How to leverage Apple Search Ads post-install data to increase the quality of your organic traffic

Aude Boscher

Sep 26, 2019

Apple Search Ads is often only thought of as a paid search tool, but the platform can have a big impact on your organic activity too. As the only place that provides keyword-level data for the App Store, Apple Search Ads represents a huge opportunity for marketers to get insights on app performance per keyword, an essential device in the app marketer’s toolkit.

However, Apple Search Ads contains some gaps which you can fill in with Adjust’s post-install data. For instance, Apple Search Ads doesn’t provide marketers with information on the quality of the users brought in when you compare one key term to another. This is where Adjust, which displays Apple Search Ads data on keyword-level, shines.

Marketers can combine Adjust and Apple data to make more informed decisions on which keywords to focus on, and it’s a capability we at Phiture frequently tap to improve traffic quality. Here are our top three tips to using the data.

Tip #1: Evaluate the potential of targeting competitive versus generic keywords

One common ASO tactic we see is including competitors’ name in the App Store keyword set. It might seem like a smart idea that could lead to a few extra installs but, in reality, your Apple Search Ads Console conversion rate will probably indicate that the conversion for competitive keywords is lower than for relevant generic keywords.

Imagine a scenario where a user searches for a brand term, such as [Doordash]. There’s a much higher likelihood that this is a ‘navigational’ query, and not a ‘discovery’ query, as a term such as [food delivery] might be. An equivalent organic ranking for both these types of keywords is not worth the same in terms of downloads.

You might still think that including your competitors’ keywords is worth the hassle — it could even be driving a large amount of traffic to your app. But think again. Looking at our clients' data, we discovered that even if the Apple Search Ads competitive campaigns were able to generate significant install volumes, the quality of this traffic is lower — meaning retaining less well and generating less revenue for our clients.

The console provided by Apple for Search Ads keeps marketers in the dark about post-acquisition metrics. So you need to use an MMP such as Adjust in order to look at post-install metrics. Use these to deep-dive into your competitor keywords, and check on keystone metrics such as LTV.

Tip #2: Prioritize and target the right search terms

A standout feature of Apple Search Ads allows you to run ad groups with ‘Search Match’ enabled. ‘Search Match’ allows Apple to automatically match user searches with your app when the algorithm thinks it will be a "relevant" result.

This tool can help you find new keywords that you're not yet exploiting in your ASO strategy. While the search volume won't always be high, new keywords are always useful to have — informing the different intents your personas may have when looking for similar apps.

Speaking of personas, you can also split your ad groups by country, age or sex. This information helps understand which audiences convert better per keyword (or globally on a specific intent), and can lead you to experiment with the "tone" of your app page to adapt it to the best-performing audiences. It also helps you understand which features you should focus on most. (For example, if you have a notes app and you see that calendar features are most searched for, you may want to change the order of the screens on your App Store page.)

But don’t define your user acquisition strategy based on short-term metrics and conversion events. Instead, it’s best to think of engagement and retention as the end game of your activity.

By looking at cohorts in Adjust’s dashboard (per week or month) you can easily see which campaign, ad group and keyword bring in the best-retaining users. This informs how well the intent and actual experience align. To improve this process, ask questions like "What are the intents that are the most aligned with long term retention?" or "is the rework of our feature actually impacting retention for users that are searching for this intent?"

From these learnings, you'll be able to make adjustments in your product strategy. For example, making sure that users searching for a specific intent can actually easily get the value they're seeking in their first sessions.

Tip #3: Tie these findings into your conversion rate optimization (CRO) strategy

If you find specific keywords have better metrics, then it’s a no-brainer to include them in your listing copy. In the example below, Lifesum, BetterMe and 8fit all talk about their benefits differently: diet, weight loss, nutrition. But which term drives the best users?

Apple Search Ads creative sets can be used to test out what works. This process normally helps performance marketers optimize their paid App Store Search presence, but they also give ASO practitioners unique insights which can be applied to their store listing.

For example, we’ve worked with an app that released a new feature that helped users to make better eating choices. The easiest way to “test” creatives on the App Store was to release new assets and compare conversions before and after the update. However, this technique didn’t give us a good understanding of the true impact of the update per cohort. Using Apple Search Ads creative sets in various ad groups helped us better understand the impact promoting this feature would have on their most valuable target user — the ones finding the app searching for [workouts] for instance. This new feature resulted in positive impact in these particular ad groups, while it had a negative impact on lower-value search terms.

Final thoughts

Analyzing the traffic going to each Apple Search Ads keyword is a useful proxy to understanding your organic search traffic. It is an important step toward prioritizing the right search terms in your metadata and creatives to improve the quality of your users. Tying your keyword with campaign learnings will also help you decipher the store's algorithms.

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