LinkedIn Ads
Guide to integrate your LinkedIn Ads with Sprinkle
Pipeline Concepts
Before setting up the pipeline, learn about pipeline concepts here
Step by Step Guide
STEP-1: Configure Connection
To learn about Connection, refer here
Log into Sprinkle application
Navigate to Ingst -> Connections Tab -> New Connection ->
Select LinkedIn Ads
Provide all the mandatory details
Name: Name to identify this connection
Connect to LinkedIn
Test Connection
Create
STEP-2: Configure Datasource
To learn about pipeline, refer here
Navigate to Ingest -> Pipeline Tab -> Add ->
Select LinkedIn Ads
Provide the name -> Create
Connection Tab:
From the drop-down, select the name of connection created in STEP-2
Update
STEP-3: Create Dataset
Datasets Tab: To learn about Dataset, refer here. Add Dataset for each report/dataset that you want to integrate, providing following details
Report Type (Required) : Select the API through which you want the result. Read more from LinkedIn api docs. Select report type from any one of the following:
Accounts
Account_Users
AdAccount Id: Select from the drop-down
Campaign_Groups
AdAccount Id: Select from the drop-down
Campaigns
AdAccount Id: Select from the drop-down
SponsoredUpdateCreativeVariables
AdAccount Id: Select from the drop-down
Creatives
AdAccount Id: Select from the drop-down
Conversions
AdAccount Id: Select from the drop-down
AD_Segments_By_Account
AdAccount Id: Select from the drop-down
AD_Targeting_Facets
AD_Forms
AdAccount Id: Select from the drop-down
AD_Analytics
AdAccount Id: Select from the drop-down
Pivot Values: Pivot of results, by which each report data point is grouped. See about Pivot here. Select from the drop-down.
Metrics: Max. 20 metrics can be selected at a time. See about metrics here.
Start Date: Start Date from which you want to fetch data. Give Start Date in Format yyyy-mm-dd
Ingestion Mode:
Complete: Will download full data in every ingestion from the start date.
Time Granularity: Results grouped by the selected value of Time Granularity. See about Time Granularity in Query Parameters here. Select from ALL, MONTHLY, YEARLY.
Incremental: Will download updated rows in the table, based on start date value in first run and checkpoint value in each run. Having Time Granularity set as DAILY
Window for Backfill: Mention window for backfill, for backfilling metrics in every run to include updates from attribution window. Can take values 1, 7 and 28.
Flatten Level(Required) : Select One Level or Multi Level. In one level, flattening will not be applied on complex type. They will be stored as string. In multi level, flattening will be applied in complex level till they become simple type.
Destination Schema (Required) : Data warehouse schema where the table will be ingested into
Destination Table name (Required) : It is the table name to be created on the warehouse. If not given, sprinkle will create like ds_<pipelinename>_<tablename>
Destination Create Table Clause: Provide additional clauses to warehouse-create table queries such as clustering, partitioning, and more, useful for optimizing DML statements. Learn more on how to use this field.
Create
STEP-4: Run and schedule Ingestion
In the Ingestion Jobs tab:
Trigger the Job, using the Run button
To schedule, enable Auto-Run. Change the frequency if needed
Dataset Fields
Account
id
reference_id
currency
name
notified_on_campaign_optimization
notified_on_creative_approval
notified_on_creative_rejection
notified_on_end_of_campaign
notified_on_new_features_enabled
type
status
test
version_tag
AD_Analytics_By_Campaign
campaign_id
date
clicks
impressions
cost_in_usd
cost_in_local_currency
conversion_value_in_local_currency
approximate_unique_impressions
follows
likes
comments
reaction
sends
shares
total_engagements
text_url_clicks
video_views
video_completions
landing_page_clicks
company_page_clicks
viral_*
video_*
AD_Analytics_By_Creative
creative_id
date
clicks
impressions
cost_in_usd
cost_in_local_currency
conversion_value_in_local_currency
approximate_unique_impressions
follows
likes
comments
reaction
sends
shares
total_engagements
video_views
video_completions
landing_page_clicks
company_page_clicks
viral_*
video_*
Campaign
id
account_id
campaign_group
associated_entity
audience_expansion_enabled
cost_type
creative_selection
daily_budget_currency_code
daily_budget_amount
unit_cost_currency_code
unit_cost_amount
local_country
local_language
name
objective_type
run_schedule_start
run_schedule_end
total_budget_currency_code
total_budget_amount
type
version_version_tag
status
story_delivery_enabled
optimization_target_type
format
pacing_strategy
test
story_delivery_enabled
offsite_delivery_enabled
created_time
last_modified_time
Campaign_Group
id
account_id
backfilled
name
run_schedule_start
run_schedule_end
status
total_budget_amount
total_budget_currency_code
test
created_time
last_modified_time
Conversion
id
account_id
attribution_type
enabled
name
latest_first_party_callback
post_click_attribution_window_size
view_through_attribution_window_size
last_callback_at
value_amount
value_currency_code
created
last_modified
Creative
id
campaign_id
clickURL
processing_state
reference
review_stats
rejection_status
status
type
test
created_time
last_modified_time
version_version_tag
Organization
id
default_local_country
default_local_language
deleted_at
version_tag
founded_on
localized_description
localized_name
parent
organization_relationship_type
parent_relationship_status
vanity_name
localized_website
staff_count_range
organization_status
organization_type
primary_organization_type
Page_Stats
date
organization_id
views_about_page_*
views_career_page_*
views_desktop_*
views_life_at_*
views_mobile_*
views_overview_page_*
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