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On this page
  • Datasource Concepts
  • Step by Step Guide
  • STEP-1: Configure Connection
  • STEP-2: Configure Datasource
  • STEP-3: Create Dataset
  • STEP-4: Run and schedule Ingestion
  • Dataset Fields
  1. Ingesting your data
  2. Data Imports
  3. Applications

LinkedIn Ads

Guide to integrate your LinkedIn Ads with Sprinkle

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Last updated 1 year ago

Datasource Concepts

Before setting up the datasource, learn about datasource concepts

Step by Step Guide

STEP-1: Configure Connection

To learn about Connection, refer

  • Log into Sprinkle application

  • Navigate to Datasources -> 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

  • Navigate to Datasources -> Datasources 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

    • 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

      • 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.

        • 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_<datasourcename>_<tablename>

  • 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

Account_User
  • user_id

  • account_id

  • role

  • campaign_contact

  • created_time

  • last_modified_at

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

Campaigns_Associated_With_Conversions
  • campaign_id

  • conversion_id

  • associated_at

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

Follower_Stats
  • date

  • organization_id

  • organic_follower_gain

  • paid_follower_gain

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_*

Share_Stats
  • date

  • organization_id

  • click_count

  • comment_count

  • comment_mentions_count

  • engagement

  • impression_count

  • ike_count

  • share_count

  • share_mentions_count

  • unique_impressions_count

Video_Ads
  • content_reference

  • account_id

  • name

  • owner

  • type

To learn about datasource, refer

Datasets Tab: To learn about Dataset, refer . 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 . Select report type from any one of the following:

Pivot Values: Pivot of results, by which each report data point is grouped. See about Pivot . Select from the drop-down.

Metrics: Max. 20 metrics can be selected at a time. See about metrics .

Time Granularity: Results grouped by the selected value of Time Granularity. See about Time Granularity in Query Parameters . Select from ALL, MONTHLY, YEARLY.

Destination Create Table Clause: Provide additional clauses to warehouse-create table queries such as clustering, partitioning, and more, useful for optimizing DML statements. on how to use this field.

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