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August 2025 - August 2026
Detailed observation of presented data
Sweden’s Cost Per App Install (CPI) series tells a compact but turbulent story: overall lower than the global benchmark, yet punctuated by dramatic month-to-month swings. 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 All industries in Sweden compared to the global benchmark.
Across the four-month sample, Sweden’s median CPI averaged about 13.46, starting at 13.32 in September 2025 and ending at 4.75 in January 2026. The local high was 32.72 in October 2025 and the low was 3.04 in November 2025 — a 10.7x span between trough and peak. That October spike (+146% vs. September) was immediately followed by a November collapse (−91% vs. October), then a modest rebound into January (+56% vs. November). On an absolute scale the range was roughly 29.7 points; measured for variability, monthly volatility averaged about 11.8 points, roughly 88% of the series mean — a sign of steep, short-term swings rather than a steady trend.
By contrast the baseline (global) CPI across the provided months averaged about 21.83, with values ranging from roughly 9.36 to an outlier 96.91 in July 2026. Sweden’s average sits about 38% below that global median, reflecting a consistently lower cost environment in this sample window despite Sweden’s own high intra-period churn.
The four-month rhythm for Sweden reads like sharp bursts: a late‑Q3 starting point, a pronounced Q4 spike and crash, and a mild recovery in early Q1. November’s deep trough is the standout monthly movement, creating a pronounced dip that breaks any simple seasonal rhythm. The baseline shows its own seasonality with a very large summer spike later in the series, but within the Sweden sample the dominant dynamic is rapid momentum shifts over weeks rather than gradual quarter-to-quarter movement.
Relative to the global benchmark, Sweden’s Cost Per App Install is below average across these months — roughly 30–45% cheaper on the median comparison. The global trend includes a high-amplitude outlier in mid‑2026 that pushes the baseline mean up; Sweden’s series is more “choppy” on a month-to-month basis, with larger percent swings (e.g., +146% then −91%) than the smoother, though occasionally spiky, baseline. In phrasing common to paid media analysis: Sweden’s CPI sits below market levels but is more volatile in the short run.
Understanding Facebook Ads benchmarks for Cost Per App Install across all industries in Sweden helps advertisers and creative strategists read country-specific ad costs and industry ad performance against broader CPC trends, CPM analysis, and CTR performance benchmarks.
Insights & analysis of Facebook advertising costs
Facebook advertising costs vary based on many factors including industry, target audience, ad placement, and campaign objectives. Different industries see varying ad costs due to market competition, user demographics, and conversion value. For campaigns targeting Sweden, advertisers should consider local market factors and user behavior. 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.
Late November (Black Friday is huge), December (Christmas and post-Christmas sales), June (Midsummer seasonal promotions), January (Winter sale season)
CPMs might spike during Black Friday and early December, especially in e‑commerce and fashion. Easter and Midsummer holidays often decrease weekday inventory but increase media usage during long weekends. Midsummer tends to be quiet in retail but active in travel and food sectors. Post-Christmas sales in January still see high digital ad demand.
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.
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.
Short videos showing app benefits, UGC-style content, and localized messaging tend to perform best. Clear CTAs and fast-paced visuals help lower your CPI.
Optimizing for installs gets volume, but optimizing for actions like signups or purchases brings higher quality users. It depends on your goals and how much post-install behavior matters.
Align your creative with the app experience, avoid misleading ads, and exclude users who already installed. You can also test lookalike audiences based on high-quality users, not just all installers.
Discover detailed cost benchmarks for different Facebook advertising metrics:
Average cost per click benchmarks across industries
Cost per thousand impressions across different markets
Benchmark click-through rates for Facebook ads
Cost per lead across different markets
Average cost per purchase benchmarks across industries
See how much it costs to get users to install an app