Facebook Ads Insights Tool

Facebook Ads Cost Per App Install Benchmarks for Software Development

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

Cost Per App Install for Software Development

October 2025 - September 2026

Insights

Benchmark observations based on the selected data

Introduction

Software Development’s cost-per-app-install ran well below the global benchmark across the 12 months from July 2025–June 2026, with a lower average, sharper relative swings, and a few pronounced month-to-month lifts. 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 Software Development in All countries available compared to the global benchmark.

The story in the data

The Software Development cost-per-app-install started the period at $1.70 in July 2025 and finished at $5.40 in June 2026 — a roughly +218% increase from start to finish driven by mid‑season spikes. Across the year the median install cost averaged about $5.17, ranging from a low of $1.70 (Jul 2025) to a high of $9.68 (May 2026). Monthly volatility was meaningful: standard deviation was roughly $2.30, and average absolute month-to-month moves ran near 40% — so swings were frequent even if absolute dollars remained below the market.

Notable inflection points: an early ramp into October (to ~$5.38), a soft late‑year lull through December–January (~$3.00–$3.38), then a steep lift in February (to ~$7.44) that held into spring and peaked in May before a pullback in June. Those peaks produced the period’s largest jumps (July→Aug and Jan→Feb each showed roughly +120% moves).

Seasonal and monthly dynamics

The rhythm shows a low-price summer into early fall, a moderate October lift, a softer Q4 into early Q1, then a clear spring surge. December and January were comparatively muted (near the mid-$3 range), followed by an intense February rebound and sustained spring pressure through May. May’s $9.68 peak stands out as the strongest monthly pressure on install costs for the cohort, with June retracing some of that strength to $5.40. Overall the year reads as two quiet pockets (summer/early fall and Q4/Q1) separated by a concentrated late-winter to spring lift.

Country vs. Global

Against the global benchmark for the same months, Software Development installs were materially lower. The baseline median across July 2025–June 2026 averaged about $15.58 per install versus ~$5.17 for Software Development — roughly 67% below the global median on average. Month-by-month the spread varied: at its narrowest (May 2026) Software Development was about 33% below baseline (Software Dev $9.68 vs baseline $14.41), and at its widest (July 2025) it was ~83% below (Software Dev $1.70 vs baseline $9.95). The global series itself showed larger absolute swings (baseline sd ≈ $5.15) and an outlier spike in the baseline series in July 2026 (~$96.91) that sits outside the primary comparison window and accentuates market noise. In relative terms Software Development showed higher coefficient-of-variation (≈44%) versus the baseline (≈33%), meaning the category had smaller absolute dollars but comparatively choppier month-to-month behavior.

Understanding Facebook Ads cost-per-app-install benchmarks for Software Development across All countries available highlights how industry ad performance and country-specific ad costs can diverge from broader CPC trends and CPM analysis in global advertising benchmarks.

About this data

Facebook advertising cost benchmarks

Facebook advertising costs vary by industry, target audience, ad placement, and campaign objective. In the Software Development 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.