How to connect Looker Studio to Google Ads (and report on it well)

Open the data source list in your Google Ads UI. If you see 'Switch account' with multiple options in the dropdown, you're inside an MCC structure.

For a single-account business: connect to the sub-account directly. Simplest path, easiest to reconcile.

For an MCC with 2-5 accounts you want aggregated: connect to the MCC level. Charts will show totals across all sub-accounts by default; you can filter to one sub-account with a dropdown control.

For an MCC with 6+ accounts where most reports are per-account: connect each sub-account as a separate data source. More setup work, but cleaner per-account reporting.

Document your choice. The Resource → Manage added data sources panel should clearly name each source ('Google Ads — Acme MCC' vs 'Google Ads — Acme Brand SubAccount').

In Looker Studio: Create → Data source. Search "Google Ads" in the connector gallery.

Click the Google-authored "Google Ads" connector. Authorize access — Looker Studio will need read access to the ad account.

On the account picker, you'll see all accounts (and MCC structures) your Google login has access to. Pick the level you decided on in step 1.

Click Connect (top-right). Looker Studio loads the field schema — typically 300+ fields for Google Ads.

Rename the data source immediately: "Google Ads — [Account Name]". This is the moment future-you will thank present-you.

In the field schema view, scroll to conversion-related fields. The main four: Conversions, Conversion value, All conversions, Cost / conv.

'Conversions' counts only the conversion actions marked as 'primary' in Google Ads (the ones bid strategies optimize toward). 'All conversions' counts every action including secondary.

For most marketing dashboards, report 'Conversions' (matches what Smart Bidding sees) and 'Cost / conv.' Report 'Conversion value' if you have e-commerce or revenue-based goals.

Hide fields you don't use. The unused 'View-through conversions' or 'Cross-device conversions' add schema noise.

Add a calculated field 'ROAS' = Conversion value / Cost (see tutorial 6 for calculated field setup). Save this once at the source level so every chart can use it.

Page 1 — Overview. Add scorecards for: Cost, Conversions, Cost / conv, Clicks, CTR, Conv. rate. Add a time series for Cost + Conversions (dual axis). Add a Date range control. This is the page leadership will look at.

Page 2 — Campaign Performance. Add a table with: Campaign name, Cost, Clicks, Impressions, CTR, Conversions, Cost / conv, ROAS (if calculated). Sort by Cost descending. This is where you spot underperformers.

Page 3 — Search Terms / Insights. Add a table with: Search query, Match type, Cost, Conversions. Sort by Cost descending. This is where you find negative keyword candidates.

Add a Campaign filter (Insert → Drop-down list, Dimension = Campaign name) at the page level on Page 2 and Page 3. Lets viewers drill into a single campaign quickly.

Add a chart-level filter on every chart on Page 1 to exclude 'Removed' campaigns: Add filter → Campaign status → Include → Enabled, Paused.

Open Google Ads in a separate tab. Set date range to Last 28 days. Note: Cost, Clicks, Impressions, Conversions at the account level (top of the page).

In Looker Studio, the Overview page scorecards should match those numbers within 1-2%. Tiny drift is normal due to data refresh timing.

If Cost is off by more than 2%, the most common cause is including/excluding removed campaigns differently between the two views. Apply the same filter to both.

If Conversions is off by more than 2%, check whether the data source is summing "Conversions" vs "All conversions" — the gap is often that misalignment.

Document reconciliation on the dashboard itself — add a small text note: "Data refreshed every 12 hours. Reconciled against Google Ads UI on [date]." Builds trust with viewers.

If you connected at MCC level: add a drop-down list (Insert → Drop-down list) with Dimension = Account name. Now viewers can filter to one sub-account, see all, or compare two.

If you connected each sub-account separately: build one report per account, then create a master "Hub" report with links to each. This is the path for 5+ accounts.

For consolidated cross-account views with custom logic (e.g., weighting conversions differently per account), you'll need data blending (see tutorial 5) or BigQuery as a staging layer.

Never aggregate accounts manually via copy-paste. The dashboard exists to eliminate that work.

Click File → Schedule email delivery.

Add recipients (email addresses). Pick frequency — Weekly on Mondays is the most common cadence for ad reporting.

Pick pages to include. Usually Overview only is enough for execs; Marketing leads want all three pages.

Schedule the first delivery for 2-3 days out so you can review the first PDF before stakeholders see it.

Once delivered, monitor: are stakeholders opening it? Asking questions? Acting on it? If the PDF is unread for 4 weeks straight, restructure the dashboard.