Most articles about short-link analytics are invented. They show you a clean pie chart, tell you "78% of users are on mobile," you redesign your landing page around it, and nothing changes.
This one is different. It is the raw output of five months of production traffic from PicKu, a URL shortener I run: 27,013 clicks across 806 short links, from 120 countries, May 25 to October 21, 2026. Every number below comes from real records, including the parts that make me look bad.
Start with the number nobody puts in a blog post
Of those 27,013 clicks, 13,745 (50.9%) arrived with no referrer at all. Another 12,220 (45.2%) came from three domains I own.
Strip my own traffic out, and the genuinely external organic traffic is 714 clicks — 2.6% of the total.
I could have left that out. Most write-ups would. But here is why it matters:
If you read your own referrer report as "where my users come from," your promotion channels will systematically mislead you. You will conclude your users come from your other site, then spend double on that site, closing a self-congratulatory loop. I nearly did exactly that.
The actionable rule: before you optimise acquisition, subtract self-referred traffic. What remains is your real acquisition surface. Mine was 2.6%. Yours might be 40%. You cannot know until you subtract.
"Direct" is over half. That is not a bug.
Every short-link system shows a fat "direct" slice. This is not broken tracking — it is the fate of the format.
A short link's whole job is to fit a long URL into a chat window. When someone taps it from WeChat, QQ, Slack, or email, the browser gets either no referrer or the referrer of the app's in-app container. Modern apps use their own WebViews and many strip the Referer header outright as a privacy measure. You cannot intercept that.
So: if a tool claims 100% source attribution, it is either lying or normalising only the tracked subset into something that looks clean and isn't usable.
The 23% "Unknown OS" is WebViews and crawlers
| OS | Clicks | Share |
|---|---|---|
| Windows 10 | 9,360 | 34.7% |
| Unknown OS | 6,320 | 23.4% |
| Android | 5,109 | 18.9% |
| Mac OS X | 2,800 | 10.4% |
| iPhone | 2,424 | 9.0% |
| Linux | 645 | 2.4% |
| iPad | 125 | 0.5% |
| Windows 7 | 91 | 0.3% |
My first reaction to "Unknown OS" at second place was that my parser was broken. It isn't. Three things land in that bucket:
- App WebViews that omit key fields or disguise themselves
- In-app browsers (27.8% of all traffic, see next section)
- Search engine prefetching — Baidu, 360, and Bing crawlers hit short links constantly
That third one deserves emphasis: short-link pages are among the most heavily crawled page types on the web. Any public short link shared into a group chat gets crawled within hours. Counting those as analytics is measuring bot traffic.
At least half of that 23% is WebView plus crawlers. That is why "mobile share" is such a soft number across most short-link tools.
One conclusion does survive the noise: Windows 10 at 34.7% plus Windows 7 at 91 clicks makes desktop Windows the absolute majority. If your short links point at landing pages with images, popups, or splash screens, design for 1366×768 through 1920×1080 first, mobile second. That runs against instinct. The data decides it, not instinct.
"Handheld Browser" at 27.8% is not a browser
| Browser | Clicks | Share |
|---|---|---|
| Chrome | 12,632 | 46.8% |
| Handheld Browser | 7,520 | 27.8% |
| Unknown Browser | 5,359 | 19.8% |
| Firefox | 790 | 2.9% |
| Safari | 695 | 2.6% |
| Internet Explorer | 5 | 0.02% |
| Opera | 1 | — |
"Handheld Browser" is the fallback label a server-side UA parser assigns when it cannot identify the engine at all. Everything in that bucket is, in substance, a mobile WebView. The frequency check confirms it: Opera, a genuinely obscure desktop browser, managed exactly 1 click.
For anyone shipping a landing page, this matters far more than "Chrome is 46.8%":
-
WeChat's in-app browser doesn't support all modern CSS —
backdrop-filter,:has(), and someposition: stickybehaviour - WeChat intercepts pages with outbound links, so an outbound button may render as an interstitial
- WebP support depends on the WeChat version — older WebViews show a blank block where your carefully optimised image should be
If you run short links in China, open your splash page inside WeChat itself, not in Chrome's device emulator. I have seen too many pages that "looked fine in the emulator" and showed no image in WeChat.
