It’s no secret the mobile app market keeps getting more competitive — hundreds of new apps hit the App Store every day, and standing out is more challenging than ever. User acquisition costs are going up, and platform algorithms are constantly shifting, making the game trickier for developers.

In a dynamic market like this, promoting your app in the App Store takes more than just running ads or updating metadata. You need a smart, well-rounded approach — and that means understanding how different marketing tools work together.

Two key tools that companies use to attract users are App Store Optimization (ASO) and Apple Search Ads (ASA). These channels can work well together — or compete with each other, leading to something called traffic cannibalization.

In this article, we’ll break down what traffic cannibalization is, how to spot it, how to measure it incrementality, and how to combine ASA and ASO for the best possible results when promoting your app.

Cannibalization vs. Protection Against Competitors

The image above shows two different scenarios. The green frames highlight cases where the Fax the Iphone appears twice in search results — both as a paid ad (ASA) and as an organic result (ASO). The orange frame, on the other hand, shows Fax the Iphone appearing only after a competitor’s ad.

In the first case, the app is protected — it shows up in both ad and organic placements, increasing the chances of a download. In the second, the app isn’t protected, which means users might end up downloading a competitor’s app that shows up first.

Now let’s look at a different situation — when the app you want to protect doesn’t look like a direct competitor to the one above it.

The green frames highlight Airbnb dominating the entire first screen, while the orange frame shows the second screen — where Airbnb disappears, and Holiday Lettings takes its place. While this means the second screen isn’t protected, Airbnb’s strategy still makes sense. Since this is a branded search, users are specifically looking for Airbnb by name, and given that Holiday Lettings is a different type of app, it’s unlikely those users would choose Holiday Lettings.

This raises a common question for popular apps: is it worth running ads to protect your top spot on the App Store if you’re already ranking high organically? And could those ads end up “stealing” traffic you would have gotten for free?

When paid ads start pulling in users who would have downloaded your app organically anyway, that’s called cannibalization.

The first step is to decide what matters most for your app — profitability or protecting your search results. One way to determine this is by analyzing your competitors. If their apps are very similar to yours, there’s a good chance they could attract your audience, even if users started by searching for your app. In that case, investing in ads to secure your placement can help prevent potential customers from drifting toward a competitor.

If your brand is well-known, users searching for your app are unlikely to be swayed by a competitor’s ad. In that case, you can skip protecting your placement and focus on other strategies to grow your traffic.

It’s also worth factoring in DEVELOPER and STORY cards and other elements that may show up in search and affect how visible your app is.

The smartest move is to evaluate each keyword and each country separately — then decide whether it makes sense to bid and protect your search results.

ASA Analytics vs. Search Traffic

The main metric to look at when analyzing search traffic is First-Time Downloads. You can find this data in App Store Connect under App Analytics — just apply the Source Type filter and select App Store Search. Keep in mind, this includes both organic installs and installs that came from Apple Search Ads.

To see just the downloads from ASA, check the New Downloads metric in your Apple Search Ads dashboard.

It’s important to understand the difference between these metrics:

• First-Time Downloads (App Store Connect) = Organic + ASA
• New Downloads (ASA) = Downloads from ad campaigns only
• Installs in ASA = New Downloads + Redownloads (when users reinstall the app)

To estimate pure organic traffic, you need to calculate New Organic Search Downloads:

New Organic Search Downloads = First-Time Downloads – New Downloads

This gives you a better picture of how many users found your app on their own — without ASA.

Incrementality vs. Cannibalization

When evaluating how well ASA is working, it’s not always clear if new downloads are actually driven by ads. Say your app normally gets 100 organic installs a day. After launching ASA, you’re seeing 50 extra installs. What does that mean?

Let’s take a look at the screenshot below.

We ran a simple experiment to see how ASA campaigns affect downloads. During the first week of September, we didn’t run any ads — just organic traffic, which held steady at around 100 downloads per day. On September 8, we turned ASA on, and the orange bars on the chart show the extra installs from those ads. Downloads jumped by about 50 a day. Two weeks later, we paused the campaign, and installs dropped back to where they were before.

So how do you tell whether it’s an incremental effect or just cannibalization?

• Incrementality means your ASA campaign brought in users who wouldn’t have downloaded the app otherwise.
• Cannibalization means ASA “took over” some of your organic traffic — users who would’ve installed the app anyway came in through paid ads instead.

In this case, we’re clearly seeing an incremental effect — the extra downloads only showed up after ASA was launched, and once ads were turned off, the numbers dropped back to 100. That means the campaign actually brought in new users, and cannibalization was minimal.

Now let’s take a look at a different scenario.

Here, the situation is completely different: after launching ASA, the total number of downloads didn’t go up — it stayed the same. But if you look at the chart, you’ll see the orange bars (ASA downloads) make up a big chunk of the traffic. Once ASA was turned off, the overall download count stayed right where it was before the ads.

This is a textbook case of cannibalization. ASA didn’t bring in any new users — it just redistributed traffic from organic to paid. Users who would’ve downloaded the app anyway ended up doing it through ads. In this case, your ASA budget isn’t adding real value — you’re basically paying for installs you could’ve gotten for free.

Here’s a more complex example.

In this chart, ASA installs alone aren’t enough to clearly say whether there’s cannibalization. The orange bars (ASA downloads) are much lower than the blue ones (organic), and organic traffic is all over the place — fluctuating by around 20 installs a day, while ASA is bringing in only about 10. That means ASA’s impact is smaller than the natural ups and downs of organic traffic. The signal (ASA) just gets lost in the noise (daily fluctuations), making it hard to draw any solid conclusions.

In reality, this kind of situation is common, and spotting cannibalization isn’t always easy. But there are a few things you can try.

First, you can increase your ASA traffic. The catch? You’ll need to target more keywords, which makes it a lot harder to analyze the results. Some keywords might show signs of cannibalization, while others could be driving a true incremental effect.

Second, you can try running ASA in a country where your app has very little organic traffic. If you’re able to launch a campaign in a region where downloads are close to zero — but the keywords are still relevant — it’s much easier to measure the true incremental effect. That said, this kind of experiment isn’t always possible. Some markets might simply not have enough relevant search queries.

Figuring out how well ASA is actually working isn’t always straightforward — it can drive new users or just shift your organic traffic to paid. One way to get clearer insights is by running campaigns in regions with low organic traffic, but that often means spending extra. If that’s not an option, step back and look at the bigger picture: analyze your overall download trends and consider all the factors that could be influencing them.