One of the most common ways advertisers waste money is not by overspending but by managing campaigns too aggressively. Too often, ads are scaled or cut based on sample sizes so small they have no real meaning. One click on five impressions may technically equal a 20% CTR, but that is not a signal worth acting on. In 2025, the most effective media buyers are the ones who know when to take action and when to step back.
1. What’s the Minimum Sample Size?
Industry best practices and Meta’s own guidance provide clear thresholds before performance data becomes reliable:
Impressions: At least 500–1,000 impressions per ad before CTR or CPC comparisons are useful.
Clicks: Around 50–100 clicks are needed before drawing directional insights about engagement or traffic quality.
Conversions: Meta recommends roughly 50 conversions per week per ad set for the algorithm to optimize effectively.
Anything smaller is unstable. A single click can double or halve your CTR. That is not actionable insight; it is variance.
2. Then vs. Now: The Evolution of Optimization
In the early years of Facebook advertising, the standard approach was to cut underperformers quickly and scale “winners” the moment they looked promising. Manual intervention was required to see results. Today, the environment has changed:
Meta’s algorithm identifies performance patterns more quickly and more accurately than a human media buyer.
Optimization happens at the campaign and ad set level, which means turning ads off too early can work against the system.
Frequent changes, such as pausing or editing, restart the learning phase and slow down progress.
The role of a modern media buyer is not to second-guess the algorithm, but to provide it with quality data and enough room to optimize effectively.
3. Applying Statistical Significance
When comparing ads, the real question is whether differences in performance are meaningful or simply the result of chance.
Confidence Level: In most digital marketing tests, the goal is 95% confidence. That means being 95% sure that the observed result is not random.
Sample Size: To reach that confidence level with CTR or CVR, dozens or even hundreds of clicks or conversions per variant are often required.
Margin of Error: With too few samples, the margin of error can be so wide that the numbers lose all practical value. A 20% CTR on five impressions could easily carry a margin of error of plus or minus 40 percentage points.
If you do not have enough data to calculate statistical significance, you do not have enough data to optimize.
4. Best Practices for Smarter Decision-Making
Budget for meaningful results. Campaigns aimed at conversions should be funded to achieve about 50 conversions per ad set per week. Minimal daily spend will not provide enough data.
Wait before making changes. Allow campaigns to run for at least 5–7 days to let volatility smooth out and to give the algorithm a chance to stabilize.
Use calculators when testing. Free tools, such as Evan Miller’s A/B Test Calculator, can quickly determine whether performance differences are statistically significant.
Prioritize big levers. Offer, audience, and creative strategy have a greater impact than making constant micro-adjustments to individual ads.
The Bottom Line
Many advertisers shut down ads after just a handful of impressions or rush to scale after one lucky click. These decisions reflect impatience rather than strategy. The true advantage now comes from knowing when to let campaigns run, when to trust Meta’s learning system, and when to act only once results are statistically reliable. Patience consistently outperforms panic, and ads that are given room to breathe almost always deliver stronger outcomes than those cut off too early.