Compare ecommerce conversion cost benchmarks by industry, region, and campaign type.
October 2025 - September 2026
Benchmark observations based on the selected data
Textiles' cost-per-purchase sat far below the global baseline for most of the 11-month window, then climbed sharply into mid-2026, ending the period materially higher than where it began. 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 Textiles in All countries compared to the global benchmark.
From August 2025 to June 2026 Textiles (All countries) moved from $3.56 to $10.50 per purchase — an increase of roughly +195%. Across the period the median cost-per-purchase averaged about $5.60, with a low of $3.43 in September 2025 and a high of $10.50 in June 2026. Month-to-month swings were notable: January 2026 produced a near 49% uptick versus December, March rose about 30% versus February, April jumped roughly 45% from March, and June finished with another 35% rise over May. Absolute range across the year was about $7.07.
Volatility was elevated: average month-over-month movement measured roughly 22% (absolute percent change), signaling more pronounced swings than typical baselines in the dataset.
While this summary centers on cost-per-purchase, the same reporting suite tracks Facebook Ads benchmarks across CPC trends, CPM analysis, and CTR performance — offering context across purchase and engagement metrics.
The rhythm shows a muted late‑2025 (Aug–Dec) plateau around $3.4–$4.1, followed by a pronounced lift in early 2026. January kicked off a new phase with a steep rise, a brief pullback in February, then renewed acceleration through spring: March-to-April delivered a strong lift, May dipped slightly from April, and June closed the period at the peak. This pattern reads like a quiet pre-holiday baseline, a post-holiday rebound and then an intensifying mid‑year escalation — with the heaviest upward momentum concentrated in Q1–Q2 of 2026.
Seasonal context in the global data also shows familiar cyclical pressures: the global benchmark hit a high in March and then softened toward June, mirroring typical shifts in competition and spend across quarters.
Compared with the global baseline over the same months, Textiles in All countries was markedly below market. The baseline median across Aug 2025–Jun 2026 averaged about $49.94 per purchase versus Textiles’ $5.60 — roughly 89% lower. The gap narrowed and widened over time: at its narrowest (June 2026) Textiles was about 24% of the global cost-per-purchase; at its widest (October/November windows) it was under 10% of the global median. Global cost-per-purchase trended modestly downward over the period (roughly −18% from Aug to Jun), while Textiles exhibited a choppier, upward trajectory (+~195%), and materially higher month-to-month volatility (~22% vs ~6% for the baseline).
Understanding Facebook Ads cost-per-purchase benchmarks for Textiles in All countries sheds light on how industry ad performance can diverge from broader baseline trends across CPC trends, CPM analysis, and CTR performance.
Facebook advertising cost benchmarks
Facebook advertising costs vary by industry, target audience, ad placement, and campaign objective. In the Textiles industry, Facebook ad costs can be influenced by seasonal trends and market competition. Geographic targeting affects ad costs through regional competition and user engagement. Campaign objectives affect costs because Facebook optimizes delivery for different goals. The data shows median values across multiple campaigns. Results can vary with ad quality, audience targeting, and campaign optimization.
A small share of campaigns has extremely high CPP values. Those outliers can inflate an average. The median is the midpoint across campaigns, so it better represents a typical result.
The data shows industry median benchmarks. Costs can vary with targeting, creative quality, and campaign optimization.
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The dataset includes over $3B in Facebook ad spend from thousands of ad accounts that use Superads to analyze and improve campaigns. Every data point is anonymized and aggregated. It does not expose an individual advertiser.
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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. A higher CPA can work when the margin supports it. Measure CPA 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 advertisers stay within a target CPA. It suits experienced advertisers who can monitor performance and adjust regularly. It provides more control and 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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