Moldova is not your 12th biggest market
| Country | Clicks |
|---|---|
| China | 10,127 |
| United States | 6,174 |
| France | 1,722 |
| (blank) | 1,417 |
| Japan | 1,268 |
| United Kingdom | 875 |
| Germany | 609 |
| Hong Kong, China | 441 |
| Canada | 420 |
| Taiwan, China | 399 |
| South Africa | 388 |
| Republic of Moldova | 385 |
That blank 1,417 (5.2%) is not "unknown country" — it means the request carried no resolvable IP. Causes: server-side internal redirects, proxy requests, CDN origin fetches, crawlers.
The easy misreading: see "China 10,127, US 6,174" and conclude your users split evenly between China and the US. But with 13,745 direct clicks in the referrer column, there is no way to tell how many were Chinese users clicking Chinese links versus overseas users clicking Chinese links.
The telling outlier is Republic of Moldova at 385 clicks, rank 12. Moldova has about 2.5 million people. A country of 2.5 million contributing 1.4% of all clicks — ahead of Japan, the UK, and Germany per-capita by an absurd margin — is not a normal number. My read: those are overseas VPS or proxy egress IPs that geolocate to Moldova, or imprecise IP database data for the region. Moldova is a known proxy-relay hub in Europe.
The lesson is not "localise for Moldova." It is: always distrust the outliers in the long tail. When a country suddenly enters your top five, check IP attribution before you build a campaign for it.
A 207-a-day average hides a weekly rhythm
October 12–21 totals 2,068 clicks, a daily average of 206.8.
| Day | Clicks |
|---|---|
| Weekdays (avg) | 266 |
| Sat, Oct 12 | 97 |
| Sun, Oct 13 | 169 |
Weekend volume collapses to 40–60% of weekday volume, and the pattern is very stable.
That is directly usable for scheduling: weekday daytime is the main arena — that is when load time and reliability matter most.
One caution I nearly got wrong myself: Oct 13's 169 looks like a drop, but it is a Sunday. Never judge a trend from a single day.
What this data is actually for
If you read those five tables and thought "so what," here are the three things I actually do with them.
1. Decide landing page dimensions instead of guessing.
Desktop Windows at 34.7% means design for 1440px wide, then fold down for mobile. Not the reverse. Most people get this order backwards.
2. Decide what your stack must support.
Handheld Browser at 27.8% means old WebView compatibility is mandatory: no :has(), do not lean on backdrop-filter, ship both WebP and JPG.
3. Strip self-owned traffic before deciding where to spend.
Remove my own domains and external natural traffic is 2.6%. That number is small, but it tells me something more important than any acquisition report: I currently have almost no external acquisition.
The uncomfortable summary
- 50.9% of clicks had no referrer. Normal, not broken.
- 45.2% came from my own domains. That is the number that should worry you about your own data.
- 2.6% was genuinely external. That is the number that should drive your budget.
- "Unknown OS" and "Handheld Browser" are not user segments. They are measurement failure.
- A country ranking can be a proxy artefact.
If your analytics show a clean picture, you are probably looking at a filtered report.
Raw dataset: 27,013 clicks, 806 links, 27,002 detail rows (an 11-row gap, 0.04%, is crawler traffic that redirects but carries no referrer or complete UA). 120 countries. Period: 2026-05-25 to 2026-10-21. Tool: PicKu — free URL shortener with click analytics. The full breakdown, including the numbers I left in this post, is at picku.org/blog/short-link-analytics-blind-spots.
Part 1 of a series. Part 2 takes the part the data does have — timing — and finds something I got wrong the first time: weekends are not dead, Saturday is the biggest day of the week. Weekends Are Not Dead. My Data Says They're 10% Better.
Top comments (1)
publishing the 2.6% figure is the brave part. most reports would quietly keep the self-referred clicks in, and then the acquisition story looks far healthier than it is.