How to connect LinkedIn Ads to Google Sheets with OWOX Data Marts

Why we made this free connector

At OWOX, we believe marketing teams shouldn’t have to rent access to their own LinkedIn Ads data. So the LinkedIn Ads connector is free and open source: run OWOX Data Marts yourself and there is no paid tier and no hidden features. The longer story is in why we built free data connectors for analysts.

Join the open-source movement

We’re not just releasing a free connector, we’re inviting you to help shape the future of open marketing analytics tools.

At OWOX, we believe that data access and transparency should be a right, not a luxury. That’s why this connector is 100% open-source – giving you full control over how it works, what it does, and how far it can go.

If you like what we do, please ⭐ star our GitHub repo to show your support – it helps us reach more analysts and grow the number of available connectors.

Also, feel free to:

•  Explore the code and customize it to fit your needs.
• Contribute to this data connectivity ecosystem: suggest new connectors, pull new connectors, and / or documentation to support the wider community.
• Join our community & share your feedback.

We’ve built the core, the foundation; now it’s your turn to take it further.

Why bring LinkedIn Ads data into Google Sheets?

If you’ve used LinkedIn Ads Manager, you know the pain:
❌ Reports are rigid, hard to customize, and don’t scale
❌ Manual exports get stale quickly and limit your analysis
❌ No simple way to connect ad data with GA4, HubSpot, or your CRM

This free LinkedIn Ads → Google Sheets connector changes that:
✅ Pull raw campaign, account, and organization-level data directly into Sheets
✅ Merge LinkedIn Ads data with your pipeline for unified reporting
✅ Define exactly which fields, metrics, and URNs you want,  no guesswork
✅ Automate refreshes and build shareable dashboards your team uses

If you’re building ROAS models, evaluating B2B performance, or mapping multi-touch attribution, this connector gives you the flexibility and structure LinkedIn Ads Manager never could.

Sheets is where marketers want to work, and that part is right. The open question is where the data should live while they do.

Why the data goes through a data warehouse

A sheet is where people read data, not where it should live. That is why OWOX Data Marts puts a data warehouse in the middle, and why there is no direct LinkedIn-to-sheet connector. Four things follow.

The sheet has a ceiling

A Google Sheets file holds at most 10 million cells. Ad data eats cells quietly: every campaign, every day and every breakdown is a row, and every field you pull is a column, so a wide import burns through the limit faster than the row count suggests.

LinkedIn’s analytics endpoint also caps a single response at 15,000 rows, so long histories are loaded in date ranges. The data warehouse holds the full history. The sheet report holds only the columns you choose.

History outlives the sheet

Data loaded into a data warehouse stays there. A tab that gets overwritten, a sheet someone re-copies or an upstream API that changes its schema does not take last year’s numbers with it. B2B sales cycles are long, so the question is often how spend from two quarters ago relates to pipeline today, and that needs the history to still be there.

LinkedIn is rarely the only channel

The moment the question is “which platform is actually paying back?”, LinkedIn data alone is not enough, and blending tabs in a sheet means lookup formulas that break when a campaign is renamed.

OWOX’s demo e-commerce project shows the alternative. Each ad platform is collected by its own connector data mart, and LinkedIn Ads is one of them – the same connector can land in BigQuery, Snowflake, Databricks or Redshift:

A separate data mart, Unified Ad Spend, then brings the platforms together. The analyst who owns it wrote the SQL: one SELECT per platform, all UNION ALLed to one daily grain with a shared source, medium and campaign naming. Here is its LinkedIn block, which maps LinkedIn’s own cost, click and conversion columns onto the shared ones:

OWOX Data Marts does not model the data for you. It publishes and governs the query the analyst wrote, so everyone reads the same definition.

One number, every place you read it

The same data mart can feed a Google Sheets report, a Looker Studio dashboard, a Slack channel or an email, so the number in the sheet is the number in the dashboard. Business users read it without needing data warehouse credentials.

