Link Analytics vs. Product Analytics: What's the Difference

TL;DR: Link analytics measures the tap: who clicked, when, from what device and referrer, and whether it opened the app or a web page. Product analytics measures what happened after: which screens someone visited, which features they used, whether they came back. Install attribution is the join between them, matching a fresh install to the link that caused it. A small mobile team should start with link analytics, because it is already part of the SDK doing deep linking and attribution, and add a product analytics suite once there is in-app behavior worth studying. WarpLink covers deep linking, install attribution, and real-time link analytics in one SDK.

Link Analytics: Before the App Opens

Link analytics answers a narrow, specific question: what happened when someone tapped a link.

It starts at the click itself, before an app has to load, sometimes before the app is even installed. That is what makes it the right layer for measuring acquisition traffic: a link click can turn into a web page view, an app open, or an app store install, and link analytics has to account for all three without assuming any of them happened.

The measurements that fall under link analytics are:

• Total and unique clicks, per link and organization-wide, with unique clicks deduplicated on a rolling 24-hour window so the same visitor tapping twice does not inflate the count.
• Where the click came from: referrer, device type, browser and OS, and country, broken down per link in the dashboard.
• UTM parameters on the click itself, captured from the query string on the short link and shown in a breakdown by source, medium, and campaign.
• Whether the click resolved to an app open or a web redirect, a source split that matters once a link serves both an app and a fallback page.
• Installs attributed to the link, and the click-to-install conversion rate that follows from it.
• A time series of activity, by day or, for the current day, by hour, over ranges from today through 90 days or a custom window.

None of it requires a script running inside the app or a page load to fire. Link analytics watches the edge of the funnel: the tap and, if attribution is wired up, the install that followed it.

Product Analytics: After the App Opens

Product analytics starts where link analytics stops: the first time the app is actually open and running.

A product analytics suite is built to answer a different set of questions. What screens did this person visit, in what order. Which feature did they try, and did they come back to it. How many users from a given week are still active a month later. What is the revenue or lifetime value attached to a cohort. These are in-app behavior questions, and answering them requires instrumenting the app itself: named events, screen views, user properties, funnels defined across multiple steps.

Side by side, the split looks like this:

	Link analytics	Product analytics
Starts measuring at	The tap on a link	The first app open
Reports	Clicks, referrer, device, country, UTM source, app open vs. web redirect, install count	Screens viewed, feature usage, funnels, retention curves, revenue and lifetime value
Needs an app to be open	No	Yes
Requires custom event instrumentation	No	Yes

Where the Two Meet

The two systems meet at exactly one point: the install.

Install attribution is the mechanism that connects a click on one side to an app open on the other, using whatever signal is strongest for the platform: the Play Install Referrer on Android, the vendor identifier on iOS, and a probabilistic match key as a fallback when neither is available. That match is what turns "someone tapped this link" and "someone opened this app for the first time" into a single fact: this install came from this link, this campaign, this channel.

That fact is the handoff. A product analytics suite picks up from the first app open forward. Everything it reports, from the first screen viewed to a cohort's retention curve six months later, is grounded in a user who exists because of an install, and that install traces back to a click that link analytics already measured. Neither system needs to duplicate the other's job. Link analytics owns the acquisition side of the join; product analytics owns everything downstream of it.

Teams pull link and click data into a product analytics suite on a schedule they choose. WarpLink exports it as CSV, and GET /v1/analytics or an MCP client's query_analytics tool reads breakdowns, filters, and period comparisons directly.

Which One a Small Mobile Team Needs First

For a small team, the answer is link analytics first, and by a wide margin.

Link analytics is close to free to have, in the sense that it rides along with the deep linking and install attribution most mobile teams already need. There is no separate SDK to wire up and no event schema to design before the first number shows up: a link goes live, someone taps it, the click and, later, the install are already there. It answers the question every early-stage team actually has first, which channel, campaign, or share is working, before anything in-app is complex enough to be worth instrumenting.

Product analytics earns its cost once there is behavior worth studying: multiple screens, a funnel with real drop-off, a retention question that matters because there is a cohort large enough to have a curve. Standing that up before there is meaningful in-app behavior to measure is instrumentation for its own sake. The two are not a choice between one or the other forever, either. Most teams that outgrow "which link worked" keep link analytics running for acquisition while adding a product analytics suite for everything that happens after the app opens, because each one is the better fit for its half of the funnel.

What WarpLink Reports

WarpLink's analytics cover the link side of that funnel: total and unique clicks, referrer, device, browser, OS, and country breakdowns, UTM source and medium and campaign, the app-open versus web-redirect split, installs attributed per link, and the click-to-install conversion rate, all in the dashboard. Totals, unique clicks, a time series, and the source split are also reachable via CSV export or an MCP client. Retention follows the plan, from 90 days on the free tier up to three years on the higher tiers.

WarpLink's analytics cover the acquisition side of the funnel: deep linking, install attribution, and real-time analytics. See what WarpLink measures for the full picture, the analytics concept page for how the numbers are computed, and Mobile Link Analytics: What to Track and Why for a deeper look at the link side alone. For the mechanism that joins a click to an install, see Install Attribution Without an MMP. Plan limits and retention windows are on the pricing page.

Frequently Asked Questions

Is link analytics the same as web analytics? No. Web analytics is a browser-based practice: a script on a page reports page views, sessions, and on-site behavior for visitors who load that page. Link analytics starts one step earlier, at the tap itself, and it has to work whether that tap opens a browser, opens an app, or triggers an app store install. It reports who tapped, when, from what device and referrer, and whether the tap resolved to a web page or an app open. Link analytics does not need a page to load first, which is what makes it the right layer for measuring the traffic around an app.

Do I need product analytics if I already have link analytics? Product analytics adds the in-app view once you have users worth studying. Link analytics tells you which channel, campaign, or share drove a tap and, when the tap led to an install, that the install happened. What a person does after that, which screens they visit, which features they use, whether they come back the next day, is a separate question that a product analytics suite is built to answer. The two cover different halves of the same funnel.

Can link-level data feed my product analytics tool? Yes, through CSV export, a REST call, or an MCP client. WarpLink's dashboard exports raw click rows to CSV, org-wide or per link, and a REST call or an MCP client can pull totals, unique clicks, a time series, source split, and dimension breakdowns like country and device. Joining link-level data into a product analytics suite is a pull you run, on a schedule you choose.

How does WarpLink fit with a product analytics tool? Teams pair WarpLink with the product analytics suite they already use.

What does WarpLink cover that a plain link shortener doesn't? A plain shortener stops at the redirect. WarpLink adds install attribution, so a click that led to a fresh install is matched back to the link that caused it, and analytics built for that match: unique clicks over a rolling 24-hour window, the install count and click-to-install rate per link, and a source split showing whether a tap resolved to an app open or a web redirect. A shortener tells you a link was clicked. WarpLink tells you what the click turned into.

To compare link analytics services on what they measure and charge, see 5 Mobile Link Analytics Services Compared sets click data, install matching, exports, and published pricing side by side for five services.

How WarpLink Helps

WarpLink covers deep linking, install attribution, and the real-time link analytics built on top of both. It answers which link, campaign, or share drove a tap and the install that followed.

Create a free WarpLink account and see the click, source, and install data for your own links today, with 10,000 clicks a month on the free tier and no time limit. Plan limits and retention windows are on the pricing page.