- For an introduction to Singular data destinations, 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 has replaced the older skan_estimated_revenue metric. Similarly, skan_roi has replaced skan_estimated_roi.
skan_revenue now contains all revenue gained, regardless of the source (IAP or ad mon) or conversion model.
When you use Singular data destinations, Singular standardizes data from your source and fits it to the data schema so you can easily query 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.
Note: For more information about each field, see the Singular Metrics and Dimensions Glossary.
A data schema can only contain one type of data - network, attribution, ad monetization, SKAN, or web data. Use the list below to help you choose the data schema that best fits your needs.
Network Data Schemas
The network data schemas include aggregate data that is pulled from the different adnetworks (for example - Facebook, Unity, etc)
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_installsSupports 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_installsHelps 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_installsSupports 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_installsAttribution Data Schemas
This schema includes aggregated data that is coming from the Singular SDK (or S2S events in cases where S2S is used instead of SDK).
This type of data typically includes installs and additional post install events such as revenue.
Dimensions:
data_connector_source_name
data_connector_id
data_connector_username
data_connector_timestamp_utc
date
app
source
os
platform
country_field
tracker_account_id
tracker_campaign_id
tracker_campaign_name //from the attribution provider
tracker_name
tracker_sub_campaign_id
tracker_sub_campaign_name
unified_campaign_name //combined from the network data (prioritized) and attribution provider. This field should be used to combine data with the data pulled from the networks
unified_campaign_id
Metrics:
revenue
tracker_impressions
tracker_clicks
tracker_installs
Cohorts: 1d, 7d, actual. Additional cohort periods can be added manually when setting up the data destination
Ad Monetization Data Schemas
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 Data Schemas
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?).
Dimensions:
app
country_field
data_connector_id
data_connector_source_name
data_connector_timestamp_utc
data_connector_username
date
etl_query_timestamp_utc
skan_app_id
skan_campaign_id
skan_conversion_value
skan_conversion_value_description
skan_digit_3
skan_digit_4
skan_network_id
skan_publisher_id
skan_redownloads
skan_source_domain
skan_unified_conversion_value
skan_validated
skan_version
skan_view_through
source
tracker_campaign_id
tracker_campaign_name
Metrics:
skan_conversion_values_count
skan_conversion_values_ratio
skan_installs
skan_p2_postbacks
skan_p3_postbacks
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:
app
country_field
data_connector_id
data_connector_source_name
data_connector_timestamp_utc
data_connector_username
date
etl_query_timestamp_utc
skan_redownloads
skan_unified_publisher_id
skan_validated
skan_view_through
source
sub_campaign_id
sub_campaign_name
unified_campaign_id
unified_campaign_name
Metrics:
adn_cost
custom_clicks
custom_impressions
skan_admon_revenue
skan_combined_revenue
skan_conversion_values_count
skan_iap_revenue
skan_installs
skan_p2_postbacks
skan_p3_postbacks
skan_revenue
tracker_installs
These two schemas provide SKAN Advanced Analytics metrics that are unique to Singular, including Modeled SKAN Revenue and 7d SKAN Revenue. Learn more in the SKAN Advanced Analytics FAQ.
Both schemas include the same fields, but in one the date given is the date in which the postback was received while in the other the date is the estimated install date as calculated by Singular (see How does Singular calculate the install date/attribution date?).
Dimensions:
app
data_connector_id
data_connector_source_name
data_connector_timestamp_utc
data_connector_username
date
etl_query_timestamp_utc
skan_redownloads
skan_validated
skan_view_through
source
sub_campaign_id
sub_campaign_name
unified_campaign_id
unified_campaign_name
Metrics:
adn_cost
custom_clicks
custom_impressions
modeled_skan_revenue
modeled_skan_revenue_7d
skan_conversion_values_count
skan_installs
skan_p2_postbacks
skan_p3_postbacks
skan_revenue
tracker_installs
Web Data Schemas
These schemas provide data about web campaigns.
Dimensions:
adn_account_id
adn_account_name
adn_campaign_id
adn_campaign_name
adn_sub_campaign_id
adn_sub_campaign_name
app
country_field
data_connector_id
data_connector_source_name
data_connector_timestamp_utc
data_connector_username
date
etl_query_timestamp_utc
os
platform
source
utm_campaign
utm_content
utm_medium
utm_source
utm_term
Metrics:
adn_clicks
adn_cost
adn_impressions
adn_installs
new_visitors
re_engaged_visitors
revenue_actual
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?
When you select and setup your data schema, you will be able to choose your custom dimensions and custom events to add to the schema.
Singular supports further customization 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.
