- Introduction
-
Getting Started
- Creating an Account in Hevo
- Subscribing to Hevo via AWS Marketplace
- Subscribing to Hevo via Snowflake Marketplace
- Connection Options
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
-
Data Ingestion
- Types of Data Synchronization
- Ingestion Modes and Query Modes for Database Sources
- Ingestion and Loading Frequency
- Data Ingestion Statuses
- Deferred Data Ingestion
- Handling of Primary Keys
- Handling of Updates
- Handling of Deletes
- Hevo-generated Metadata
- Best Practices to Avoid Reaching Source API Rate Limits
-
Edge
- Getting Started
- Data Ingestion
- Core Concepts
-
Pipelines
- Familiarizing with the Pipelines UI (Edge)
- Creating an Edge Pipeline
- Working with Edge Pipelines
- Pipeline Job History
- Object and Schema Management
- Activity Log
-
Sources
- PostgreSQL
- Oracle
- MySQL
- SQL Server
- CockroachDB
- Troubleshooting Database Sources
- Salesforce Bulk API V2
- Ordergroove
- BambooHR
- Stripe
- NetSuite SuiteAnalytics
- Shopify
- Slack
- ClickUp
- Monday.com
- Pipedrive
- Workable
- Fathom
- HubSpot
- Salesforce Marketing Cloud
- Google Analytics 4
- Google Ads
- Facebook Ads
- Microsoft Ads
- LinkedIn Ads
- Naming Conventions for Source Data Entities
- Destinations
- Transformations
- Alerts
- Custom Connectors
-
Releases
- Edge Release Notes - August 2026
- Edge Release Notes - July 2026
- Edge Release Notes - June 2026
- Edge Release Notes - May 2026
- Edge Release Notes - April 2026
- Edge Release Notes - March 2026
- Edge Release Notes - February 2026
- Edge Release Notes - January 2026
- Edge Release Notes - December 2025
- Edge Release Notes - November 2025
- Edge Release Notes - October 2025
- Edge Release Notes - September 2025
- Edge Release Notes - August 2025
- Edge Release Notes - July 2025
- Edge Release Notes - November 2024
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Data Loading
- Loading Data in a Database Destination
- Loading Data to a Data Warehouse
- Optimizing Data Loading for a Destination Warehouse
- Deduplicating Data in a Data Warehouse Destination
- Manually Triggering the Loading of Events
- Scheduling Data Load for a Destination
- Loading Events in Batches
- Data Loading Statuses
- Data Spike Alerts
- Name Sanitization
- Table and Column Name Compression
- Parsing Nested JSON Fields in Events
-
Pipelines
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
- Working with Pipelines
- Managing Objects in Pipelines
- Pipeline Jobs
-
Transformations
-
Python Code-Based Transformations
- Supported Python Modules and Functions
-
Transformation Methods in the Event Class
- Create an Event
- Retrieve the Event Name
- Rename an Event
- Retrieve the Properties of an Event
- Modify the Properties for an Event
- Fetch the Primary Keys of an Event
- Modify the Primary Keys of an Event
- Fetch the Data Type of a Field
- Check if the Field is a String
- Check if the Field is a Number
- Check if the Field is Boolean
- Check if the Field is a Date
- Check if the Field is a Time Value
- Check if the Field is a Timestamp
-
TimeUtils
- Convert Date String to Required Format
- Convert Date to Required Format
- Convert Datetime String to Required Format
- Convert Epoch Time to a Date
- Convert Epoch Time to a Datetime
- Convert Epoch to Required Format
- Convert Epoch to a Time
- Get Time Difference
- Parse Date String to Date
- Parse Date String to Datetime Format
- Parse Date String to Time
- Utils
- Examples of Python Code-based Transformations
-
Drag and Drop Transformations
- Special Keywords
-
Transformation Blocks and Properties
- Add a Field
- Change Datetime Field Values
- Change Field Values
- Drop Events
- Drop Fields
- Find & Replace
- Flatten JSON
- Format Date to String
- Format Number to String
- Hash Fields
- If-Else
- Mask Fields
- Modify Text Casing
- Parse Date from String
- Parse JSON from String
- Parse Number from String
- Rename Events
- Rename Fields
- Round-off Decimal Fields
- Split Fields
- Examples of Drag and Drop Transformations
- Effect of Transformations on the Destination Table Structure
- Transformation Reference
- Transformation FAQs
-
Python Code-Based Transformations
-
Schema Mapper
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Manually Mapping Event Types
- Modifying Schema Mapping for Event Types
- Schema Mapper Actions
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Resizing String Columns in the Destination
- Changing the Data Type of a Destination Table Column
- Schema Mapper Compatibility Table
- Limits on the Number of Destination Columns
- File Log
- Troubleshooting Failed Events in a Pipeline
- Mismatch in Events Count in Source and Destination
- Audit Tables
- Activity Log
-
Pipeline FAQs
- Can multiple Sources connect to one Destination?
