Automation Recipe: Sync Your Placement Exclusions Across Tools—Google Ads, DV360 and Your CRM

Stop chasing exclusions across platforms — keep one list synchronized, enforced and auditable

Pain point: Ad ops teams waste hours re-entering placement blocks across Google Ads, DV360 and internal CRMs — then discover mismatches during a campaign run. You need a single, trusted exclusion list that updates everywhere in real time.

What this recipe delivers (the short version)

This workflow recipe shows a practical, production-ready way to sync placement exclusions across Google Ads (now with account-level exclusions), Display & Video 360 (DV360), and your CRM suppression lists using a single source of truth, plus implementation options for both no-code teams (Zapier/Make) and engineering teams (serverless connectors + scripts).

"Google Ads now supports account-level placement exclusions (Jan 2026). Use that to simplify enforcement — and automate the rest."

Why this matters in 2026

In 2026 ad platforms are more automated and privacy-constrained than ever. Google’s Jan 2026 rollout of account-level placement exclusions lets advertisers apply one block list across Performance Max, Demand Gen, YouTube and Display. That reduces campaign-level drift, but it doesn’t solve cross-platform sync — DV360 and your internal suppression lists still need to match.

Modern programmatic ecosystems expect automation. Brands that keep exclusion lists human-managed will face wasted spend, brand-safety incidents, and audit gaps. This recipe converts a single list into platform actions with traceability, error handling and reconciliation.

Architecture overview — single source of truth + connectors

Best practice: build a simple architecture with three layers:

1. Source of Truth (editable by ops/comms): Airtable, Google Sheet, or an internal DB table labeled exclusions_master.
2. Sync Middleware (automated): Cloud Function/Cloud Run or a no-code automation platform (Zapier/Make) that normalizes, diffs and sends updates to endpoints.
3. Target Connectors: Google Ads (account-level exclusions), DV360 (advertiser-level negative sites/apps list), CRM (suppression flags or suppression-list object).

Why this layout?

• Clear edit rights on the source (legal/brand teams).
• Business logic and error handling consolidated in one place.
• Traceable, auditable sync logs and reconciliation.

Choose your Source of Truth (pick one)

Pick based on team skillset and scale:

• Airtable — great UI, built-in API, good for mid-size teams.
• Google Sheets — easiest to adopt, Zapier/Make native triggers, manual-friendly.
• Postgres / BigQuery — best for enterprise scale and auditability.

Connector options — No-code to code

Two supported implementation tracks:

1. No-code / Low-code: Zapier or Make for teams without dev resources.
2. Serverless / Custom: Cloud Run or Lambda for teams that need scale, robust error handling and security.

No-code recipe: Zapier (fast, low-maintenance)

Use this when legal/brand owners will edit the list and ops want a fast deployment.

Zap steps (example using Airtable as source)

1. Trigger: Airtable - New or Updated Record in exclusions_master.
2. Action: Formatter - Normalize the domain/placement entry (strip http(s), lowercase, remove paths).
3. Action: Webhooks - POST to Google Ads sync endpoint (cloud function or Zapier’s built-in Google Ads action if available).
4. Action: Webhooks - POST to DV360 sync endpoint (Display & Video 360 API via webhook; include OAuth token stored in Zapier).
5. Action: HubSpot/Salesforce - Update suppression_list or do_not_contact field.
6. Action: Gmail/Slack - Send a digest to the ad-ops channel with operation result.

Notes:

• Zapier supports OAuth2 for many services. For DV360, you may need to use the Webhooks (Custom Request) action and a stored service account token.
• Use Zapier storage for rate-limit backoff counters if you need retries.

No-code recipe: Make (for visual flows & batching)

Make (Integromat) is better when you need batching and advanced transformations.

Make Scenario

1. Google Sheets / Airtable Watch Records module triggers every 5 minutes.
2. Iterator normalizes inputs; filters remove duplicates or already-synced entries.
3. HTTP module: batch request to internal Cloud Function to upsert 50 exclusions at once to Google Ads (reduce API calls).
4. HTTP module: call DV360 batch endpoint via service account OAuth.
5. CRM module: Update suppression object in bulk.
6. Logger module: write results back to a Google Sheet or DataDog for audit.

Serverless recipe: reliable, auditable, scalable

For scale and security build a small sync service. Use Cloud Run (GCP) or AWS Fargate + a cron/AWS EventBridge trigger.

