Free report · Beatly Reporting Out 01

The Click Window

When Nordic audiences actually click creator links, and what to have ready before they do. Based on 119,236 tracked clicks from Beatly campaigns.

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PDF · 9 pages · Sweden, Norway, Denmark, Finland · January 2025 to August 2026

Cover of The Click Window, Beatly Report 01
of clicks arrive within 12 hours of publishing
50%
arrive on day one
65%
click rate on Instagram story links, about 6× the feed
1.33%
more clicks on Monday than on Saturday
2.2×

What we found

Clicks come early, and on a schedule

Creator campaigns usually get judged on reach. This report looks at the moment people act: every tracked click on Beatly campaign links in the Nordics since January 2025, each with an exact timestamp. The window is short, and predictable enough to plan around. Here are three of the findings; the full report has the tables, the method and a launch checklist.

01

Most clicks happen before the next morning

38% of clicks land within 6 hours, 65% within 24 and 70% within 48. Stories finish fast: the median story click comes about 8 hours after publishing. Feed posts keep working longer, with a median of 22 hours. The landing page, the discount code and the stock need to be ready at minute one.

Cumulative share of clicks by time since publishing
  1. Within 6 hours38%
  2. Within 12 hours50%
  3. Within 24 hours65%
  4. Within 48 hours70%

Half of all clicks by 12 hours. Two thirds on day one.

02

Reach and clicks are different jobs

Instagram story links get a 1.33% click rate, six times the feed (0.22%). TikTok videos come in at 0.10%. Feed posts and TikTok travel further per follower, so the formats work best together: one builds attention, the story with the link collects the clicks.

Link clicks per 1,000 impressions · one cursor = one click

  • Instagram story≈ 13 per 1,000 1.33% click rate

  • Instagram feed≈ 2 per 1,000 0.22% click rate

  • TikTok video≈ 1 per 1,000 0.10% click rate

03

The evening window and the Monday click

Clicks peak at 18:00 CET, and 17:00 to 20:00 brings almost a third of the day’s clicks. Monday is the biggest click day of the week, 2.2× Saturday and ahead of Sunday.

Clicks by day of week · all 119,236 clicks
  1. 23.0kMon
  2. 18.3kTue
  3. 15.2kWed
  4. 16.5kThu
  5. 16.0kFri
  6. 10.5kSat
  7. 19.8kSun

Inside the full report

Nine pages you can plan with

  • The full decay curveFrom the first click to week two
  • Format and timing tablesClicks, impressions and click rate for stories, feed and TikTok
  • The day-one checklistSeven things to have live before a creator post goes up
  • Measuring the whole campaignWhy every tracked link counts, not only the post
  • The methodologyWhere the data comes from and how to read the findings
Get the PDF
Report page: the decay curveReport page: clicks by hour and dayReport page: the day-one checklist

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PDF · 9 pages · 5.6 MB.

How this was measured

119,236 clicks on Beatly-tracked campaign links, January 2025 to August 2026, each with an exact server timestamp (CET). 50,838 clicks were attributed to a specific publication. Decay, format and click-rate figures use this attributed set; hour and day patterns use all clicks. Markets: Sweden, Norway, Denmark and Finland. All data is aggregated and anonymised; no client, campaign or creator is identified. The PDF ends with a full methodology page.

Questions

Before you download

Is the report free?

Yes. It is a 9-page PDF you can keep and share inside your team.

Where does the data come from?

119,236 clicks on Beatly-tracked links from creator campaigns in Sweden, Norway, Denmark and Finland, January 2025 to August 2026, each with an exact timestamp.

Are any brands or creators named?

No. Everything is aggregated and anonymised. No client, campaign or creator is identified.

Can I get these numbers for my own campaigns?

Yes. Beatly benchmarks the campaigns it runs against this dataset. Talk to a strategist about your next campaign.

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For your brand

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Beatly plans, runs and measures creator campaigns across the Nordics, and benchmarks every campaign against this dataset.

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