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
The main story: Cost per purchase for Textiles in All countries ran far below the global benchmark but moved with clear momentum — a quiet late‑2025 trough gave way to a sharp climb across early 2026, ending the window near the year’s high. 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.
Across the 11‑month window (Aug 2025 → Jun 2026) Textiles’ median cost per purchase started at $3.56 and finished at $9.56 — a +169% rise from the opening month. The series averaged $5.49 per purchase, ranging from a low of $3.43 (September 2025) to a high of $9.56 (June 2026). Month‑to‑month moves were meaningful: average absolute change was about $1.11, with a standard deviation near $2.16, showing substantive swings on a small-dollar base.
By contrast, the global baseline hovered around $48.02 on average for the same months, with baseline medians generally in the $49–$55 band until a steep drop to $25.50 in June 2026. Textiles’ cost per purchase was therefore typically an order of magnitude lower than the global median — roughly 89% below the benchmark on average.
Late 2025 showed a softer rhythm: August–December remained compressed between $3.43 and $4.11, a relatively calm period. January 2026 marked a rebound (to $5.48), followed by alternating rises and modest pullbacks in February–March. From March into April the series accelerated (March $5.93 → April $8.59), then held elevated through May and peaked in June at $9.56. The pattern reads as late‑year lull, early‑year lift, and a steep spring surge into early summer.
Meanwhile the global baseline displayed a steadier plateau for much of the period, then an abrupt decline in June 2026 (from ~$45 in May to $25.50 in June), which narrowed the absolute gap between Textiles and the benchmark in the final month.
Measured against the baseline, Textiles’ cost per purchase tracked well below global medians throughout the year. Relative gaps started extremely wide (Textiles about 92–93% below global levels in Aug–Dec 2025), narrowed modestly in early 2026 (around 89–83% below in Jan–May), and closed most in June 2026 when the baseline fell — Textiles was approximately 63% below the global median in June. On a relative basis Textiles showed greater variability: coefficient of variation for Textiles was roughly 39% versus about 17% for the global baseline, indicating more pronounced proportional swings on a lower dollar base.
This dataset sits in the broader context where conversations about Facebook Ads benchmarks often include CPC trends, CPM analysis, and CTR performance; here the country‑specific ad costs and industry ad performance story is focused on cost‑per‑purchase behavior for Textiles across All countries.
Understanding Facebook Ads cost‑per‑purchase (COST_PER_PURCHASE) benchmarks for the Textiles industry in All countries helps advertisers evaluate industry ad performance and compare country‑specific ad costs to 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 Textiles 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.
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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