- What happens if I re-create a deleted Pipeline?
- Why is there a delay in my Pipeline?
- Can I change the Destination post-Pipeline creation?
- Why is my billable Events high with Delta Timestamp mode?
- Can I drop multiple Destination tables in a Pipeline at once?
- How does Run Now affect scheduled ingestion frequency?
- Will pausing some objects increase the ingestion speed?
- Can I see the historical load progress?
- Why is my Historical Load Progress still at 0%?
- Why is historical data not getting ingested?
- How do I set a field as a primary key?
- How do I ensure that records are loaded only once?
- Why can't I see my Pipelines after logging in?
- Events Usage
-
Sources
- Free Sources
-
Databases and File Systems
- Data Warehouses
-
Databases
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Elasticsearch
-
MongoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
-
Troubleshooting MongoDB
-
Errors During Pipeline Creation
- Error 1001 - Incorrect credentials
- Error 1005 - Connection timeout
- Error 1006 - Invalid database hostname
- Error 1007 - SSH connection failed
- Error 1008 - Database unreachable
- Error 1011 - Insufficient access
- Error 1028 - Primary/Master host needed for OpLog
- Error 1029 - Version not supported for Change Streams
- SSL 1009 - SSL Connection Failure
- Troubleshooting MongoDB Change Streams Connection
- Troubleshooting MongoDB OpLog Connection
-
Errors During Pipeline Creation
- SQL Server
-
MySQL
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Generic MySQL
- Google Cloud MySQL
- MariaDB MySQL
-
Troubleshooting MySQL
-
Errors During Pipeline Creation
- Error 1003 - Connection to host failed
- Error 1006 - Connection to host failed
- Error 1007 - SSH connection failed
- Error 1011 - Access denied
- Error 1012 - Replication access denied
- Error 1017 - Connection to host failed
- Error 1026 - Failed to connect to database
- Error 1027 - Unsupported BinLog format
- Failed to determine binlog filename/position
- Schema 'xyz' is not tracked via bin logs
- Errors Post-Pipeline Creation
-
Errors During Pipeline Creation
- MySQL FAQs
- Oracle
-
PostgreSQL
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Generic PostgreSQL
- Google Cloud PostgreSQL
- Heroku PostgreSQL
- Upgrading Pipelines with PostgreSQL Sources to Use the pgoutput Plugin
-
Troubleshooting PostgreSQL
-
Errors during Pipeline creation
- Error 1003 - Authentication failure
- Error 1006 - Connection settings errors
- Error 1011 - Access role issue for logical replication
- Error 1012 - Access role issue for logical replication
- Error 1014 - Database does not exist
- Error 1017 - Connection settings errors
- Error 1023 - No pg_hba.conf entry
- Error 1024 - Number of requested standby connections
- Errors Post-Pipeline Creation
-
Errors during Pipeline creation
-
PostgreSQL FAQs
- Can I track updates to existing records in PostgreSQL?
- How can I migrate a Pipeline created with one PostgreSQL Source variant to another variant?
- How can I prevent data loss when migrating or upgrading my PostgreSQL database?
- Why do FLOAT4 and FLOAT8 values in PostgreSQL show additional decimal places when loaded to BigQuery?
- Why is data not being ingested from PostgreSQL Source objects?
