Mobile Attribution and MMPs Explained

I have spent a lot of years moving app budget around, and the single thing that decides whether that budget grows or gets cut is attribution. If you cannot say with confidence which channel drove an install and whether that user did anything valuable afterward, you are guessing. On mobile, attribution works differently than it does on the web, and the tool most teams lean on is called a Mobile Measurement Partner, or MMP.

In this post I want to walk you through how mobile attribution actually works, what an MMP does for you, and the pieces you will run into on your first app campaign: attribution windows, deterministic and probabilistic matching, deep links, Apple's SKAdNetwork, and in-app event postbacks. I will keep it practical and US-focused, the way I would explain it to someone joining my team.

Why mobile is different from the web

On the web, attribution mostly runs on cookies and pixels. Someone clicks your ad, lands on your site, and a pixel fires in the browser. The browser carries state, so you can stitch the click and the conversion together fairly easily. Mobile does not work like that. App installs happen inside the App Store or Google Play, not on a page you control, and the browser that showed the ad is a separate world from the app that gets installed.

So the industry built a workaround. When someone taps your ad, the ad network records the click along with device signals. When the app opens for the first time, a measurement tool inside the app records the install with its own signals. Something has to compare those two events and decide whether they belong together. That something is your MMP, and the comparison is what we call matching.

What an MMP actually does

A Mobile Measurement Partner is a neutral middle layer. You integrate its SDK into your app, and you connect it to every ad network you buy from. From then on it becomes the single source of truth for installs and events. AppsFlyer, Adjust, and Singular are the common names in the US market, and for a beginner they do broadly the same core job.

Here is what you get from having one in place:

• One dashboard for every channel. Instead of trusting each ad network's own numbers, you compare Google, Meta, TikTok, and Apple Search Ads side by side on the same definitions.
• Deduplication. Two networks will both claim the same install. The MMP applies attribution rules and gives credit to one, so you are not double-counting.
• Postbacks to networks. The MMP tells each ad platform which of its clicks turned into installs and events, which is how the platform's algorithm learns to find more good users.
• Fraud protection. Most MMPs filter out obvious click spam and fake installs before they pollute your reporting.

The reason the MMP is neutral matters. An ad network grading its own homework will always look good. A third party using consistent rules is what lets you make honest budget calls.

Windows, deterministic vs probabilistic matching

Attribution windows are the time limits for giving credit. A click has a lookback window, often 7 days, meaning if the install happens within 7 days of the click, that click can get credit. There is usually a shorter window for view-through (someone saw the ad but did not tap). You set these, and they directly change who wins credit, so keep them consistent across channels or your comparisons fall apart.

Matching comes in two flavors. Deterministic matching uses a hard identifier that appears on both the click and the install, so you know it is the same device. It is precise. Probabilistic matching uses softer signals like IP address, device type, and timestamps to make a statistical guess. It is less precise and, importantly, Apple restricts it. Deterministic is what you want when you can get it, but privacy changes have made it harder to rely on, which brings us to iOS.

SKAdNetwork and iOS privacy in plain English

A few years ago Apple decided users had to opt in before an app could access the device identifier used for tracking (the IDFA). Most people say no. That broke the clean deterministic matching everyone relied on for iPhone campaigns, and it is the single biggest shift in app marketing this decade.

Apple's answer is SKAdNetwork, or SKAN. Instead of you matching individual users, Apple does the attribution itself and hands back a privacy-safe postback with no user-level detail. You get counts and a coarse conversion value, usually on a delay, and often with thresholds that hide small numbers. The practical takeaway: on iOS you plan around aggregated, delayed, less granular data, and you lean on your MMP to organize SKAN alongside your regular reporting. On Android the older device-identifier model still largely works, though Google has its own privacy roadmap moving in a similar direction.

You do not need to memorize the SKAN internals to start. You just need to expect that iOS numbers arrive slower and blurrier than you are used to, and that this is normal, not a bug in your setup.

Deep links, in-app events, and where budget goes

Deep links send a user to a specific place inside your app rather than a generic home screen. Deferred deep linking is the useful version for acquisition: someone taps an ad for a specific product, does not have the app yet, installs it, and lands directly on that product instead of starting from scratch. Your MMP handles the handoff so the context survives the install. Better first impression, better conversion.

Installs are only the start. What you really care about are in-app events: signups, trials, subscriptions, purchases. You define these events, the MMP records them, and it sends postbacks to the ad networks so their algorithms optimize toward the events that make you money, not just cheap installs. This is the whole game. A channel with cheap installs and no purchases is a channel you shrink, and a channel with pricier installs that turn into paying users is where you scale. Clean event attribution is what lets you tell those two apart, and if you want the deeper economics behind that call, my post on LTV and CAC covers it.