How it works

1. A LinkedIn Ads data mart of the Connector type loads your ad data into tables in your data warehouse. A manual run backfills history, and a trigger keeps it fresh.
2. Google Sheets is connected as a destination. The data mart publishes its data there.
3. You read it in Sheets with a report created on the data mart, or by pulling it with the OWOX Data Marts extension inside Google Sheets.
4. Or you just ask. Through OWOX MCP you can blend the same data with other LinkedIn Ads endpoints, other ad platforms, or your CRM and GA4 data, using the data model.

OWOX Data Marts does not transform your data. It loads, publishes and governs it, and any SQL on top is written by an analyst.

What you need

• A data warehouse. OWOX Data Marts supports BigQuery, Snowflake, Databricks, AWS Athena and AWS Redshift. The examples here use BigQuery.
• A LinkedIn Ads account you can read campaign data from, and its Account URNs.
• OWOX Data Marts, either self-managed with Node.js and the OWOX CLI (free and open source) or OWOX Cloud.
• A Google account for the Google Sheets report.

Step-by-step: send LinkedIn Ads data to Google Sheets

Seven steps. The first five load your LinkedIn Ads data into your data warehouse. The last two bring it into Google Sheets.

Step 1: Start OWOX Data Marts ( ~2 min)

Choose how to run it:

• OWOX Cloud: sign in or sign up and you are ready for step 2.

• Self-managed (open source): install Node.js 22.22.0 or later, then run:

  npm install -g owox
  owox serve

  Open http://localhost:3000 and you are in. The OWOX docs cover deployment options beyond a local machine.

Step 2: Connect your data warehouse ( ~3 min)

Open Storages in the left menu and add your data warehouse, for example BigQuery. This is where the LinkedIn Ads tables will be created. The BigQuery walkthrough, including the service account, is in the LinkedIn Ads → BigQuery guide.

Step 3: Create the LinkedIn Ads Data Mart ( ~2 min)

1. Click New Data Mart, give it a title and select the data warehouse from step 2.
2. Set the type to Connector and choose LinkedIn Ads (the LinkedIn Ads data source).
3. Authorize the connection:
   • OWOX Cloud: authorize LinkedIn Ads with your login through OAuth. There are no credentials to copy.
   • Open-source version: it has no OAuth, so you connect with a Client ID, a Primary Client Secret and a Refresh Token from a LinkedIn developer app. Get them below, then paste them into the connector.
4. Add your Account URNs. To find one, open LinkedIn Ads in Campaign Manager and look for the account URN:

Open-source version: get your LinkedIn credentials

The open-source version needs three things from a LinkedIn developer app: a Client ID, a Primary Client Secret and a Refresh Token. Follow these steps to get them.

• Visit the LinkedIn Developer portal.
  • Navigate to: https://www.linkedin.com/developers/
• Create a new app:
  • Click the Create App button**.**

• Enter your App Name.
• Paste the link to your company’s LinkedIn page in the LinkedIn Page field.

• Upload your company logo.
• Accept the legal agreement and click Create App.

• Verify your app:
  • Go to the Settings tab.
  • Click the Verify button.

The admin of your LinkedIn company page will receive a request to approve the app.

• Request access to the LinkedIn Advertising API:
  • Go to the Products tab of your app.
  • Request access to the Advertising API.

Note: Approval may take up to 24 hours. You’ll receive an email once approved.

• Once approved, the Advertising API will appear under the Added Products section.

• Copy your Client ID and Primary Client Secret:
  • On the Auth tab, copy the Client ID and the Primary Client Secret.
• Generate the token:
  • On the same Auth tab, click OAuth 2.0 Tools in the right-hand panel.

• Click the Create Token button.

• Configure scopes:
  • If you see the error: “There aren’t any scopes available for this app…”, it means the Advertising API access has not been granted yet.

• Ensure these two scopes are selected:

r_ads
r_ads_reporting

• Then click **Request access token.

  **

• Authorize and copy the Refresh Token:

  • On the next screen, click Allow to approve access.
  • Copy the Refresh Token, not the Access Token. The Refresh Token is at the bottom of the page. Store it securely.