- Troubleshooting Database Sources
- Database Source FAQs
- File Storage
- Engineering Analytics
- Finance & Accounting Analytics
-
Marketing Analytics
- ActiveCampaign
- AdRoll
- Amazon Ads
- Apple Search Ads
- AppsFlyer
- CleverTap
- Criteo
- Drip
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Freshsales
- Google Ads
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo v2
- Lemlist
- LinkedIn Ads
- Mailchimp
- Mailshake
- Marketo
- Microsoft Ads
- Onfleet
- Outbrain
- Pardot
- Pinterest Ads
- Pipedrive
- Recharge
- Segment
- SendGrid Webhook
- SendGrid
- Salesforce Marketing Cloud
- Snapchat Ads
- SurveyMonkey
- Taboola
- TikTok Ads
- Twitter Ads
- Typeform
- YouTube Analytics
- Product Analytics
- Sales & Support Analytics
- Source FAQs
-
Destinations
- Familiarizing with the Destinations UI
- Cloud Storage-Based
- Databases
-
Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
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Google BigQuery
- Clustering in BigQuery
- Partitioning in BigQuery
- Structure of Data in the Google BigQuery Data Warehouse
- Loading Data to a Google BigQuery Data Warehouse
- Near Real-time Data Loading using Streaming
- Modifying BigQuery Destinations to Use Service Account Authentication
- Troubleshooting Google BigQuery
- Google BigQuery FAQs
- Hevo Managed Google BigQuery
- Snowflake
- Troubleshooting Data Warehouse Destinations
-
Destination FAQs
- Can I change the primary key in my Destination table?
- Can I change the Destination table name after creating the Pipeline?
- How can I change or delete the Destination table prefix?
- Why does my Destination have deleted Source records?
- How do I filter deleted Events from the Destination?
- Does a data load regenerate deleted Hevo metadata columns?
- How do I filter out specific fields before loading data?
- Transform
- Alerts
- Account Management
- Activate
- Glossary
-
Releases- 2026 Releases
-
2025 Releases
- Release 2.44 (Dec 01, 2025-Jan 12, 2026)
- Release 2.43 (Nov 03-Dec 01, 2025)
- Release 2.42 (Oct 06-Nov 03, 2025)
- Release 2.41 (Sep 08-Oct 06, 2025)
- Release 2.40 (Aug 11-Sep 08, 2025)
- Release 2.39 (Jul 07-Aug 11, 2025)
- Release 2.38 (Jun 09-Jul 07, 2025)
- Release 2.37 (May 12-Jun 09, 2025)
- Release 2.36 (Apr 14-May 12, 2025)
- Release 2.35 (Mar 17-Apr 14, 2025)
- Release 2.34 (Feb 17-Mar 17, 2025)
- Release 2.33 (Jan 20-Feb 17, 2025)
-
2024 Releases
- Release 2.32 (Dec 16 2024-Jan 20, 2025)
- Release 2.31 (Nov 18-Dec 16, 2024)
- Release 2.30 (Oct 21-Nov 18, 2024)
- Release 2.29 (Sep 30-Oct 22, 2024)
- Release 2.28 (Sep 02-30, 2024)
- Release 2.27 (Aug 05-Sep 02, 2024)
- Release 2.26 (Jul 08-Aug 05, 2024)
- Release 2.25 (Jun 10-Jul 08, 2024)
- Release 2.24 (May 06-Jun 10, 2024)
- Release 2.23 (Apr 08-May 06, 2024)
- Release 2.22 (Mar 11-Apr 08, 2024)
- Release 2.21 (Feb 12-Mar 11, 2024)
- Release 2.20 (Jan 15-Feb 12, 2024)
-
2023 Releases
- Release 2.19 (Dec 04, 2023-Jan 15, 2024)
- Release Version 2.18
- Release Version 2.17
- Release Version 2.16 (with breaking changes)
- Release Version 2.15 (with breaking changes)
- Release Version 2.14
- Release Version 2.13
- Release Version 2.12
- Release Version 2.11
- Release Version 2.10
- Release Version 2.09
- Release Version 2.08
- Release Version 2.07
- Release Version 2.06
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2022 Releases
- Release Version 2.05
- Release Version 2.04
- Release Version 2.03
- Release Version 2.02
- Release Version 2.01
- Release Version 2.00
- Release Version 1.99
- Release Version 1.98
- Release Version 1.97
- Release Version 1.96
- Release Version 1.95
- Release Version 1.93 & 1.94
- Release Version 1.92
- Release Version 1.91
- Release Version 1.90
- Release Version 1.89
- Release Version 1.88
- Release Version 1.87
- Release Version 1.86
- Release Version 1.84 & 1.85
- Release Version 1.83
- Release Version 1.82
- Release Version 1.81
- Release Version 1.80 (Jan-24-2022)
- Release Version 1.79 (Jan-03-2022)
-
2021 Releases
- Release Version 1.78 (Dec-20-2021)
- Release Version 1.77 (Dec-06-2021)
- Release Version 1.76 (Nov-22-2021)
- Release Version 1.75 (Nov-09-2021)
- Release Version 1.74 (Oct-25-2021)
- Release Version 1.73 (Oct-04-2021)
- Release Version 1.72 (Sep-20-2021)
- Release Version 1.71 (Sep-09-2021)
- Release Version 1.70 (Aug-23-2021)
- Release Version 1.69 (Aug-09-2021)
- Release Version 1.68 (Jul-26-2021)
- Release Version 1.67 (Jul-12-2021)
