See how your purchase costs compare. Explore ecommerce conversion cost benchmarks by industry, region, and campaign type
August 2025 - August 2026
Detailed observation of presented data
This analysis is based on $3B worth of advertising data from our dataset, which provides strong directional benchmarks. In short: cost-per-purchase for IT Services & Outsourcing (All countries available) ran materially above the global median in early 2026, with a dramatic spike in April and elevated volatility across the three-month window. The cohort began March markedly above the baseline, exploded in April, then cooled toward May — a pattern of sharp lift and partial rebound that stands in contrast to a relatively stable global benchmark.
This analysis explores ad performance trends for IT Services & Outsourcing in All countries available compared to the global benchmark.
Cost-per-purchase for IT Services & Outsourcing averaged about $397 across March–May 2026, driven by a low of roughly $162 in March, a peak of $677 in April, and a mid-year readjustment to about $351 in May. That represents a March→May increase of roughly 117% (from $162 to $351), but the month-to-month swing was extreme: March→April jumped ~318%, then April→May fell ~48%.
By contrast, the global baseline median across July 2025–July 2026 averaged about $47.6, with a high near $56 (March) and a low near $19 (July). The IT Services & Outsourcing cohort ran roughly 8x the global median over the three months (about 777% higher on average). The gap was smallest in March (about 2.9x the global March median) and widest in April (about 13.6x the global April median).
Volatility numbers underline the difference: the IT Services & Outsourcing series shows a standard-deviation-scale swing (~$213) and average absolute monthly moves near 180% across the window, while the global baseline displayed a standard deviation of roughly $8.6 and average monthly absolute changes near 10%.
The three-month cadence reads like a short burst cycle: a base in March, a large April spike, then a partial retrenchment in May. The baseline sequence across the prior 13 months is comparatively muted, with small month-to-month changes until an abrupt dip into July’s low. The IT Services & Outsourcing series was far choppier — the April spike is the standout month, producing the largest single-month lift in the sampled period before the partial decline in May.
Typical seasonal language is visible in the baseline (moderate Q4 stability with a notable late-summer dip), while the selected cohort demonstrates a concentrated event pattern in spring 2026 rather than a smooth seasonal arc.
Framed relatively: IT Services & Outsourcing (All countries available) was consistently and substantially above the global cost-per-purchase benchmark. March’s gap was the narrowest (about 2.9x global), May sat around 7.4x, and April widened to roughly 13.6x. In volatility terms the cohort was more volatile and episodic than the global baseline — bigger spikes, deeper single-month reversals, and a higher coefficient of variation.
This comparison highlights how a single industry cohort can diverge from the broader market: the IT Services & Outsourcing cost-per-purchase stream for All countries available shows episodic surges that far exceed typical Facebook Ads benchmarks and ordinary CPC trends or CPM analysis signals, while CTR performance and engagement metrics in the baseline remain comparatively steady.
Understanding Facebook Ads cost-per-purchase benchmarks for IT Services & Outsourcing in All countries available provides a data-grounded view of how industry-specific ad costs can diverge from 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. In the IT Services & Outsourcing industry, Facebook ad costs can be influenced by seasonal trends and market competition. 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.
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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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