High-level flow

1. Webhook or scheduled job reads exclusions_master and computes a diff vs last-synced snapshot.
2. Normalize and dedupe entries (domains, app IDs, placement IDs).
3. Batch upserts to Google Ads API (account-level placements endpoint).
4. Batch upserts to DV360 Inventory/Negative Sites shared list.
5. Patch CRM suppression records via CRM API.
6. Persist success/failure & create retry queue for failures.

Example Node.js pseudo-code (serverless)

// Pseudo-code: batch upsert to Google Ads and DV360
const rows = await fetchSourceRows();
const normalized = normalize(rows);
const diff = computeDiff(normalized, lastSnapshot);
await upsertGoogleAds(diff.adds, oauthTokenGA);
await upsertDV360(diff.adds, oauthTokenDV);
await updateCRM(diff.adds, crmToken);
saveSnapshot(normalized);

Tips:

• Use incremental snapshots (ETag or timestamp) to avoid reprocessing unchanged rows.
• Respect API rate limits. Batch into sizes recommended by each API — typically 50–200 items per request.
• Store operation IDs so you can match asynchronous job responses back to the source entry.

How to call each platform (practical specifics)

Google Ads (2026 update: account-level placement exclusions)

Use the Google Ads API to manage account-level placement exclusions — centralizing enforcement across Performance Max, Display, YouTube and Demand Gen. If you don't have engineering resources, the Google Ads UI now supports a shared account-level exclusion list you can update via CSV import.

Programmatic approach:

• Authenticate with OAuth2 or service account via OAuth2 service flow.
• Use the Customer-level negative placement resource (Customer Negative Placement endpoint) to upsert domains and placement IDs.
• Batch changes and verify with the API’s response. On 2026 platforms, Google returns per-item status in batch upsert calls.

DV360

DV360 still manages negative sites at the advertiser or company level. The Display & Video 360 API supports updating shared lists of negative sites and apps for an advertiser.

• Authenticate using a Google service account with DV360 access.
• PUT or PATCH the advertiser’s negative sites list with the normalized list. Use batch operations where possible.
• DV360 may accept both domains and app bundle IDs — normalize both types separately.

CRM (HubSpot or Salesforce)

For CRM suppression, either:

• Create/update a suppression_list custom object and attach domains or customer identifiers; or
• Set do_not_contact flags on contacts/accounts if the placement is tied to a known domain owner.

Normalization rules (always do this first)

Common cause of drift is inconsistent formatting. Normalize every entry before sending:

• Lowercase hostnames; strip protocol and path (keep domain and effective TLD+1).
• For YouTube channels/placement IDs, map channel IDs to canonical placement IDs.
• Split mobile app bundle IDs vs. web domains; treat separately.
• Remove wildcards or unsupported patterns that target systems don’t accept; map to closest valid form.

Conflict resolution & dedupe logic

Rule-based conflict handling keeps lists deterministic. Recommended precedence:

1. Manual 'block' entries from Legal/Brand (highest priority).
2. Automated signals (fraud detection tools).
3. Historical campaign-level blocks (lowest priority).

If an entry is removed in the master list, the middleware should soft-delete in targets (mark as archived) rather than immediate hard delete. That preserves an audit trail and reduces risk.

Rate limits, batching and retry strategy

APIs throttle. Protect your sync:

• Batch writes: group by 50–200 items depending on API recommendations.
• Exponential backoff for 429s and 5xx responses.
• Use a retry queue so failed items are retried without reprocessing successful items.

Monitoring, reconciliation and auditing

Monitoring matters more than the initial sync. Implement:

• Sync logs with per-item status and timestamps stored in BigQuery or a log store.
• Daily reconciliation job that reads the target platform lists and compares them to the master source; report diffs to Slack/email.
• Alert on omissions and API errors above a threshold.

Sample reconciliation check (pseudo-SQL)

-- Items in master not in Google Ads
SELECT m.domain
FROM master_exclusions m
LEFT JOIN google_ads_exclusions g ON m.domain = g.domain
WHERE g.domain IS NULL;

Security & permissions

• Use least-privilege service accounts for APIs (scoped tokens for Google Ads & DV360).
• Rotate credentials and keep them in a secrets manager (GCP Secret Manager, AWS Secrets Manager).
• Enable audit logs for changes in the source of truth and for API operations.