- Release Version 1.66 (Jun-28-2021)
- Release Version 1.65 (Jun-14-2021)
- Release Version 1.64 (Jun-01-2021)
- Release Version 1.63 (May-19-2021)
- Release Version 1.62 (May-05-2021)
- Release Version 1.61 (Apr-20-2021)
- Release Version 1.60 (Apr-06-2021)
- Release Version 1.59 (Mar-23-2021)
- Release Version 1.58 (Mar-09-2021)
- Release Version 1.57 (Feb-22-2021)
- Release Version 1.56 (Feb-09-2021)
- Release Version 1.55 (Jan-25-2021)
- Release Version 1.54 (Jan-12-2021)
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2020 Releases
- Release Version 1.53 (Dec-22-2020)
- Release Version 1.52 (Dec-03-2020)
- Release Version 1.51 (Nov-10-2020)
- Release Version 1.50 (Oct-19-2020)
- Release Version 1.49 (Sep-28-2020)
- Release Version 1.48 (Sep-01-2020)
- Release Version 1.47 (Aug-06-2020)
- Release Version 1.46 (Jul-21-2020)
- Release Version 1.45 (Jul-02-2020)
- Release Version 1.44 (Jun-11-2020)
- Release Version 1.43 (May-15-2020)
- Release Version 1.42 (Apr-30-2020)
- Release Version 1.41 (Apr-2020)
- Release Version 1.40 (Mar-2020)
- Release Version 1.39 (Feb-2020)
- Release Version 1.38 (Jan-2020)
- Early Access New
Edge Pipeline is now available for Public Review. You can explore and evaluate its features and share your feedback.
LinkedIn is the world’s largest professional network, and LinkedIn Ads is its self-serve advertising platform that lets businesses reach and engage professional audiences at scale. It provides ad formats such as Sponsored Content, Sponsored Messaging, Text Ads, and Dynamic Ads, along with tools to create Lead Gen Forms, target audiences by professional attributes, and measure campaign performance and conversions.
Hevo uses the LinkedIn Marketing API to replicate data from your LinkedIn Ads account to the Destination of your choice. To ingest the data, you must authorize Hevo to access your LinkedIn Ads account using Open Authorization (OAuth) 2.0.
Supported Features
| Feature Name | Supported |
|---|---|
| Capture deletes | No |
| History mode | No |
| Custom data (user-configured tables & fields) | No |
| Data blocking (skip objects and fields) | Yes |
| Resync (objects and Pipelines) | Yes |
| API configurable | No |
Prerequisites
-
An active LinkedIn Ads account exists, with at least one ad account, from which data is to be ingested.
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You have the required user role on the LinkedIn ad account(s) you want to sync.
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To sync the Follower Statistics, Page Statistics, and Share Statistics objects, the authorized account must have Administrator access to the LinkedIn Company Page(s) associated with your ad accounts.
Configure Linkedin Ads as a Source in your Pipeline
Perform the following steps to configure your Linkedin Ads Source:
-
Click Pipelines in the Navigation Bar.
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Click + Create Pipeline in the Pipelines List View.
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On the Select Source Type page, select Linkedin Ads.
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On the Select Destination Type page, select the type of Destination you want to use.
-
On the Select Pipeline Type page, click Edge, and then click Continue.

This page appears only if the selected Destination type is supported in Edge and your Team has an existing Linkedin Ads Pipeline with the same Destination type. Otherwise, you can proceed to create an Edge Pipeline.
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In the Connect to your LinkedIn Ads account section, click Authenticate Your LinkedIn Ads Account, log in to your LinkedIn Ads account, and click Allow to grant Hevo access to your account.

-
In the Configure Source screen, specify the following:

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In the Sync Settings section:
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Accounts sync mode: Choose whether to sync data from all accessible accounts or only specific accounts.
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Sync all accounts: Hevo syncs data for all ad accounts accessible to your authorized LinkedIn Ads account, including any accounts added later.
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Sync specific accounts: Hevo ingests data only for the accounts you select from the Accounts to sync drop-down.
