Mobile Link Analytics: What to Track and Why It Matters

TL;DR: WarpLink records every click and every attributed install as they happen, per link and per campaign, broken down by device, country, referrer, and UTM parameters. Uniqueness is computed server-side: one click per link, address, and 24 hour window, and bot traffic is excluded before a click event is ever built rather than filtered afterward. Installs join back to the click that caused them once you register an app, and a trend chart shows click-to-install conversion day by day. None of this needs a separate analytics product bolted on afterward: the same SDK and the same dashboard already cover deep linking, install attribution, and analytics. This guide covers what to track, how the numbers differ from in-app product analytics, and the mistakes that make a campaign look better or worse than it actually is.

What Link Analytics Measures

Every link starts producing two kinds of data the moment someone taps it: what happened at the click, and, once the link points at a registered app, what happened at the install it produced.

At the click. Total clicks and unique clicks, per link and across your whole organization. Country, referrer, device type, and UTM source, medium, and campaign, broken down per link. Whether the tap resolved to your app opening or fell through to a web redirect.

At the install. Once an app is registered, the attribution match cascade joins new installs back to the click that caused them, and both the install count and a day-by-day click-to-install conversion rate sit next to the click numbers for the same link.

What	Where it shows up
Total and unique clicks	Per link and org-wide
Country, referrer, device type	Per link and org-wide
OS, browser	Per link
UTM source, medium, campaign	Per link
Installs and conversion rate	Per link, once an app is registered

Two things hold regardless of what a link points at. The click-side numbers are recorded the same way whether the link is a bare web redirect or a deep link into a registered app, so you get real analytics on day one, before you have registered anything. And none of it is filtered after the fact: a bot's tap is caught before a click event is ever built, so the number you see is already the human number.

Why Link-Level Data Is Different From In-App Analytics

Link analytics and product analytics answer different questions, and mixing them up leads to disappointment on both sides. Link analytics is about the join: which link, campaign, or channel produced this click, and which install did that click cause. It stops at the app opening. Product analytics is about what happens next: screens viewed, features used, funnels completed, revenue and retention measured over time, inside an app you already got someone to open. WarpLink does the first job and deliberately does not do the second: there is no custom event tracking, no funnel builder, and no revenue or cohort data anywhere in the click pipeline. If you need both, you are looking at two categories of product that share one boundary, the install itself. Link analytics vs. product analytics walks through where that boundary sits and how the two fit together.

Reading Campaign Performance in Real Time

Clicks and installs appear as they happen, not on an hourly rollup or an overnight batch. A link shared at 9:00 already has numbers worth reading by 9:20, because there is no schedule sitting between a tap and its row landing in your dashboard.

The date range picker covers Today, 7, 30, and 90 days, plus a custom range, with hourly granularity available for Today and daily granularity everywhere else. How far back you can look depends on your plan: 90 days on Free, up to three years on Scale and Unlimited.

The click-to-install conversion rate lives in the trend chart, computed per day as installs divided by unique clicks. Read it as a shape across days, not a single figure: one day's rate can read above 100% when an install lands a day or two after the click that caused it, because attribution matches within a window and the two events do not always fall on the same calendar day. Trust the trend across a full campaign, not any single day's number.

Common Mistakes

Three mistakes account for most of the confusion teams report when they first look at their numbers.

Reading total clicks instead of unique clicks. Total clicks count every tap, including one visitor who taps a link five times testing it before sharing it further. Unique clicks, deduplicated per link, address, and 24 hour window, are the number that reflects actual reach. Use unique clicks to compare campaigns against each other, and total clicks only when you care about repeat engagement with one specific link.

Confusing a link's inbound UTM tags with UTM tags appended to the destination. Every click carries whatever UTM parameters arrived on the incoming request, so a link shared as ?utm_source=newsletter shows up correctly in your UTM breakdown. That is a separate mechanism from a link's own stored UTM fields being carried through to wherever it redirects to: they are not appended automatically today. If a UTM parameter needs to land at the destination, put it on the inbound share URL rather than relying on the link's saved settings alone.

