Sync your Google Ads campaign data directly into PostgreSQL for deep analysis, custom reporting, and automated budget decisions.
Store all campaign metrics in your own PostgreSQL database for full control.
Query spend, clicks, and conversions with custom SQL on your schedule.
Trigger budget adjustments based on database-side performance thresholds.
Log daily Google Ads metrics into PostgreSQL tables for long-term trend analysis and auditing.
Join ad click data with your own conversion tables to build proprietary attribution models.
Query spend-to-conversion ratios and trigger alerts when campaigns exceed target CPA thresholds.
Aggregate data from multiple Google Ads accounts into unified PostgreSQL views.
Store keyword-level bid, impression, and click data to optimize bids over rolling time windows.
Record ad creative performance metrics in structured tables to compare variants statistically.
Authorize Google Ads and provide your PostgreSQL connection credentials.
Describe which campaigns, metrics, and time ranges to sync.
Execute the first sync immediately, then schedule recurring runs.
| Google Ads Action | PostgreSQL Action | Use Case |
|---|---|---|
| Campaign metrics export | Insert into tables | Performance archiving |
| Keyword stats retrieval | Store in keyword schema | Bid optimization |
| Conversion event export | Join with CRM tables | Attribution modeling |
| Daily spend totals | Query against thresholds | Budget alerts |
| Creative performance fetch | Aggregate in analysis table | A/B testing |
| MCC child account access | Unify in single schema | Multi-account reporting |
Google Ads provides powerful campaign management, but its native reporting has limits. PostgreSQL removes every one of those constraints by letting you own the data entirely.
Neotask handles the orchestration without you writing ETL code. You describe what data you want and how often to sync it. The agent pulls reports, transforms the data, and inserts rows into your target tables.
Once Google Ads data lives in PostgreSQL, your entire data ecosystem can reference it. Metabase, Tableau, Redash, and similar tools connect directly.
Tell Neotask which account to connect, point it at your PostgreSQL host, and describe the tables you want populated.
Use incremental syncing by filtering on the date field to avoid re-fetching historical data.
Create indexed columns on campaign_id and date in PostgreSQL to keep queries fast.
Store raw API responses in a staging table first, then transform into your clean schema.
Yes. You can connect multiple accounts and route all data into a single schema with account-level identifiers.
Neotask manages pagination and rate limit backoff automatically.
Yes. Neotask will structure inserts to match your existing tables or suggest a schema if starting fresh.
Yes. You can instruct Neotask to query your database for underperforming campaigns and apply changes in Google Ads.
Stop exporting CSVs. Let Neotask automate your Google Ads to PostgreSQL pipeline.
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