-
-
Historical Sync Time Frame: The duration for which you want to ingest existing data from the Source. This cannot be changed after the Pipeline is created.
-
-
In the Conversion Attribution Settings section:
-
View-Through Attribution window: The number of days between a person viewing your ad and completing a conversion. Default value: 7 days.
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Post-Click Attribution window: The number of days between a person clicking your ad and completing a conversion. Default value: 30 days.
-
-
-
Click Test & Continue to test the connection to your Linkedin Ads Source.
Data Replication
Hevo replicates data for all the objects selected on the Configure Objects page during Pipeline creation. By default, all supported objects and their available fields are selected. However, you can modify this selection while creating or editing the Pipeline.
Selecting a parent object automatically includes all its associated child objects for replication. Child objects cannot be selected or deselected individually.
Hevo ingests the following types of data from your Source objects:
-
Historical Data: The first run of the Pipeline ingests historical data for the selected objects, based on the Historical Sync Time Frame specified when creating the Pipeline, and loads it into the Destination.
-
Incremental Data: Once the historical load is complete, new and updated records for objects are ingested as per the sync frequency.
For the following objects, Hevo ingests only the incremental data in subsequent Pipeline runs:
| Object Category | Objects |
|---|---|
| Ad Analytics Reports | Ad Analytics by Campaign, Ad Analytics by Creative, Ad Analytics by Creative with Conversion Breakdown, Monthly Ad Analytics by Member Country, Monthly Ad Analytics by Member Region, Monthly Ad Analytics by Member Company, Monthly Ad Analytics by Member Company Size, Monthly Ad Analytics by Member Industry, Monthly Ad Analytics by Member Seniority, Monthly Ad Analytics by Member Job Function, Monthly Ad Analytics by Member Job Title |
| Company Page Analytics | Follower Statistics, Page Statistics |
| Reference Data | Organization |
For the Ad Analytics objects, Hevo uses the day field for daily reports and the month field for monthly reports to fetch incremental data.
For Follower Statistics and Page Statistics objects, Hevo fetches incremental data using the date field.
To capture delayed conversion updates, Hevo also re-fetches data within the configured View-Through Attribution or Post-Click Attribution window, depending on which is longer, during every Pipeline run.
For all other objects, Hevo ingests the entire data during each Pipeline run.
Linkedin Ads currently enforces a rate limit on the ad analytics reporting endpoint. If this limit is exceeded, a rate limit exception occurs. To understand how Hevo handles such scenarios, read Handling Rate Limit Exceptions.
Note: You can create a Pipeline with this Source only using the Merge load mode. The Append mode is not supported for this Source.
Schema and Primary Keys
Hevo uses the following schema to upload the records to the Destination. For a detailed view of the objects, fields, and relationships, click the ERD.
Data Model
The following is the list of tables (objects) that are created at the Destination when you run the Pipeline:
| Object | Description |
|---|---|
| Account | Contains basic details about a LinkedIn ad account, including its name, currency, linked organization, and status. This object has a child object, Account Serving Status. |
| Account User | Contains details of which LinkedIn members have access to an ad account and what role each one holds, such as Account Manager or Viewer. |
| Ad Analytics by Campaign | Contains daily performance metrics for each campaign, including impressions, clicks, spend, conversions, and engagement. |
| Ad Analytics by Creative | Contains daily performance metrics for each ad creative. |
| Ad Analytics by Creative with Conversion Breakdown | Contains daily performance metrics for each ad creative, split out by conversion rule. |
| Campaign | Contains details of each campaign, including its objective, budget, bid strategy, and status. This object has the following child objects: - Campaign Serving Status - Targeting Criteria Include - Targeting Criteria Exclude |
| Campaign Group | Contains details of campaign groups that organize related campaigns, including budget, run schedule, and status. This object has the following child objects: - Campaign Group Serving Status - Campaign Group Allowed Campaign Type |
| Conversion | Contains details of conversion rules set up in the account, including how conversions are tracked, the time window used to count them, and the value assigned. This object has a child object, Conversion Associated Campaign. |
| Creative | Contains details of each ad creative, including its type (Sponsored Content, Text Ad, Spotlight, Follower, Jobs, Document, or Event ad), review status, and associated campaign. This object has a child object, Creative Serving Status. |
| Distribution Target Industry | Contains the industry-based targeting rules set for a Post’s distribution. |
| Distribution Target Interface Locale | Contains the language-based targeting rules set for a Post’s distribution. |
