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Facebook Ads Cost Per Purchase Benchmarks for Public Administration in Germany

See how your purchase costs compare. Explore ecommerce conversion cost benchmarks by industry, region, and campaign type

Cost Per Purchase for Public Administration in Germany

October 2024 - October 2025

Insights

Detailed observation of presented data

  • Scope: This analysis looks at cost-per-purchase trends for industry Public Administration and target country Germany compared to the global trend. The analysis is based on $3B worth of advertising data from our dataset, which provides strong directional benchmarks.
  • Data availability: No in-market observations are available for Public Administration in Germany over the period provided, so relative positioning versus the global baseline cannot be quantified for the selected series.
  • Baseline context: The global median cost-per-purchase averaged 47.82 over the last 12 months, peaking in February (53.89) and bottoming in September (32.29). From October to September, the baseline fell 30.8%.
  • Seasonality: Costs rose into December and remained elevated in Q1, then eased through spring and summer, with a sharp September dip—consistent with holiday-driven Q4 pressure and mid-year softness.
  • Volatility: Average month-to-month change in the baseline was ~7.0% (absolute), or ~4.7% excluding the September outlier.

Scope and dataset

  • Metric: cost-per-purchase (median, monthly)
  • Industry: Public Administration
  • Country: Germany
  • Comparison: selected data (Germany, industry-specific) vs global baseline
  • Note: The selected time series contains no values; therefore, the section below focuses on the global baseline to provide directional benchmarks.

Selected data overview (Germany, Public Administration)

  • Observations: None available in the provided period.
  • Averages, highs, lows, and volatility cannot be computed for the selected series.
  • Interpretation: With no localized observations, the selected series cannot be classified as above market, below average, or in line with overall trends.

Global baseline trend analysis

  • Overall level: Average 47.82 across the last 12 months.
  • High/low:
  • High: 53.89 in February 2025
  • Low: 32.29 in September 2025
  • Change over time: -30.8% from October 2024 (46.67) to September 2025 (32.29).
  • Seasonality:
  • Q4 (Oct–Dec) average: 47.13, with a pronounced December lift (51.53) after a softer November (43.19).
  • Q1 (Jan–Mar) average: 52.94, the highest quarterly level, led by February’s peak.
  • Q2 (Apr–Jun) average: 49.83, gradual easing from early-year highs.
  • Q3 (Jul–Sep) average: 41.39, substantially lower due to September’s dip.
  • Volatility (month-to-month absolute change):
  • Average: ~7.0%; excluding September’s drop, ~4.7%.
  • Notable movements:
  • December vs November: +19.3% jump.
  • June vs May: -7.9% pullback.
  • September vs August: -29.3% sharp decline.

Comparison: selected data vs global baseline

  • Due to the absence of selected data for Public Administration in Germany, a direct comparison (averages, highs/lows, volatility) cannot be made.
  • For context, the global series suggests costs typically increase in Q4 around holiday periods, remain elevated in Q1, then soften into mid-year, with potential late-Q3 dips.

Understanding cost-per-purchase benchmarks on Facebook Ads in industry Public Administration and Germany helps advertisers make more efficient budget and creative choices.

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 Administration industry, Facebook ad costs can be influenced by seasonal trends and market competition. For campaigns targeting Germany, advertisers should consider local market factors and user behavior. 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.

Germany Advertising Landscape

National Holidays

Jan 1New Year's Day
Apr 18Good Friday
Apr 21Easter Monday
May 1Labour Day
May 29Ascension Day
Jun 9Whit Monday
Oct 3German Unity Day
Dec 25Christmas Day
Dec 26Boxing Day

Key Shopping Season

Late November (Black Friday/Cyber Monday), Christmas shopping (late December), Back-to-school (August/September), Spring promotions (Easter period)

Potential Advertising Impact

Media consumption might rise during Easter, Ascension Day, and Pentecost, especially for travel campaigns. Late November and December bring pronounced spikes in retail advertising. German Unity Day often triggers localized campaigns. Regional holidays may create unique local competition. Sunday/holiday retail restrictions may contract ad inventory.

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.