplow Media Player Package

The package source code can be found in the snowplow/dbt-snowplow-media-player repo, and the docs for the model design here.

The package contains a fully incremental model that transforms raw media player event data into derived tables for easier querying. It can support media events tracked using the following tracking implementations on Web and mobile:

Version 1 and version 2 of the media event and context entity schemas

There are two versions of schemas for media events that our trackers may use to track media events. This has an effect on the information provided by the media package. In contrast with v1, the v2 schemas contain information about the media playback that is computed directly on the tracker and is more accurate (e.g., play time, buffering time). They also introduce new schemas for tracking ads during media playback.

  1. v1 media schemas (used by the HTML5 and YouTube plugin for JavaScript tracker):
  2. v2 media schemas (used by the media and Vimeo plugins for the JavaScript trackers and the mobile trackers):
note

Support for the version 2 schemas (as used by the media, Vimeo JS plugin or the mobile trackers) has been added in version 0.6 of the media player package. Older package versions only support version 1 schemas.

Overviewโ€‹

The package contains multiple staging models however the mart models are as follows:

  • Base: Performs the incremental logic, outputting the table snowplow_media_player_base_events_this_run which contains a de-duped data set of all events required for the current run of the model, and is the foundation for all other models generated.
  • Media base: Summarizes the key media player events and metrics of each media element on a media session level (or media_id and page/screen view if media session context is not tracked, which is essentially the same), identified by the play_id key, which is considered as a base aggregation level for media events.
    • The media base module outputs the snowplow_media_player_base table.
    • It also produces a _pivot_base table to calculate the percent_progress boundaries and weights that are used to calculate the total play_time and other related media fields.
  • Media plays: Removes impressions from the media base table while keeping the same structure as the snowplow_media_player_base table. Removing impressions means that only media sessions (identified by the play_id key) in which the user played the content are kept.
    • The media plays module outputs the snowplow_media_player_plays_by_pageview view.
  • Media stats: Aggregates the media base table to individual media_identifier level, calculating the main KPIs and overall video/audio metrics.
    • It uses the native dbt incremental materialization on a pageview basis after a set time window passed. This is to prevent complex and expensive queries due to metrics which need to take the whole page_view events into calculation. This way the metrics will only be calculated once per pageview / media, after no new events are expected.
    • The media stats module outputs the snowplow_media_player_media_stats table.
  • Media ad views: Summarizes metadata and KPIs for each ad view within a media playback. Each ad a user viewed will result in a single row with information about the progress reached, whether the ad was skipped or clicked.
    • The media ad views module outputs the snowplow_media_player_media_ad_views table.
  • Media ads: Aggregates all ad views to produce a summary of the KPIs for each ad played within each media content. Produces total counts of views, skips, clicks and progress reached. It also counts the metrics in terms of unique users (e.g., number of users who clicked the ad).
    • It outputs the snowplow_media_player_media_ads table.

Identifiersโ€‹

The package generates robust identifiers for use in the incremental logic and keys for the derived tables.

IdentifierDefinition
session_identifierThe session identifier as defined in your dbt project variables which is is used for the package's incremental sessionization logic. If not set, this defaults to the mediaSessionId from the media session entity if enabled, else to the page/screen view id. This ensures all media events for a play spanning multiple domain_sessionids are modelled. The more traditional session identifier domain_sessionid can be extracted from the domain_sessionid_array field.
user_identifierThe user identifier as defined in your dbt project variables. If not set, this defaults to be domain_userid for web or the userId from the client session entity for mobile.
media_identifierUsed to identify individual media elements/content. It is generated from the player_id, media_label, media_type and media_player_type fields.
play_idThe unique identifier for each individual play of media content. This is the mediaSessionId from the media session entity if enabled. Otherwise this uses the page/screen view identifier together with the media_identifer to generate a unique play id.
media_ad_idGenerated identifier that identifies an ad (identified using the ad_id) played with a specific media (identified using the media_identifier) and on a specific platform (based on the platform property).
media_ad_view_idThe unique identifier for each individual ad view. It is generated from the play_id, ad_break_id and media_ad_id fields.

Mixing web and mobile eventsโ€‹

The package makes no distinction between events tracked from the web and those tracked from a mobile application, so long as you are tracking media events and from allowed app_ids. The sessionId from the client_session context, and the id from the mobile_screen context, overwrite the domain_sessionid_array and page_view_id fields respectively in our intermediate and derived tables, for events where they are populated. If you are just using web events, the package will work out the box. If you are using a mix of web and mobile events, you will need to set the snowplow__enable_mobile_events package variable to true and events will be processed from both sources. If you are only tracking mobile events, you can set the snowplow__enable_web_events to false.

Custom modelsโ€‹

There are two custom models included in the package which could potentially be used in downstream models:

  1. the snowplow_media_player_session_stats table, which aggregates the snowplow_media_player_base table on a session level

  2. the snowplow_media_player_user_stats table, which aggregates the snowplow_media_player_session_stats to user level

By default these are disabled, but you can enable them in the project's profiles.yml, if needed.

dbt_project.yml
  models:
snowplow_media_player:
custom:
enabled: true

Just like in case of the web model, users are encouraged to use the Media Player model and its incremental logic to design their own custom models / modules. The snowplow_media_player_base_events_this_run table is designed with this in mind, where a couple of potentially useful fields are generated that the Media Player model does not use downstream but they nonetheless have the potential to be incorporated into users custom models. For more information on creating custom models, visit the guide here.

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