Monday morning. You open three browser tabs: Meta Ads Manager for the Facebook and Instagram numbers, LinkedIn Campaign Manager for the Sponsored Content stats, Google Analytics 4 (GA4) for the website conversions. You copy the numbers from each dashboard into a spreadsheet. It takes 20 minutes, and by the time you are done, the data is already a day old. The spreadsheet gets sent to your manager, who asks a question you cannot answer because the data in that column came from a different time period than the data in this column.

This is the Monday spreadsheet shuffle. It happens in marketing teams everywhere, and it wastes hours every week. The fix is a reporting workflow that collects the data and builds the report without anyone copying and pasting. Airtable, Make and Google Analytics 4 are the three tools that do this work for you. Google Analytics is a popular choice for measuring social campaign attribution, and this workflow takes the manual effort out of using it well.

What the Monday spreadsheet shuffle looks like

The problem is not that the data does not exist. GA4 has all the session data, conversion events, and revenue attribution you need. LinkedIn Campaign Manager knows your cost per lead. Meta knows your reach and engagement. The problem is that each platform speaks a different language. GA4 labels a conversion from LinkedIn as "social" with source "linkedin.com / referral." LinkedIn calls it a "lead form fill." You spend your Monday translating between these taxonomies instead of analysing what the numbers mean.

According to Gartner, marketing teams spend 20 to 30 percent of their time on manual reporting. That is one day a week spent moving numbers between tools instead of deciding what to do with them. For a team of five, that is a full person-year of reporting time lost every year.

What you will need

Step 1: Set up Google Analytics data export

Step 1

Set up Google Analytics data export

GA4 provides a Data API that gives programmatic access to your reporting data. This is what Make uses to pull the numbers into your report. You need a Google Cloud project with the Analytics API enabled, and a service account with access to your GA4 property.

In the Google Cloud Console, create a service account, download the JSON key, and add the service account email as a viewer on your GA4 property. This gives Make permission to query the Data API on your behalf.

The GA4 Data API documentation covers the full set of dimensions and metrics available. For social campaign reporting, you typically need dimensions like sessionSource, sessionMedium, campaignName, and metrics like sessions, engagedSessions, conversions, and totalRevenue.

Step 2: Connect GA4 to Make for automated data pull

Step 2

Connect GA4 to Make for automated data pull

In Make, add the Google Analytics module and select Run Report. Configure it with your property ID, the date range (yesterday or the last seven days), and the dimensions and metrics you want.

Set the module to return data grouped by campaign name and source or medium. This gives you a row per campaign showing sessions, engaged sessions, conversions, and revenue. For the attribution-focused use case, add the firstUserSource or sessionSource dimension depending on which attribution model you use.

Add a filter to exclude internal traffic. You do not want your own team's visits inflating the numbers. GA4 has a built-in internal traffic filter; Make can apply an additional filter for known internal IP ranges.

The Make Google Analytics module documentation explains the exact parameter format for the Run Report module, including how to specify date ranges and metric expressions.

Step 3: Build the Airtable reporting base

Step 3

Build the Airtable reporting base

Airtable hosts the report. Create a new base with three tables:

  • Campaigns — one row per campaign with fields for campaign name, platform (LinkedIn, Meta, Google), start date, end date, budget, and target KPIs.
  • Daily Metrics — one row per campaign per day. Fields include date, campaign link, sessions, engaged sessions, conversions, revenue, CPA (formula field), and ROAS (formula field).
  • Platform Summary — a rollup table that aggregates daily metrics by platform for the weekly report. Airtable's linked record and rollup fields calculate these automatically.

Airtable's interface feature lets you build a dashboard view on top of these tables. Add chart blocks for spend trends, conversion breakdowns, and platform comparisons. The interface shows the same data your team looks at in the spreadsheet, except it updates itself every morning.

Airtable's reporting templates include pre-built dashboard designs you can duplicate and customise.

Step 4: Schedule daily report updates

Step 4

Schedule daily report updates

Configure Make to run the scenario every morning at 8am. The scheduler in Make lets you set the exact time and timezone. When it triggers, Make:

  1. Pulls yesterday's data from GA4 via the Run Report module.
  2. Transforms the response into records that match your Airtable table structure.
  3. Creates or updates records in the Daily Metrics table using Make's Airtable module.
  4. Optionally sends a Slack message to your marketing channel: "Daily report ready. 47 new sessions from LinkedIn yesterday, 12 conversions from Meta."

The Airtable module in Make supports upsert behaviour: if a record for yesterday already exists (because you ran the workflow midday and it captured partial data), it updates instead of creating a duplicate. This is important for running the workflow multiple times without cluttering the base.

Make's Airtable module documentation covers the create, update, search, and upsert operations.

The live attribution analysis in our attribution pipeline guide and the unified ad attribution post cover how to extend this reporting base with multi-platform attribution logic once the Airtable foundation is in place.

What changes when reporting runs itself

Once this workflow is running, Monday morning looks different. Instead of opening three dashboards and cross-referencing numbers, your team opens the Airtable interface. The data is already there, populated at 8am before anyone arrived. The numbers from GA4 are aligned: the same date range, the same metric definitions, the same attribution model.

The time that used to go into compiling the report goes into reading it. Which campaigns are underperforming? Where is the CPA creeping up? Which platform drove the highest-value conversions yesterday? The team discusses the meaning of the numbers instead of arguing about whose data is correct.

This reporting foundation also scales. Once Airtable is the central repository, you can add data from LinkedIn Ads and Meta Ads through the same Make workflow. The Make Google Analytics module handles the GA4 side, and parallel modules handle the ad platform APIs. The Airtable base stays the same. The team's reporting process stays the same. Only the data volume grows.

Frequently asked questions

Which GA4 metrics are most useful for social campaign reporting?

The most common metrics are sessions, engaged sessions, event count, conversions, total revenue, and source or medium. Add campaign name and social network dimensions for breakdown.

Can I add data from LinkedIn and Meta too?

Yes. Make has modules for LinkedIn Ads and Meta Ads. You can add parallel data pulls for each platform and merge them into the same Airtable base.

Does this replace Google's built-in reports?

No. GA4's built-in reports remain the source of truth. This workflow copies the data you need into Airtable so your team can see everything in one place without navigating three different UIs.

How much does the setup cost?

Airtable's free tier supports the base structure. Make's free tier handles 1,000 operations a month. GA4 is free. Total cost is under AUD 30 per month.

How often does the data update?

Once a day by default. You can configure Make to run every 6 hours if you need intraday updates for active campaigns.