Facebook Ads Insights Tool

Facebook Ads Cost Per Lead Benchmarks in Denmark

See how your CPL compares. Explore lead generation cost benchmarks by industry, region, and campaign type

Cost Per Lead in Denmark

January 2025 - January 2026

Insights

Detailed observation of presented data

Introduction

Across all industries in Denmark, cost per lead spent much of the year oscillating between restrained and extreme, diverging sharply from the global benchmark at key moments. The year opened below market, then surged into a steep Q1 lift and an extraordinary July spike, before cooling into autumn at still-elevated levels. The global series, by contrast, moved in a narrow band with mild late‑year firmness. 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 Denmark compared to the global benchmark.

The story in the data

  • Starting point and finish: Denmark’s CPL began at 26.11 in December 2024 and ended at 66.81 in November 2025, a net increase of roughly 156%.
  • Highs and lows: The low came in January (19.31). The high was a July spike to 1,080.59—the clear outlier of the series.
  • Average and typical levels: Across the observed months, Denmark averaged 195, heavily skewed by July. The median month sat at 95.16, indicating most months clustered far below the July extreme but still well above global levels.
  • Key movements:
  • January dipped 26% from December, then February rebounded to 41.43 (+115% MoM).
  • March vaulted to 159.43 (+285% vs. February), marking the first major breakout.
  • After a modest ease into June (146.01, −8% vs. March), July exploded to 1,080.59 (+640% vs. June).
  • By September, costs reset to 95.16 (−91% from July), then held in a tighter band through October (120.55) and November (66.81).

Volatility was pronounced. Using month-to-month changes across the observed intervals, Denmark’s average absolute swing was about 270 points; removing the July anomaly, the underlying churn still averaged roughly 40. The global benchmark over the same intervals moved by only about 4.2 on average, underscoring how atypical Denmark’s amplitude was.

Seasonal and monthly dynamics

  • Q1 cadence (Jan–Mar): A soft January opened the year, followed by a February recovery and a sharp March lift, producing a Q1 average of 73—buoyed by March’s breakout.
  • Mid-year dynamics: The series eased slightly into June before the July surge. That peak dominated Q3, with a two-month average of 588 (July and September combined), despite September’s comedown.
  • Late-year pattern: October and November settled into a mid‑range zone (121 and 67 respectively), higher than the December 2024 baseline but far below the July apex. This aligns with typical patterns where Q4 competition can lift costs globally, though Denmark’s Q4 read still looked more restrained than mid-year.

Country vs. Global

Relative to the global Facebook Ads benchmarks for CPL:

  • Denmark started below market: December was 32% cheaper than global; January was 45% lower.
  • From February onward, Denmark consistently ran above the benchmark: +4% in February, +382% in March, +260% in June, and a striking +2,580% in July.
  • Into autumn, Denmark stayed elevated: +98% in September, +149% in October, and +46% in November.
  • On average (matching months), Denmark’s CPL was about 195 versus the global 41—roughly 4.8x higher. Even excluding July, Denmark’s average (~84) still nearly doubled the global benchmark. The gap was narrowest in early Q1 and widest in July.

Closing

Viewed through cost per lead, all‑industry Facebook Ads benchmarks in Denmark tell a year of sharp swings: an early‑year lift, a mid‑year spike, and a late‑year cool‑down—consistently more volatile and generally above the global benchmark. Understanding cost‑per‑lead trends for all industries in Denmark helps marketers assess country‑specific ad costs, compare CPL performance to global patterns, and contextualize Facebook Ads benchmark movements over the year.

Understanding the Data

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 Denmark, 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.

Why we use median instead of average

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.

Key Factors Affecting 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.)

Note: This data represents industry median values and benchmarks. Your actual costs may vary based on specific targeting, ad creative quality, and campaign optimization.

Optimize Smarter with Superads

Improve your Facebook ad performance

Instant performance insights – See which ads, audiences, and creatives drive results.

Data-driven creative decisions – Spot patterns to improve ROAS.

Effortless reporting – No spreadsheets, just clear insights.

Get Started for free →

The data behind the benchmarks

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.

Denmark Advertising Landscape

National Holidays

Jan 1New Year's Day
Apr 17Maundy Thursday
Apr 18Good Friday
Apr 20Easter Sunday
Apr 21Easter Monday
May 29Ascension Day
Jun 8Whit Sunday
Jun 9Whit Monday
Dec 25Christmas Day
Dec 26Second Day of Christmas

Key Shopping Season

Christmas & Boxing Day (late Dec), Easter holidays (groceries, travel, tourism), Mother's Day and Valentine's Day

Potential Advertising Impact

CPM and CPC could rise during Easter period due to travel-related campaigns. Late December ad competition might intensify in retail and hospitality. Whit Weekend might reduce weekday competition. Strict retail closures on holidays could drop competition, but pre-holiday CPMs may escalate.

What is considered a good cost per lead on Facebook in 2025?

A good CPL usually ranges from $10 to $50, depending on your industry and target audience. B2C offers tend to be cheaper, while B2B or high-ticket services may see CPLs over $100.

Why is my CPL higher than industry averages?

Your CPL could be high due to weak creative, irrelevant targeting, or an offer that doesn't resonate. Low engagement or poor conversion rates on your landing page can also drive up costs.

Does campaign objective impact CPL?

Yes. Campaigns optimized for conversions or leads tend to generate cheaper and more qualified leads compared to traffic or engagement objectives. Facebook needs clear signals to find the right users.

How can I generate leads at a lower cost without hurting lead quality?

Focus on improving your offer, targeting the right audience, and using high-converting creative. Test native lead forms, but make sure you're still qualifying users properly.

Should I optimize for leads or conversions if my goal is pipeline growth?

If your goal is sales or revenue, optimizing for deeper funnel conversions is better. Optimizing for leads alone can inflate volume but hurt quality.