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Facebook Ads Cost Per App Install Benchmarks for Energy and Mining

Compare mobile acquisition cost benchmarks by industry, region, and platform.

Cost Per App Install for Energy and Mining

October 2025 - September 2026

Insights

Benchmark observations based on the selected data

Introduction

Headline: Cost-per-install for Energy and Mining moved from low double-digits into a late-July outlier, producing a year of choppy momentum and outsized volatility.

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.

The story in the data

Across the 13-month series (July 2025 → July 2026) median cost-per-app-install averaged about $21.8, with values clustering between roughly $9 and $30 for most months before a dramatic spike to $96.91 in July 2026. The period opened at $9.95 in July 2025 and closed at $96.91 — an almost 875% increase from start to finish driven by two marked surges.

Low points: December 2025 bottomed at $9.36 (the series low). Typical mid-range months included July–October 2025 and March–June 2026, where installs commonly landed in the $12–$19 range. High points: February 2026 showed an early spike to $30.13 (+135% vs January), and July 2026 produced the outlier at $96.91 — more than six times the June level of $14.77.

Monthly momentum was uneven: notable lifts in August–October 2025 (steady rise to $16.43), a softening into December, a rebound and spike in February, a choppy spring, and then the extreme July upswing. Median behavior therefore shows a central tendency near $15 but with a long right tail.

Seasonal and monthly dynamics

Seasonal rhythm is visible: late-year softness in December (9.36) preceded a January pickup ($12.83) and a pronounced February surge ($30.13). Spring months (March–May) reverted toward mid-teens ($16.6 → $14.4), suggesting a period of relative normalization after the winter bump. June held steady ($14.77) before the large end-point jump in July 2026.

Volatility followed a stop-start pattern — quieter transitions in early fall (Sep→Oct +4.9%) and late spring (May→Jun +2.5%), contrasted with big swings around year-end and early-year (Nov→Dec −37%, Dec→Jan +37%, Jan→Feb +135%). July’s +556% month-to-month move versus June is the defining outlier of the series.

Country vs. Global

Because this series represents Energy and Mining across all available countries, it reads like an industry-level benchmark within the global set. The median of ~$21.8 over the period sits above many single-month lows (<$10) but is skewed by two spikes (Feb and particularly Jul). Volatility averaged an absolute monthly change near 77% when the July outlier is included; excluding that single outlier the average absolute monthly move falls to roughly 33%, illustrating how a single month can reshape headline bench­marks.

In plain comparative terms: the dataset shows Energy and Mining cost-per-install as episodically above typical low-double-digit installs, punctuated by large, infrequent spikes — a pattern that elevates the overall mean versus the more stable months.

Closing

Understanding Cost Per App Install benchmarks for Energy and Mining in All countries available provides a clear, data-grounded view of industry ad performance and country-specific ad costs trends within broader Facebook Ads benchmarks, CPC trends, CPM analysis, and CTR performance conversations.

About this data

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.

Why we use median instead of average

A small share of campaigns has extremely high CPI values. Those outliers can inflate an average. The median is the midpoint across campaigns, so it better represents a typical result.

Factors that affect Facebook Ad Costs

  • Competition within your selected industry and audience demographics
  • Ad quality and relevance score. Higher quality ads can lower costs.
  • Campaign objective and bid strategy
  • Timing and seasonality. Costs often increase during holiday periods.
  • Ad placement (News Feed, Instagram, Audience Network, etc.)

The data shows industry median benchmarks. Costs can vary with targeting, creative quality, and campaign optimization.

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The data behind the benchmarks

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.

The dataset updates as new ad data is available.

What's a good CPI for iOS vs Android in 2026?

iOS CPIs often range from $2 to $5 or more. Android is usually cheaper, between $1 and $3. Your CPI will depend on geo, creative, and optimization goal.

Why is my app install cost higher in some countries?

Some regions like the US, UK, and Canada have higher competition and stricter privacy regulations, which drive up costs. Countries with lower purchasing power typically have cheaper CPIs.

What creatives drive the lowest CPI on Facebook?

Short videos that show app benefits, UGC-style content, and localized messaging tend to perform best. Clear CTAs and fast-paced visuals can lower CPI.

Should I optimize for installs or in-app actions?

Optimizing for installs increases volume. Optimizing for actions such as signups or purchases brings higher-quality users. Choose based on your goals and the importance of post-install behavior.

How do I lower CPI without tanking app retention or quality?

Align creative with the app experience, avoid misleading ads, and exclude people who already installed. Test lookalike audiences based on high-quality users rather than all installers.