Google Ads Deleting Historical Data: What Advertisers Must Do Now
Understanding Google’s New Data Retention Policy for Advertisers
Google Ads is rolling out a formal data retention policy that fundamentally changes how long advertisers can access historical performance records within the platform. Starting June 1st, granular reporting data — including hourly, daily, and weekly breakdowns — will only be retained for 37 months. Once that window closes, the data disappears permanently from both the Google Ads interface and its APIs. Monthly, quarterly, and annual summaries receive a much longer shelf life of 11 years, but the granular data most useful for day-to-day optimization and trend analysis will face tighter cutoffs. Reach and frequency metrics face the strictest limits of all, with unique user counts, average impression frequency per user, 7-day and 30-day frequency averages, and full frequency distribution data only accessible for three years. For many advertisers, this policy change may come as a surprise since historically Google Ads stored performance data indefinitely. Understanding the distinction between retention windows — 3 years for frequency metrics, 37 months for sub-monthly data, and 11 years for aggregated monthly reports — is the critical first step before building any response strategy. This is not a gradual phase-out; it is a hard deletion deadline that requires proactive planning well before 2026.
Why This Change Creates Real Risks for Long-Term Campaign Analysis
The implications of this policy extend far beyond routine reporting. Advertisers, agencies, and in-house analytics teams that rely on multi-year historical datasets for media mix modeling, competitive benchmarking, or seasonal trend forecasting are the most exposed. Granular sub-monthly data powers many sophisticated analytical workflows — identifying micro-trends in hourly performance, tracking weekly budget pacing patterns, and evaluating the incremental impact of creative refreshes over time. Losing access to this data retroactively could create gaps in attribution models and undermine the accuracy of year-over-year comparisons. Reach and frequency metrics losing accessibility after just three years poses a specific challenge for brand awareness campaigns, where understanding cumulative audience exposure patterns over time is essential for planning. Teams using AI tools integration within their analytics stacks — connecting Google Ads data to machine learning forecasting models or automated dashboard systems — must audit their data pipelines immediately to ensure historical pulls are captured before expiration. Agencies managing large portfolios of client accounts face an amplified version of this risk, since each account’s historical data must be independently preserved. Without proactive action, organizations could find themselves making future strategic decisions with an incomplete view of their own performance history, reducing the competitive advantage that deep historical analysis provides.
Practical Steps to Protect Your Google Ads Historical Data Before It’s Gone
The most important immediate action is to audit how far back your current Google Ads reporting data goes and prioritize exporting anything beyond the upcoming retention windows. Use the Google Ads API or built-in reporting exports to pull granular daily and hourly data, frequency metrics, and any custom segments that fall within the three-year or 37-month risk zones. Storing this data in a dedicated warehouse solution — whether that is BigQuery, Amazon Redshift, or a simpler structured cloud storage setup — ensures long-term accessibility independent of Google’s platform decisions. Implementing automated export pipelines is strongly recommended rather than relying on manual downloads, which are easy to forget and difficult to scale across multiple accounts. Tools leveraging AI tools integration can help schedule recurring data pulls and flag anomalies or gaps in coverage. An Auto Backlinks Builder tool analogy applies here conceptually: just as building backlinks systematically compounds SEO value over time, systematically archiving ad performance data compounds your analytical edge. Connect exported data to your existing BI dashboards to maintain reporting continuity. Document retention schedules internally so teams are aligned on what data exists, where it lives, and for how long. Acting before mid-2025 gives your organization a comfortable buffer to verify data completeness before the June 2026 deletion window begins taking effect.
Source: Google Ads will start deleting historical reporting data after set retention periods
