Google Ads will restrict access to granular reporting data to a strict 37-month rolling window starting June 1, 2026. This policy update actively replaces the 11-year data retention window previously established in November 2024. The 37-month limitation explicitly enforces data deletion across the Google Ads API, Google Ads scripts, the Google Analytics Data API, and the BigQuery Data Transfer Service.
How the 37-Month Limit Impacts Granular Google Ads Data
Daily, hourly, and weekly performance metrics older than 37 months will be permanently blocked from access starting June 1, 2026. Advertisers utilizing this granular data for long-term trend forecasting or deep year-over-year algorithmic comparisons must export their historical logs immediately. High-level metric aggregations grouped by monthly, quarterly, and yearly segments will remain fully accessible for the original 11-year retention lifespan.
Google's official May 1, 2026 Help Center update confirms that any granular reporting data collected beyond the 37-month threshold will be completely inaccessible via both the user interface and all APIs. Specific measurement metrics tied strictly to reach and frequency forecasting will face a tighter, 36-month (three-year) retention restriction.
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Google Ads API and BigQuery System Requirement Changes
Requesting granular data segments like "segments.date" or "segments.week" for dates older than 37 months via the Google Ads API will instantly trigger a DateRangeError.INVALID_DATE failure code beginning June 1, 2026. Nadine Wang from the Advertising and Measurement APIs Team explicitly noted that subsequent API version releases will replace this with a highly specific DateRangeError.REQUESTED_DATE_GRANULARITY_NOT_SUPPORTED error code to clarify the exact compliance failure.
Developers must immediately reconfigure legacy API queries to utilize broader segments, specifically "segments.month", "segments.quarter", or "segments.year", to retrieve any data exceeding the 37-month cutoff. Unsegmented historical data queries must flawlessly align with exact calendar month boundaries to prevent API rejection. Engineering teams and advertising agencies bear the sole responsibility for auditing their data pipelines to prevent catastrophic reporting crashes.
The Google Analytics Data API will silently truncate queries containing the "date" dimension for ad cost, clicks, and impressions down to exactly 36 months without generating a failure code. Data integration teams blending datasets from both the Google Ads API (which throws a hard error) and the Google Analytics Data API (which silently filters data) must execute strict reconciliation protocols to prevent undetected reporting gaps.
The BigQuery Data Transfer Service will permanently block backfill runs for Search Ads 360 and Google Ads connectors for any date older than 37 months starting June 1, 2026. Google Analytics 4 (GA4) administrators must exercise extreme caution; executing a manual backfill for data exceeding the 37-month limit will actively overwrite and delete existing historical BigQuery records by replacing them with empty null values.
Why Google is Enforcing the 37-Month Retention Limit
Reversing the 11-year data retention policy introduced in November 2024 perfectly aligns Google Ads with identical 37-month granular data caps currently enforced by competitor platforms like Facebook Ads. This structural standardization severely limits an agency's ability to execute multi-year strategic planning without maintaining an independent, proprietary data warehouse.
Regulatory pressure surrounding global data storage and stringent privacy compliance frameworks is actively driving a massive reduction in data lifecycles across the entire Google ecosystem. Google recently restricted Customer Match retention to a strict 540-day limit in 2025 and slashed historical data limits within Google AdMob.
Mandatory Action Steps for Advertisers Before June 1, 2026
Exporting all required granular historical data into an external database prior to the June 1, 2026 deadline is the sole method to prevent permanent data loss. Google explicitly advises developers managing API integrations and automated bidding scripts to instantly update their application query parameters to guarantee compliance with the impending 37-month truncation.
Data stitching processes reliant on the Google Analytics Data API must be fundamentally rebuilt to accommodate the silent 36-month data truncation limits. Organizations executing complex omnichannel reporting by blending data from multiple Google APIs must meticulously audit their extraction workflows to avoid serving clients incomplete performance dashboards.
Triggering manual BigQuery backfill runs immediately is mandatory for data engineers requiring historical preservation exceeding 37 months. Because complex database backfills require extensive processing time, failing to initiate this sync well in advance of the June 1 cutoff guarantees irreversible data forfeiture.
Timeline of Google's Data Retention Reductions
- November 13, 2024: Google Ads implemented an 11-year data retention policy to support long-term reporting.
- April 7, 2025: Customer Match targeting data retention was strictly limited to 540 days.
- June 2025: Google AdMob permanently reduced its historical data retention window for all mobile publishers.
- May 1, 2026: Google officially announced the upcoming 37-month retention policy for all granular Google Ads data.
- June 1, 2026: The 37-month retention limit officially takes effect across the Google Ads API, Google Ads scripts, and BigQuery integrations.
Final Strategy for the 37-Month Retention Limit
Advertisers must instantly migrate their daily, weekly, and hourly performance data to independent data warehouses to survive this aggressive retention reduction. While high-level monthly, quarterly, and yearly aggregates remain intact for 11 years, losing granular segment data permanently fractures an agency's ability to execute precise day-of-week campaign benchmarking. Surviving the June 1 transition requires overhauling API queries, running immediate BigQuery backfills, and updating automated Google Ads scripts to prevent catastrophic pipeline errors.
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