You check your Facebook Ads Manager at 9 a.m. and see $247 spent with 18 conversions. You open Google Ads in the next tab: $198 spent, 22 conversions. LinkedIn shows $310 spent, 11 conversions. You drop the numbers into a spreadsheet to calculate blended cost-per-acquisition, then check again two hours later. Facebook hasn’t moved. Google added three conversions. LinkedIn subtracted one.
Welcome to the reality of paid social dashboards: every platform updates metrics on its own schedule, and none of them tell you when the last refresh happened.
Why update intervals matter
Most operators treat ad dashboards like bank balances—refresh the page, get the current number. But ad platforms process billions of events across millions of campaigns. They batch updates, prioritize certain metrics over others, and apply attribution windows that shift as more data arrives.
Facebook Ads Manager typically updates spend and impression data every 15 to 30 minutes during active campaign hours. Conversion data can lag by one to four hours, especially if you’re using the Conversions API or tracking offline events. If you’re running campaigns across multiple time zones, the dashboard may show blended data from different collection windows.
Google Ads refreshes most metrics every three hours for standard campaigns. Search campaigns update faster—often within 60 minutes—because query data arrives in near-real-time. Display and YouTube campaigns batch less frequently. Conversion imports from Google Analytics 4 can take six to twelve hours to appear, and the attribution window keeps adjusting for up to 90 days if you allow data-driven attribution.
LinkedIn Campaign Manager updates impressions and clicks roughly every two to four hours. Lead gen form fills appear faster, usually within 30 minutes, because LinkedIn processes them as first-party events. Conversion tracking via the Insight Tag can delay by four to eight hours depending on pixel fire volume and whether you’ve enabled enhanced conversions.
When stale data breaks decisions
The update lag becomes a problem when you’re making budget decisions across platforms in the same session. If Facebook shows yesterday’s conversion total but Google reflects this morning’s, your cost-per-acquisition comparison is measuring different time windows. You might pause a LinkedIn campaign that looks expensive at 11 a.m., only to see five conversions arrive by 3 p.m. that would have changed the math.
One operator I spoke with pulls reporting at the same time every day—8 a.m. Eastern—and assumes all platforms are showing data through midnight. He realized Facebook was still processing West Coast conversions from 9 p.m. to midnight, so his morning snapshots undercounted by 12 to 18 percent. He shifted his reporting pull to 10 a.m. and saw the discrepancy drop to under 5 percent.
The other trap: platforms don’t update all metrics simultaneously. Facebook might refresh spend in real time but hold conversion data for the next batch cycle. If you calculate return on ad spend while spend is current but conversions are three hours old, you’re blending live and lagged numbers.
How to work around dashboard lag
Set a consistent daily reporting time at least four hours after your highest-traffic period ends. If most conversions happen between 6 p.m. and 10 p.m., pull reports after 2 p.m. the next day. That gives every platform time to process overnight events and apply attribution.
Use each platform’s bulk export or API for anything you’re putting into a spreadsheet. Exports often pull from a more complete dataset than the live dashboard. Facebook’s Ads Reporting API lets you specify a date range and attribution window; the response includes a data freshness timestamp so you know exactly when the numbers were last calculated.
When comparing platforms, add a staleness column. Mark which metrics updated in the last hour, the last four hours, or earlier. If LinkedIn conversion data is eight hours old and Facebook’s is two hours old, flag the comparison and revisit it later rather than making a budget shift on mismatched windows.
For operators running high-frequency tests—creative swaps, bid adjustments, audience shifts—check the platform’s API documentation for real-time vs. batched endpoints. Google Ads has a real-time reporting service for search campaigns that updates every few minutes, but it costs more in API quota. Facebook offers a similar accelerated delivery insight, though it’s not exposed in the standard dashboard.
When to trust the dashboard and when to wait
Spend data is almost always current within 30 minutes across all three platforms. Impressions and clicks update faster than conversions. If you need a quick pulse check on whether a campaign is delivering traffic, the dashboard is reliable. If you’re calculating return on ad spend or cost per lead, wait until the conversion window closes.
One pattern I’ve seen work: check dashboards for pacing and delivery in the morning, but reserve budget and optimization decisions for end-of-day when conversion data has caught up. If a campaign looks like it’s burning budget without results at 10 a.m., tag it for review but don’t pause it until 5 p.m. unless spend is wildly over target.
Platforms won’t fix this. Real-time everything is expensive to build and even more expensive to scale. The update intervals we have now are design choices that balance infrastructure cost against operator needs. Understanding the lag is part of the job.
What’s your reporting routine? Do you pull data at the same time daily, or do you check dashboards ad hoc? Hit reply and let me know—I’m collecting operator workflows for a future piece on attribution reconciliation.