Compare ecommerce conversion cost benchmarks by industry, region, and campaign type.
October 2025 - September 2026
Benchmark observations based on the selected data
The main story: Energy and Mining cost-per-purchase in our multi-country sample started the period extremely elevated, spiked to the year’s peak in October, then collapsed into a very low trough by December and held low into January. Compared to the global benchmark, the Energy and Mining series was meaningfully higher on average but far more volatile, with dramatic month-to-month swings that punctuated the seasonal rhythm.
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 Energy and Mining in all countries available compared to the global benchmark.
Across the five-month window from September 2025 to January 2026, median cost-per-purchase for Energy and Mining averaged about $65.6. The series opened at $131.7 in September, climbed to a peak of $146.4 in October, then plunged to $35.7 in November and collapsed further to $6.51 in December before a modest rebound to $7.56 in January. The high-to-low swing amounted to a roughly 98% decline from October’s peak to January’s close.
Over the same months the global baseline median sat near $50.15 per purchase. That makes the Energy and Mining five‑month mean about 31% above the global benchmark, but that average masks extreme month-level divergence: Energy and Mining ran roughly 2.5–2.8x the baseline in September–October, then shifted to being 23% below the global level in November and roughly 85% below in December–January.
Volatility was striking. Monthly percent moves for Energy and Mining were +11% (Sep→Oct), −76% (Oct→Nov), −82% (Nov→Dec), and +16% (Dec→Jan). The average absolute monthly change was about 46% — nearly nine times the baseline’s average monthly absolute change of ~5%.
The series shows a compressed seasonality: a late‑Q3/early‑Q4 spike followed by a sharp drop into late Q4 and anemic levels in early Q1. October is the clear standout with the largest lift; November through January is the trough period with the steepest declines and the lowest absolute costs. The global baseline displays a much flatter rhythm across the same window, with only modest dips and recoveries rather than the dramatic swings seen in Energy and Mining.
These month-to-month dynamics create a rhythm where short bursts of elevated cost-per-purchase give way to rapid deflation — a pattern that reads less like a smooth seasonal cycle and more like episodic volatility tied to discrete moments in the period.
Relative to the global benchmark, Energy and Mining was both above market and below market at different times: materially above in September and October (about +150–180% vs. baseline), then substantially below in December and January (about −85%). In volatility terms, Energy and Mining was far more volatile than the global trend — roughly nine times the baseline’s month-to-month movement — indicating sharper swings in country-specific ad costs within this industry.
Across these months the headline position shifts from “well above average” at the start of the period to “well below average” at the end, creating a large and rapidly changing gap with the global benchmark.
Understanding cost-per-purchase benchmarks for Energy and Mining across all countries available helps marketers and analysts interpret industry ad performance and compare country-specific ad costs to broader CPM analysis and Facebook Ads benchmarks in the market.
Facebook advertising cost benchmarks
Facebook advertising costs vary by industry, target audience, ad placement, and campaign objective. In the Energy and Mining 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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