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Facebook Ads Cost Per Purchase Benchmarks for Public Safety

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Cost Per Purchase for Public Safety

July 2025 - July 2026

Insights

Detailed observation of presented data

Introduction

Public Safety’s cost-per-purchase ran materially above the baseline over this period, with sharp summer peaks and a deep September correction that set the tone for a choppy second half and a modest rebound into early 2026. This analysis is based on $3B worth of advertising data from our dataset, which provides strong directional benchmarks. This analysis explores ad performance trends for Public Safety in All countries available compared to the global benchmark.

The story in the data

Cost per purchase (COST_PER_PURCHASE) for Public Safety averaged about $80.23 across the 10-month window (June 2025–March 2026). Values ranged from a high of $109.83 in June 2025 down to a low of $52.41 in September 2025. The series began at roughly $109.83 and finished at $68.84 — a net decline of about 37% from start to finish.

The month-to-month profile tells the momentum story: modest easing from June to July (−7.1%), a small uptick into August (+5.1%), then a dramatic collapse into September (≈ −51%). September’s trough was followed by the largest single-month rebound (September→October, ≈ +57%). Subsequent months were choppy: October→November (−29.7%), November→December (+49.8%), then a gradual softening into February before a March uptick (+20.9%).

Volatility is a defining feature: absolute monthly swings averaged roughly 28.7% — large moves versus most ad-cost series and noticeably higher than the baseline.

Seasonal and monthly dynamics

The series shows a heavy summer pressure (June–August) with elevated peaks, a sharp correction in September, and a volatile Q4 that alternates between spikes and pullbacks. December remained elevated relative to autumn lows, while early 2026 trade shows settling into mid-range levels with intermittent rebounds. In short, the rhythm is high summer peaks → abrupt September correction → choppy recovery through Q4 → mixed early-Q1 movement.

This pattern aligns with cyclical budget and competitive shifts often visible in paid channels, producing uneven month-to-month momentum rather than a smooth seasonal curve.

Country vs. Global

Against the baseline (global median for the same months ≈ $50.65), Public Safety was generally above market. The average gap was about +58.5% (Public Safety $80.23 vs baseline $50.65). Month-by-month the premium varied: extremely elevated in June (+124%), July (+108%), August (+105%), then nearly convergent in September (−1% vs baseline). From October through March the premium fluctuated between roughly +13% (Feb) and +75% (Dec).

Volatility comparison sharpens the contrast: Public Safety’s average absolute monthly change of ~28.7% versus the global series’ ~4.6% — Public Safety showed roughly six times the month-to-month movement of the baseline. In language familiar to media strategists, the category was “above average” on cost and “more volatile” in pacing than the global benchmark.

Closing

This summary highlights Facebook Ads benchmarks for cost-per-purchase in Public Safety across All countries available, positioning the metric within broader discussions of CPC trends, CPM analysis, and CTR performance as complementary lenses on industry ad performance and country-specific ad costs. Understanding cost-per-purchase benchmarks for Public Safety in All countries available clarifies how conversion costs moved relative to the global market.

Understanding the Data

Insights & analysis of Facebook advertising costs

Facebook advertising costs vary based on many factors including industry, target audience, ad placement, and campaign objectives. In the Public Safety industry, Facebook ad costs can be influenced by seasonal trends and market competition. Geographic targeting affects ad costs based on market competition and user engagement in different regions. Different campaign objectives lead to varying costs based on how Facebook optimizes for your specific goals. The data shown represents median values across multiple campaigns, and individual results may vary based on ad quality, audience targeting, and campaign optimization.

Why we use median instead of average

We use the median CTR because the underlying distribution of click-through rates is highly skewed, with a small share of campaigns achieving extremely high CTRs. These outliers can inflate a simple average, making it less representative of what most advertisers actually experience. By using the median—which sits at the midpoint of all campaigns—we provide a more rigorous and realistic benchmark that reflects the true underlying data model and helps you set attainable performance expectations.

Key Factors Affecting Facebook Ad Costs

  • Competition within your selected industry and audience demographics
  • Ad quality and relevance score – higher quality ads can lower costs
  • Campaign objective and bid strategy
  • Timing and seasonality – costs often increase during holiday periods
  • Ad placement (News Feed, Instagram, Audience Network, etc.)

Note: This data represents industry median values and benchmarks. Your actual costs may vary based on specific targeting, ad creative quality, and campaign optimization.

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The data behind the benchmarks

All data is sourced from over $3B in Facebook ad spend, collected across thousands of ad accounts that use Superads daily to analyze and improve their campaigns. Every data point is fully anonymized and aggregated—no individual advertiser is ever exposed.

This dataset updates frequently as new ad data flows in. It will only get bigger and better.

What's a healthy cost per purchase for ecommerce brands?

It depends on your product price and margins. Most brands aim for $10 to $50. For higher-ticket products, a higher CPA may be acceptable as long as you're maintaining a strong return on ad spend.

How does product price impact CPA benchmarks?

Higher-priced products typically have a higher CPA because people take longer to convert. That's not necessarily a problem if your margin can support it. You should measure CPA in context with AOV and LTV.

Why are my purchase costs going up despite stable ROAS?

Your AOV may be increasing, which helps maintain ROAS even if CPA rises. You could also be facing higher CPMs, lower conversion rates, or creative fatigue.

Should I use manual bidding to control CPA more effectively?

Manual bidding can help if you're struggling to stay within target CPA. It's best used by experienced advertisers who can monitor performance and adjust regularly. It gives more control, but also requires more effort.

How do I scale spend without letting CPA skyrocket?

Increase budget gradually, rotate creative often, and avoid overlapping audiences. Scaling too quickly can lead to audience saturation and rising CPAs.