Facebook Ads Insights Tool

Facebook Ads Cost Per Purchase Benchmarks for E-commerce in Germany

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

Cost Per Purchase for E-commerce in Germany

October 2024 - October 2025

Insights

Detailed observation of presented data

Facebook Ads cost per purchase benchmarks: E-commerce in Germany vs. global

This analysis looks at cost per purchase trends for industry E-commerce 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.

#### Main takeaways

  • Overall level: Germany’s average cost per purchase was 45.28, about 5% below the global baseline (47.82), placing it slightly below market overall.
  • Seasonality: Costs were elevated in Q4 2024 (Germany: 52.02 vs. global: 47.13), then eased in early 2025. A notable spike appeared in August 2025, followed by an unusually sharp dip in September 2025.
  • Volatility: Germany showed higher month-to-month variability (average absolute change 8.64) than the global trend (3.25).
  • Relative positioning: Germany was above market in 4 of 12 months (notably Q4 and August), and below market in 8 months (especially January–July and September).

Selected data highlights: E-commerce in Germany

  • Average and median: Average 45.28; median 46.24 across Oct 2024–Sep 2025.
  • Highs and lows:
  • High: 58.27 in August 2025.
  • Low: 11.64 in September 2025.
  • Range: 46.63.
  • Trend and change:
  • From first to last month: 48.44 (Oct 2024) to 11.64 (Sep 2025), a decrease of about 76%.
  • Average month-to-month change (absolute): 8.64.
  • Seasonal patterns:
  • Q4 2024 average: 52.02, indicating holiday-period inflation.
  • Early 2025 eased: January–June average 45.40, with the lowest typical month in June (41.17) before rebounding in July (44.97) and peaking in August (58.27).
  • Notable movements: A sharp surge in August followed by a pronounced dip in September.

Comparison with global baseline

  • Baseline averages and extremes:
  • Average 47.82; high 53.89 (February 2025); low 32.29 (September 2025).
  • First-to-last decrease: about 31% (46.67 in Oct 2024 to 32.29 in Sep 2025).
  • Average month-to-month change (absolute): 3.25.
  • Relative positioning by period:
  • Q4 2024: Germany above market (52.02 vs. 47.13).
  • January–June 2025: Germany below market (45.40 vs. 51.38).
  • Month-by-month comparison:
  • Germany above market in 4 months (Oct–Dec 2024 and Aug 2025).
  • Germany below market in 8 months (Jan–Jul and Sep 2025).
  • Notable gaps:
  • August 2025: Germany 27.6% above the global baseline (58.27 vs. 45.69).
  • September 2025: Germany 64% below the baseline (11.64 vs. 32.29).

Seasonal context and trend summary

  • Holiday effect: Costs typically increase in Q4 around holiday periods, visible in both Germany and the global series.
  • Early-year normalization: Both series eased post-holidays, but Germany tracked consistently below the global average through H1 2025.
  • Late-summer divergence: Germany’s August spike and September dip created a wider range and higher volatility than the global baseline over the period.

Understanding cost-per-purchase benchmarks on Facebook Ads in industry E-commerce 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 E-commerce industry, Facebook ad costs can be varied, with peaks during holiday seasons and competitive product categories. 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.

Optimize Smarter with Superads

Improve your Facebook ad performance

Instant performance insights – See which ads, audiences, and creatives drive results.

Data-driven creative decisions – Spot patterns to improve ROAS.

Effortless reporting – No spreadsheets, just clear insights.

Get Started for free →

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.