Android-First Apps: Do You Still Need SKAN?

Short answer: you need SKAN (and its successor, AdAttributionKit) if you buy iOS installs on any ad network other than Apple Ads, however small iOS is in your install mix. You do not need it for organic iOS installs or for Apple Ads, which attributes through AdServices. Your iOS share decides how much schema work to do, not whether to do it.

Picture a growth team at an Indian fintech app. Android is most of the installs, the iOS app exists mainly for credibility, and the backlog already has deep link bugs and a Meta event audit on it. Then someone asks whether the team needs a SKAN conversion value schema. The honest answer is "it depends on one thing", and it is not the platform split.

How Android-first is a typical Indian app?

Very. In Linkrunner's State of Mobile App Growth: India 2026 report, which covers 77 India-based app startups and about 25M installs, nearly 9 in 10 installs were on Android and roughly 1 in 8 were on iOS. The report publishes install share only, not iOS share by category, and the spread between individual apps is wide.

The exact figure depends on the sample, but the direction does not: for most Indian apps, iOS is a minority platform. If you are still choosing tools for that reality, our ranking of the best MMP for Android-first apps covers the Android side.

What does SKAN actually measure?

SKAN attribution is Apple's privacy-preserving way of crediting iOS installs from ads to the ad network that showed them, using delayed, aggregated postbacks instead of user-level data. AdAttributionKit is its successor and interoperates with it.

What follows from that definition:

• It only measures installs from ads. Organic iOS installs never produce a SKAN postback.
• It works without tracking consent. Apple's AdAttributionKit documentation says apps can call its attribution APIs regardless of their tracking authorisation status, which is exactly why ad networks lean on it for users who decline ATT.
• In-app quality travels as a conversion value: a number you set as the user engages, which the network receives later in a postback.

So the question "do we need SKAN?" is really "do we buy iOS installs from networks that measure with it?"

When do you need SKAN or AdAttributionKit?

Why the paid-network rows are a firm yes:

• Meta. Meta's developer documentation says iOS 14 app ads can only be created in ad sets under SKAdNetwork campaigns, and campaign attribution must be set to SKAdNetwork or Aggregated Event Measurement. You cannot run them without choosing one.
• Google. Google Ads help describes setting up a SKAdNetwork conversion value schema for in-app event measurement in iOS App campaigns, through Google Analytics, an app attribution partner or the Google Ads API, and recommends picking one place to manage it.
• Optimisation. Without conversion values, the network only sees installs from users who declined tracking. It optimises towards cheap installs, not users who sign up or pay.

Why install share is the wrong test

Teams often skip SKAN because "iOS is only a small slice". That reasoning breaks in three ways:

• A small budget still needs a signal. Even a modest iOS test on Meta spends money against a target the network cannot see without conversion values.
• iOS users can be worth more. A small install share can still be a larger share of revenue. Check your own revenue split by platform before deciding iOS does not matter.
• Retrofitting costs more. Meta notes that once an SKAdNetwork campaign is live, you cannot edit its promoted object or its SKAdNetwork flag. Setting things up after launch means rebuilding campaigns.

The share still matters for depth. Our SKAN postback intensity benchmark argues that if iOS is under around 5 per cent of your installs, the engineering hours spent on a fine-grained schema for the third postback need a clear return. Start lean and grow the schema with the budget.

What goes wrong when Android-first teams launch iOS ads

A pattern in Linkrunner's support conversations: most SKAN questions are not about conversion values at all. They fall into two buckets.

• Expectations. Teams expect user-level data, deferred deep links or event-level attribution from SKAN. It provides none of these. It is aggregate and delayed by design, and Meta's documentation says deferred deep linking is unavailable for new iOS 14 SKAdNetwork campaigns.
• Missing prerequisites at launch. Ad network IDs missing from Info.plist, no postback copy endpoint, Meta SDK events not firing, or the schema never copied into Meta.

Both are cheaper to fix before the first rupee of iOS spend than after.

A lean SKAN setup for Android-first teams

If your table row says yes, this is the minimum viable setup:

1. Add the ad network IDs for every iOS network you buy from to Info.plist. Your MMP SDK or the network's docs list them.
2. Set the postback copy endpoint so your MMP receives a copy of winning postbacks.
3. Map three to five events to conversion values: install, sign-up, first purchase or a revenue bucket. Keep it simple until iOS spend justifies more.
4. Use the same schema everywhere. Copy it into Meta and Google so all three agree on what each value means.
5. Check Meta's campaign settings: SKAdNetwork or Aggregated Event Measurement, chosen before launch.
6. Wait before judging. Postbacks arrive with delays. Read results across days, not hours.
7. Plan for AdAttributionKit. Apple Ads registered with AdAttributionKit in April 2025, and the two frameworks interoperate. Our comparison of AdAttributionKit vs SKAN explains what changes.

How Linkrunner handles this

Linkrunner is a mobile and web attribution platform (the Web SDK is in beta), India-first, with rupee pricing and local support:

• SKAN is included on every plan, with a SKAN 4.0 wizard for conversion values and support for AdAttributionKit, so a lean iOS setup does not need a separate tool or a higher tier.
• Android stays deterministic first, with IP and user-agent matching only as a fallback when no deterministic signal exists.
• iOS channels sit in the same dashboard, including Apple Ads (formerly Apple Search Ads), Meta, Google and TikTok.
• Pricing follows attributed installs: 25k one-time free installs, then ₹1.20 down to ₹0.80 per attributed install on the INR card, postpaid. The SKAN dashboard docs show how postbacks are reported.

FAQs

Do I need SKAN if I only run Android campaigns?

No. If you buy no iOS installs from ad networks, SKAN has nothing to measure. Keep the iOS SDK installed for organic installs, deep links and events, and skip the schema work.

Does Apple Ads use SKAN?

Apple Ads attributes installs through AdServices, which returns campaign, ad group and keyword data at first launch. Apple Ads also registered with AdAttributionKit in April 2025, but you do not need a SKAN schema to attribute Apple Ads installs.

Is AdAttributionKit replacing SKAN?

It is Apple's successor framework and interoperates with SKAN; our AdAttributionKit primer covers what it adds. Most teams run both through their MMP, and a SKAN 4 conversion value schema carries over as a starting point.

What iOS share justifies a full conversion value schema?

There is no fixed threshold. As a rule of thumb, start with a lean schema whenever you buy iOS installs, and expand it when iOS becomes a dedicated budget line or a clearly higher-value segment.

Can SKAN give me user-level iOS data?

No. SKAN postbacks are aggregated and delayed, and do not include user or device identifiers. For user-level iOS journeys, use web-to-app flows or channels with deterministic data such as Apple Ads.

The rule in one line

Set up SKAN and AdAttributionKit before you spend on iOS ads with any network other than Apple Ads, and let your iOS revenue, not your install share, decide how detailed the schema gets. If you want SKAN and Android attribution in one place without paying for a higher tier, request a demo of Linkrunner and run the seven-step setup above before your first iOS campaign.