Assuming bot traffic still needs filtering. It does not. Bot detection runs before a click is ever recorded, so there is nothing to subtract from your totals and no separate "bot clicks" figure sitting inside your numbers waiting to be excluded. If a count from WarpLink reads lower than a raw server log from somewhere else, that gap is very likely bot traffic the other log counted and WarpLink never wrote in the first place.

Setting It Up

Analytics needs no separate setup step. Create a link, in the dashboard or through the REST API, and clicks start recording the moment it goes live, with no app required.

To add installs to the picture, register an app under your organization and add the SDK to it. Once that is done, new installs from your links join automatically through the match cascade, and the install count and conversion trend appear on the same link you already created. Install attribution without an MMP covers how that match works end to end.

From there, the numbers are reachable from two places today: the dashboard, for the full breakdown by device, country, referrer, and UTM, plus CSV export; and an MCP client, for total clicks, unique clicks, the time series, and the source split, read straight from a script or an AI assistant. There is no public REST endpoint for analytics yet, so a full dimensional breakdown currently has to come from the dashboard or the export.

The analytics page covers the dashboard view in full, the analytics concept doc covers how the numbers are computed, and the install attribution page covers the join that puts installs next to clicks. Every plan, including Free, includes analytics: the free tier covers 10,000 clicks a month before new analytics is gated behind an upgrade, though your links themselves keep redirecting either way. Compare plans on pricing.

Frequently Asked Questions

What counts as a click in mobile link analytics? Any tap on your link that reaches a real visitor. Bot traffic is caught at the edge before a click event is ever built, so bot taps are never written to your numbers in the first place. There is no separate "bot clicks" count sitting inside your totals waiting to be subtracted, because nothing needs filtering after the fact.

How are unique clicks calculated? A click is unique per combination of link, visitor address, and a rolling 24 hour window, computed server-side at the moment the click is written. One person tapping the same link four times in an afternoon still counts as one unique click, so unique clicks are the number to trust for reach, while total clicks tell you how much repeat interest a single link is getting.

Does link analytics need the mobile SDK, or does it work for web-only links? It works without the SDK. A link is a smart URL shortener from the moment you create it: clicks, devices, countries, referrers, and UTM parameters are all recorded whether or not the link points at an app. Registering an app and adding the SDK unlocks one more layer, installs joined back to the click that caused them, but click-side analytics needs nothing beyond the link itself.

How is this different from product analytics? Link analytics measures what happens before and at the moment of the tap, plus the install it produced, and stops there. It does not track what a user does after your app opens: no custom events, no funnels, no revenue or retention curves. That is a separate category of product, and the two are complementary rather than overlapping. Link analytics vs. product analytics covers the boundary in full.

Can I export or query link analytics programmatically? Yes, in two ways. The dashboard exports raw click rows as CSV, org-wide or per link, including UTM term and content fields. An MCP client can call get_link_analytics for a link's total clicks, unique clicks, time series, and redirect-versus-app-open source split over the Model Context Protocol. There is no public REST endpoint for analytics today, so a full breakdown by device, country, referrer, or UTM currently has to come from the dashboard or the CSV export.

How WarpLink Helps

Mobile link analytics is not a bolt-on report. It is one of WarpLink's three pillars, deep linking, install attribution, and real-time analytics, all built on the same click a visitor generates the moment they tap. The linking pillar sends that tap to the right destination, the attribution pillar joins it to the install it produced, and the analytics pillar surfaces both as they happen instead of after an overnight batch.

Create a free WarpLink account and start reading device, country, referrer, and UTM breakdowns on your first link today, with 10,000 clicks a month on the free tier and no time limit on how long you can run it. Every plan, including Free, gets the same analytics; compare click ceilings on the pricing page.