Data Destinations: Aggregated Data Schemas

For an introduction to Singular data destinations and how they work, see Singular Data Destinations (ETL) FAQ.

For the data schemas for user-level data, see Data Destinations: User-Level Data Schemas.

Update [April 2022]: In the SKAdNetwork data schemas, the skan_revenue metric is replacing the older skan_estimated_revenue metric. Similarly, skan_roi replaces skan_estimated_roi.

skan_revenue now contains all revenue gained, regardless of the source (IAP or ad mon) and regardless of what conversion model was used.

 

When you use Singular data destinations, Singular standardizes data from different sources into the same data schema so you can easily query on it in your database.

Singular offers a choice of data schemas. Each schema defines a different set of dimensions and metrics that the Singular data destination will load into your database.

Use the list below to help you choose the data schema that best fits your needs.

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Data Schema Options

Note: For more information about each field, see the Singular Metrics and Dimensions Glossary.

 

Campaign Data Schema

Useful for campaign-level and network-level optimization. Keeps your data footprint small and manageable.

Dimensions:
data_connector_source_name
data_connector_id
data_connector_username
data_connector_timestamp_utc
date app source os platform country_field adn_sub_adnetwork_ name adn_account_id adn_account_name adn_campaign_id adn_campaign_name adn_sub_campaign_id adn_sub_campaign_name adn_campaign_url Metrics: adn_cost adn_original_cost adn_original_currency adn_impressions adn_clicks adn_installs
Campaign and Keyword Data Schema

Supports keyword-level optimization for search campaigns.

Dimensions:
data_connector_source_name
data_connector_id
data_connector_username
data_connector_timestamp_utc
date app source os platform country_field adn_sub_adnetwork_ name adn_account_id adn_account_name adn_campaign_id adn_campaign_name adn_sub_campaign_id adn_sub_campaign_name adn_campaign_url keyword_id keyword Metrics: adn_cost adn_original_cost adn_original_currency adn_impressions adn_clicks adn_installs
Campaign, Keyword, and Publisher Data Schema

Helps you optimize publisher-based bids, whitelists, and blacklists. May create large volumes of data!

Dimensions:
data_connector_source_name
data_connector_id
data_connector_username
data_connector_timestamp_utc
date app source os platform country_field adn_sub_adnetwork_ name adn_account_id adn_account_name adn_campaign_id adn_campaign_name adn_sub_campaign_id adn_sub_campaign_name adn_campaign_url keyword_id keyword publisher_id publisher_site_id publisher_site_name Metrics: adn_cost adn_original_cost adn_original_currency adn_impressions adn_clicks adn_installs
Campaign and Creative Data Schema

Supports creative-based optimization.

Dimensions:
data_connector_source_name
data_connector_id
data_connector_username
data_connector_timestamp_utc
date app source os platform country_field adn_sub_adnetwork_ name adn_account_id adn_account_name adn_campaign_id adn_campaign_name adn_sub_campaign_id adn_sub_campaign_name adn_campaign_url creative_type adn_creative_id adn_creative_name creative_url creative_image creative_text creative_width creative_height creative_is_video asset_id asset_name Metrics: adn_cost adn_original_cost adn_original_currency adn_impressions adn_clicks adn_installs
Ad Monetization Data Schema

Helps you track your ad revenue.

Dimensions:
data_connector_source_name
data_connector_id
data_connector_username
data_connector_timestamp_utc
date
etl_query_timestamp_utc
app
source
os
platform
ad_country
ad_type_id
ad_type_name
ad_placement_id
ad_placement_name
instance_id
instance_name
original_revenue_currency

Metrics:
ad_requests
ad_impressions
ad_clicks
ad_revenue
original_ad_revenue
SKAdNetwork Raw Data Schemas

skan_raw_schemas.png

These schemas provide raw SKAdNetwork data as received in SKAdNetwork postbacks.

Both schemas include the same fields. The difference is that in one, the date given is the date in which the postback was received, while in the other, it's the estimated install date as calculated by Singular (see How does Singular calculate the install date/attribution date?).

Note: Due to Facebook's limitations, this schema does not include Facebook data.

Dimensions:
data_connector_id
data_connector_timestamp_utc
date source app country_field skan_app_id skan_network_id skan_campaign_id skan_publisher_id skan_conversion_value skan_conversion_value_description skan_redownloads skan_validate tracker_campaign_id tracker_campaign_name Metrics: skan_installs
SKAdNetwork Data Schemas

skan_data_schemas.png

These schemas provide data about SKAdNetwork campaigns, based on decoded SKAdNetwork postbacks, along with network data about the same campaigns (if available).

Both schemas include the same fields. The difference is that in one, the date given is the date in which the postback was received, while in the other, it's the estimated install date as calculated by Singular (see How does Singular calculate the install date/attribution date?).

Dimensions:
source
app
date country_field unified_campaign_id unified_campaign_name skan_validated Metrics: adn_cost custom_installs custom_impressions custom_clicks skan_redownloads skan_installs
skan_revenue
skan_roi
Web Data Schema

These schemas provide data about web campaigns.

Dimensions:
source
app
date
country_field
adn_campaign_id
adn_campaign_name
adn_sub_campaign_name
adn_sub_campaign_id
account_id
account_name
platform
os
utm_campaign
utm_content
utm_medium
utm_source
utm_term

Metrics:
adn_cost
adn_impressions
adn_clicks
adn_installs
new_visitors
re_engaged_visitors
total_web_conversions

FAQ

Can I change the data schema in the future?

Once you create and save the data destination, you cannot switch to another data schema. This is because changing the table structure in a live database with existing data comes with a number of dangers and complications.

If you need a data schema change, simply create a new destination. You can either delete the old table before creating the new destination or configure the new destination to load data to a new table with a different name. This process will ensure that your data stays safe and existing queries and work-loads continue working.

Can I create a custom data schema?

Singular supports custom schemas for premium customers. Any field supported in Singular's API is also supported in Singular data destinations (see Metrics and Dimensions for a full list). If you need a specific combination of fields that is not found in the existing schemas, discuss it with your Singular Customer Success Manager or contact Singular's support team.