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January 2025 - January 2026
Detailed observation of presented data
All industries in Germany operated at a consistently higher cost per purchase than the global benchmark in 2025, with sharper swings month to month. The year opened at mid-60s levels, spiked dramatically in February, then cooled into a summer trough before lifting in October and easing into year-end—ultimately finishing close to where it started. Compared with the steadier global track, Germany’s pattern was more episodic: punctuated by a February surge and an August low, with Q4 partially rebounding.
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 all industries in Germany compared to the global benchmark.
For Germany, median cost per purchase (CPP) averaged 73.3 across the year, ranging from a high of 100.1 in February to a low of 55.2 in August. The year began at 63.9 in January and ended at 65.3 in December, a near-flat +2% finish despite substantial intra-year movement.
Key inflection points:
The average absolute month-to-month swing in Germany was about 14 points, far choppier than the global series (~1.8 points). Six months sat above the German annual average (notably February and April–June, plus October–November), and six below (January, March, July–September, December).
Globally, CPP averaged 51.4, peaking at 54.8 in February and trending down toward 45.1 by December. From January to December, the global median declined roughly 15%, a smoother descent compared to Germany’s zigzagging path.
The rhythm in Germany tracked familiar auction seasonality, but with outsized amplitude:
Globally, seasonality was more linear: modest levels in Q1 eased through Q2–Q3, then dipped further in Q4 to the year’s lowest quarterly average (48.3).
Germany’s CPP sat above market every month, by an average margin of about 43%. The gap was narrowest in August (+4% vs global) and widest in February (+83%). Through spring (April–June), Germany held 61–63% above the global benchmark; in Q3, the gap narrowed (about +15% on average) as German costs softened while global levels stayed relatively steady. The global trend was a steady decline (−15% Jan→Dec), whereas Germany’s net change was small (+2%) but far more volatile.
Understanding Facebook Ads cost-per-purchase benchmarks for all industries in Germany highlights a market with elevated, more volatile country-specific ad costs versus the global baseline. This CPP view complements broader Facebook Ads benchmarks across CPC trends, CPM analysis, and CTR performance, helping teams contextualize industry ad performance in Germany against global patterns.
Insights & analysis of Facebook advertising costs
Facebook advertising costs vary based on many factors including industry, target audience, ad placement, and campaign objectives. Different industries see varying ad costs due to market competition, user demographics, and conversion value. 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.
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.
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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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.
Late November (Black Friday/Cyber Monday), Christmas shopping (late December), Back-to-school (August/September), Spring promotions (Easter period)
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.
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.
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.
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.
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.
Increase budget gradually, rotate creative often, and avoid overlapping audiences. Scaling too quickly can lead to audience saturation and rising CPAs.
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Average cost per purchase benchmarks across industries
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