| Distribution Target Job Function | Contains the job-function-based targeting rules set for a Post’s distribution. |
| Distribution Target Location | Contains the location-based targeting rules set for a Post’s distribution. |
| Distribution Target Seniority | Contains the seniority-based targeting rules set for a Post’s distribution. |
| Distribution Target Staff Count Range | Contains the company-size-based targeting rules set for a Post’s distribution. |
| Document | Contains details of document files uploaded for use in Document Ads and document posts. |
| Follower Statistics | Contains the daily count of new organic and paid followers gained by an organization’s LinkedIn Page. |
| Function | Contains LinkedIn’s standard list of job functions, used across targeting and reporting. |
| Geo | Contains LinkedIn’s standard list of geographic locations, used across targeting and reporting. |
| Image | Contains details of image files uploaded for use in creatives and posts. |
| Industry | Contains LinkedIn’s standard list of industries, used across targeting and reporting. |
| InMail Content | Contains the message content for Sponsored InMail and Conversation Ads creatives, including the subject line, body, sender, and call-to-action. |
| Lead Form | Contains details of Lead Gen Forms, including the headline, privacy policy consent text, and the message shown after submission. This object has the following child objects: - Lead Form Question - Lead Form Consent - Lead Form Hidden Field - Lead Form Rejection Reason |
| Lead Form Response | Contains individual lead submissions collected through a Lead Form. This object has the following child objects: - Lead Form Response Answer - Lead Form Response Multiple Choice Answers - Lead Form Response Consent |
| Monthly Ad Analytics by Member Company | Contains monthly campaign performance metrics, broken down by the company of the members reached. |
| Monthly Ad Analytics by Member Company Size | Contains monthly campaign performance metrics, broken down by the company size of the members reached. |
| Monthly Ad Analytics by Member Country | Contains monthly campaign performance metrics, broken down by the country of the members reached. |
| Monthly Ad Analytics by Member Industry | Contains monthly campaign performance metrics, broken down by the industry of the members reached. |
| Monthly Ad Analytics by Member Job Function | Contains monthly campaign performance metrics, broken down by the job function of the members reached. |
| Monthly Ad Analytics by Member Job Title | Contains monthly campaign performance metrics, broken down by the job title of the members reached. |
| Monthly Ad Analytics by Member Region | Contains monthly campaign performance metrics, broken down by the region of the members reached. |
| Monthly Ad Analytics by Member Seniority | Contains monthly campaign performance metrics, broken down by the seniority of the members reached. |
| Multi Image | Contains the individual images that make up a multi-image Post. |
| Organization | Contains details of LinkedIn Company Pages referenced across your campaigns, ad accounts, and analytics data, including the name, description, and logo. |
| Page Statistics | Contains daily view statistics for an organization’s LinkedIn Company Page, broken down by device and page tab. |
| Poll | Contains the question, options, and vote counts of a poll Post. |
| Post | Contains details of organic and sponsored posts (shares) published from your LinkedIn Company Page, including the author, commentary, visibility, and lifecycle state. This object has the following child objects: - Content - Carousel Card |
| Seniority | Contains LinkedIn’s standard list of job seniority levels, used across targeting and reporting. |
| Share Statistics | Contains engagement statistics, such as impressions, clicks, likes, comments, and shares, for posts published from an organization’s LinkedIn Company Page. |
| Sponsored Message Content | Contains the message body, sender, and call-to-action content of a Conversation Ads (sponsored message) campaign. This object has a child object, Sponsored Message Option. |
| Sponsored Message Option | Contains the reply options and follow-up content configured for a Sponsored Message Content. |
| Title | Contains LinkedIn’s standard list of job titles, used across targeting and reporting. |
Additional Information
Read the detailed Hevo documentation for the following related topics:
Source Considerations
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LinkedIn retains most ad performance data, such as account, campaign, and creative analytics, for up to 10 years, while professional demographic data, such as Monthly Ad Analytics by Member, is retained for only 2 years. Hevo cannot ingest data older than these retention periods.
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Some metrics are not available immediately through the LinkedIn API. Metrics based on professional demographics, such as company size and job function, can be delayed by 12–24 hours, while the videoWatchTime and averageVideoWatchTime metrics can take up to 48 hours to become available.
Revision History
Refer to the following table for the list of key updates made to this page:
| Date | Release | Description of Change |
|---|---|---|
| Aug-04-2026 | NA | New document. |