Step 4: Choose what to load and backfill your history ( ~2 min)

1. Select the endpoint: Ad Accounts, Campaign Groups, Campaigns, Creatives or the LinkedIn Ads Analytics Report. Ad Accounts is the simplest first run, and the LinkedIn Ads Analytics Report carries the impressions, clicks, spend and conversions that most reports need.
2. Select the fields you need and set the dataset name, or keep the default.
3. Click Publish Data Mart.
4. Click Manual Run and choose Backfill for the first run. Add the start and end dates and click Run. This puts your historical LinkedIn Ads data into the data warehouse. For a long history, run it in date ranges.
5. Open Run History and check for Success.

An incremental load, which imports the current day plus a lookback window, takes over once you schedule it in the next step.

Step 5: Schedule the refresh ( ~1 min)

1. Open the Triggers tab of the data mart and click Add Trigger.
2. Choose Connector Run as the trigger type, then set daily, weekly, monthly or interval, plus the time, days and time zone.
3. Click Create Trigger. LinkedIn Ads data now refreshes on its own.

Step 6: Connect Google Sheets as a destination ( ~2 min)

Open Destinations in the left menu, click New Destination and choose Google Sheets (more on the Google Sheets destination). A destination is where a data mart can deliver its data; the same list also holds Looker Studio, Slack and email.

Step 7: Bring the data into Google Sheets ( ~2 min)

You have two ways to read the data mart in Sheets. Both are part of spreadsheet reporting in OWOX Data Marts.

Option A: a report on the data mart. Reports live on the Destinations tab.

1. Open the data mart, go to the Destinations tab and click New Report under your Google Sheets destination.
2. Give the report a title and share the Google document with the address the form shows.
3. Paste the URL of your Google Sheet, or click New Sheet to create one.
4. Choose the report columns you want in the sheet.
5. Click Create & Run report.

Each report is listed on the Destinations tab with its last run and status. Run it again whenever you need fresh data, or put it on a schedule with a report trigger.

Option B: the OWOX Data Marts extension. Install OWOX Data Marts from the Google Workspace Marketplace, open it inside Google Sheets and pull the data mart from there, without leaving the sheet. If your team works in Excel, there is an OWOX Excel add-in too.

Ask the blended question in plain language

LinkedIn Ads data rarely answers a question on its own. With OWOX MCP you can blend it with other LinkedIn Ads endpoints, with other ad platforms, or with your CRM data and GA4 data (GA4 through its native BigQuery export), using the data model, and ask for all of it in plain language.

Once ad spend is a governed data mart, nobody has to write the join to ask about it. Connect Claude to OWOX Data Marts with the OWOX Claude connector and a marketer can ask:

How does LinkedIn compare with our other paid channels on cost per conversion?

Claude asks OWOX which data marts are relevant, reads their fields and the joins the analyst defined, and queries the one it picks. Ask it against raw data warehouse tables instead and it has to guess the join.

Here is the answer Claude gave against OWOX’s demo e-commerce project:

MCP is the interface here, not the guarantee. The guarantee is the governed data mart behind it, and every question is logged in Run History. For how that works end to end, read governed MCP analytics.

What’s next?

This connector is part of our effort to make data ownership simple, transparent and accessible for everyone.

Here are more resources to explore:

• The LinkedIn Ads connector for each data warehouse: BigQuery, Snowflake, Databricks, AWS Athena and AWS Redshift.
• The full data warehouse setup in the LinkedIn Ads → BigQuery guide.
• The same route for another platform: Facebook Ads → Google Sheets. More free connectors are on the connectors page.

Check out our GitHub repo, leave us a ⭐ star, and let’s build better tools together.

Google BigQueryHow to Load Data into BigQuery: Every Method and When to Use ItOctober 6, 2026→Data IntegrationHow to Connect Facebook Ads to Google Sheets with OWOX Data MartsSeptember 30, 2026→Google BigQueryHow to Connect BigQuery to Google Sheets: Three WaysOctober 6, 2026→

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