See how your purchase costs compare. Explore ecommerce conversion cost benchmarks by industry, region, and campaign type
July 2025 - July 2026
Detailed observation of presented data
Cost-per-purchase moved from roughly $49 in July 2025 to a surprisingly low $19.7 by July 2026, tracing a year of pronounced swings and a late-stage collapse. 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 available in All countries compared to the global benchmark.
Across the 13-month window the median cost-per-purchase averaged about $47.6. The series began at $49.18 (Jul 2025), peaked at $56.0 in March 2026, and troughed at $19.7 in July 2026. Monthly movement was material: average absolute monthly change ran roughly $4.8 (about 10% of the mean), underlining persistent volatility rather than a flat seasonal curve.
Key movements read like a momentum chart. After an early lift from $49.18 into the low $50s through Sep–Oct 2025, there was a dip to $46.39 in Nov, a modest rebound into winter ($49–$50 in Dec–Feb), then a pronounced lift to $55.98 in March. From that March high the metric moved lower through spring and early summer — $49.85 in April, $47.37 in May, $42.97 in June — before a dramatic decline to $19.69 in July 2026. The start-to-end change represents roughly a 60% decline.
Rhythm in the data shows a mid-winter plateau (Dec–Feb) followed by a spring spike and then progressive softening into summer. November showed a softer period relative to October, while March stood out as the single-month peak. The most extreme monthly swing occurred from June to July 2026, a decline of about 54% month-over-month that defines the series’ end-state.
These patterns suggest typical peaks and troughs across Q4–Q1–Q2, but with an unusually steep end-of-window move. Overall volatility was higher than a benign seasonal profile: the mean monthly absolute change (~$4.8) signals more jagged month-to-month behavior than steady seasonal rolls.
Because the selected series (All industries, All countries) is identical to the baseline, the country-level and global benchmarks are the same for this period. In other words, All countries’ cost-per-purchase mirrored the global benchmark exactly through the full series — average ≈ $47.6, high ≈ $56.0 (Mar 2026), low ≈ $19.7 (Jul 2026). The profile was characterized by short-lived lifts and sharper declines rather than a smooth climb.
Understanding cost-per-purchase benchmarks for All industries in All countries provides a clear picture of how aggregated Facebook Ads benchmarks, CPC trends, CPM analysis and broader CTR performance signals can translate into country-specific ad costs and industry ad performance comparisons at scale.
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. 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.
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.
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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