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Facebook Ads Cost Per Purchase Benchmarks for Software Development in Germany

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Cost Per Purchase for Software Development in Germany

October 2024 - October 2025

Insights

Detailed observation of presented data

Key takeaways

  • Based on $3B worth of advertising data from our dataset, which provides strong directional benchmarks.
  • This analysis looks at cost-per-purchase trends for industry Software Development and target country Germany compared to the global trend.
  • Germany’s cost-per-purchase averaged 67.76 across Oct 2024–Aug 2025, about 37.6% above the global baseline average over the same months (49.24).
  • Volatility in Germany was high: average absolute month-to-month movement was 34.0% (baseline: 4.7%). Costs ranged 3.7x from the monthly low to high.
  • Seasonal pattern: below market in Q4 2024, then sharply higher than market from late spring into summer 2025.
  • From the first to the last observed month, Germany rose +47.8%, while the baseline edged down −2.1% over the same window.

Germany (Software Development): trend highlights

  • Overall level: Average cost-per-purchase was 67.76 across 11 months.
  • Highs and lows:
  • High: 116.17 in May 2025.
  • Low: 31.43 in November 2024.
  • Range: 84.75 points (3.7x spread), indicating pronounced swings.
  • Month-to-month dynamics:
  • Largest jump: +115.4% from April to May 2025 (53.93 → 116.17).
  • Sharpest drop: −34.5% from October to November 2024 (47.97 → 31.43).
  • Average absolute MoM change: 34.0%.
  • Seasonal shape:
  • Q4 2024: Dip in November, rebound in December. Q4 average 43.91.
  • Q1 2025: Steady climb into February (Jan–Mar average 57.88), brief pullback in March.
  • Q2 2025: Exceptional spike in May–June (Q2 average 92.80).
  • Early Q3 2025: Elevated but cooling (July–August average 80.79).
  • First-to-last change: +47.8% from October 2024 (47.97) to August 2025 (70.90).

Comparison to the global baseline

  • Level comparison:
  • Overlapping average (Oct 2024–Aug 2025): Germany 67.76 vs baseline 49.24 (+37.6% above market).
  • Germany was above the baseline in 9 of 11 months; below only in November 2024 and March 2025.
  • Highs and lows:
  • Baseline highs were stable (peak 53.89 in February 2025; most months clustered 46–52).
  • Overlapping baseline low 43.19 (November 2024). Beyond the overlap, the baseline dipped further to 32.29 in September 2025.
  • Volatility:
  • Germany’s average absolute MoM change was 34.0% vs the baseline’s 4.7%, underscoring a much choppier market in Germany for Software Development.
  • Seasonal context:
  • Baseline shows a familiar year-end uptick (December higher than November) and gradual easing into summer.
  • Germany followed the December uptick but diverged strongly in late spring and summer: May was +128% above the global average for that month (116.17 vs 50.97), June +131% (108.29 vs 46.96), July +96%, and August +55%.

Quarter-by-quarter positioning (Germany vs baseline)

  • Q4 2024: 43.91 vs 47.13 — below market.
  • Q1 2025: 57.88 vs 52.94 — modestly above market.
  • Q2 2025: 92.80 vs 49.83 — well above market.
  • Early Q3 2025: 80.79 vs 45.95 — well above market.

Understanding cost-per-purchase benchmarks on Facebook Ads in industry Software Development 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 Software Development 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.