See how your purchase costs compare. Explore ecommerce conversion cost benchmarks by industry, region, and campaign type
February 2025 - February 2026
Detailed observation of presented data
Cost per purchase for Facebook Ads in Great Britain ran materially above the global benchmark and moved with far sharper swings. The year opened soft, dipped again mid-year, then accelerated through late Q3 and broke decisively higher in Q4, culminating in a new high in January 2026. In contrast, the global series stayed relatively flat for most of 2025 before sliding into year-end and dropping sharply in January 2026. 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 Great Britain compared to the global benchmark.
Great Britain’s median cost per purchase began at 39.69 in January 2025 and closed the year at 108.21, then climbed again to 135.94 in January 2026. The 2025 average landed at 70, rising to 75 across the full 13-month window. The low came at the start (39.69 in January) with a secondary trough in June (45.78). The late-year high arrived in December (108.21), then a further record in January 2026 (135.94).
Momentum unfolded in clear waves: a February–March lift (64.41 to 79.43), a reset into April–June (64.38 to 45.78), and a steady Q3 climb (65.20 to 83.47). October marked a brief pullback to 64.45, followed by a November rebound (78.32) and a December surge (108.21). Month-to-month absolute changes averaged 17.6 points, signaling pronounced volatility.
Globally, the median hovered in a tight band for most of 2025 (roughly 47–55), averaging 51.65 for the year. December closed at 47.62, and January 2026 dropped sharply to 25.15. Average monthly volatility was far lower at 3.33 points, though that includes the steep January decline.
Seasonality was visible on both series but in opposite directions late in the year. Great Britain’s costs accelerated from late Q3 into Q4, consistent with holiday competition lifting purchase costs. Q4 averaged 83.66 in Great Britain versus 49.25 globally. Earlier in the year, Great Britain’s Q1 averaged 61.18, close to the steady global Q1 of 53.61. A softer patch emerged in early summer (June’s local low), and October provided a brief autumn lull before the year-end climb.
Relative to Facebook Ads benchmarks worldwide, Great Britain was higher and more volatile. From February onward, it stayed above the global line each month. The 13‑month average in Great Britain (75) ran 51% above the global average (49.6). The gap was narrowest in June 2025, when Great Britain sat 10% below the global level. It widened dramatically by January 2026, when Great Britain’s cost per purchase was 440% above the global median. Directionally, 2025 ended with a +173% move from January to December in Great Britain, while the global series eased about 10% over the same span. The divergence deepened in January 2026: Great Britain rose a further 26% month over month; global costs fell 47%.
These Facebook Ads benchmarks show that cost-per-purchase for all industries in Great Britain was consistently above market and markedly more volatile than the global trend, with a strong Q4 lift extending into January 2026. Understanding country-specific ad costs and industry ad performance helps contextualize CPC trends, CPM analysis, and CTR performance against global patterns for Great Britain.
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 United Kingdom, advertisers experience moderate to high costs with strong performance in urban areas. 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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Late November (Black Friday/Cyber Monday surge), Late December (Christmas & Boxing Day promotions), Early May holiday weekend promotions
CPM and CPC might increase around early May and late August bank holidays as people engage in leisure travel or retail browsing. During Black Friday/Cyber Monday, retail CPMs could spike sharply in fashion, electronics, and online shopping. Late December typically sees peak CPMs, with e‑commerce budgets needing early ramp-up.
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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