Testing & rollout checklist

1. Run in a staging advertiser/Google Ads test account first.
2. Dry-run mode: generate diffs and send only to Slack without applying changes.
3. Apply to a limited advertiser subset (canary) and monitor carefully for 24–72 hours.
4. Gradually scale to all advertisers once stable.

Zapier & Make recipe examples (copy/paste friendly)

Zapier (Airtable & Google Ads)

1. Airtable: New/Updated Record trigger.
2. Formatter: Extract domain: use Regex to remove protocol (https?://) and paths.
3. Webhooks: POST JSON to your Cloud Function endpoint /sync, body:

   {
     "action": "upsert",
     "domain": "{{Formatter_output}}",
     "source": "airtable:brand-team"
   }
   

4. Cloud Function returns per-target status; Zap logs and posts success/failure to Slack.

Make (Google Sheets & DV360 + Google Ads)

1. Google Sheets: Watch rows module (poll every 5 minutes).
2. Aggregator: collect up to 100 rows per run.
3. Router: dedupe and separate by type (web domain, app bundle, youtube).
4. HTTP: call DV360 batch update endpoint with OAuth2 token (service account).
5. HTTP: call Google Ads account-level upsert endpoint.
6. Logger: append results to an audit sheet and send a Slack summary.

Common pitfalls and how to avoid them

• Mixing formats — always normalize (domains vs. full URLs vs. placement IDs).
• Not honoring platform-specific constraints — run tests to confirm the platform accepts your format.
• Lack of soft-delete policy — prefer archiving in targets to allow rollback.
• Not reconciling — daily reconciliation uncovers drift before it costs ad spend.

Real-world example (case study)

One mid-market ecommerce client in late 2025 consolidated legal and ops blocks into an Airtable master list and ran a Make scenario to sync to Google Ads and DV360. Within two weeks:

• Blocked placements decreased mismatches by 92%.
• Manual time spent on synchronization dropped from 8 hours/week to 40 minutes/week (mostly monitoring).
• Brand-safety incidents tied to unwanted placements dropped to zero in the monitored period.

Future-proofing & 2026 trends

Expect these developments through 2026–2027:

• More ad platforms will expose account/advertiser-level exclusion APIs (Google led in Jan 2026).
• Standardization of negative lists across programmatic supply chains will improve (shared negative list standards).
• Privacy-first signals and contextual targeting will make brand-safe exclusion lists more important — you'll need to sync lists with contextual providers and consent-management platforms.

Quick checklist to ship this in 2 weeks

1. Pick a source of truth (Airtable or Google Sheets). Add fields: domain, type, reason, owner, status.
2. Create a Zapier or Make scenario that triggers on new/updated rows and normalizes entries.
3. Wire Zapier/Make to call a small Cloud Function that upserts to Google Ads and DV360 (start with Google Ads only if you must lower scope).
4. Add CRM update action in Zapier/Make and a Slack digest for failures.
5. Run canary on a single advertiser/campaign for 72 hours and reconcile daily.

Wrapping up — what you can do this afternoon

If you have 60 minutes right now, do this:

1. Create the master sheet with canonical columns.
2. Set up a Zap that sends newly added rows to a Slack channel (quick visibility).
3. Open a staging Google Ads account and try a manual account-level exclusion to understand the shape required.

Final takeaways

In 2026, centralized, automated exclusion syncs are low-hanging fruit for reducing wasted ad spend and brand-safety risk. Use a single source of truth, normalize entries, batch operations, and instrument reconciliation. Whether you choose Zapier/Make for speed or a serverless connector for scale, this workflow will save time and create auditability across Google Ads, DV360 and your CRM.

Ready to implement? If you want a starter repo, a tested Cloud Function template, or a Make scenario copy we use with mid-market teams, request the quicks.pro automation bundle and we’ll send the scripts and recipes that match your stack.

Related Reading

• Integrating CRM Customer Data into Quant Models: Use Cases and Pitfalls
• Retailer Tie-Ins & Unlock Codes: Best Practices from Nintendo Crossovers
• How to Spot Loan Applications Sourced From Deepfakes or AI-Generated Documents
• Workshop Plan: Teach a Small-Batch Syrup Making Class for Aspiring Bartenders
• Micro-Retreats in Mountain Towns: Planning a Relaxing Long Weekend in Whitefish or the Drakensberg