Seven Ways to Optimise ASO and ASA Strategies in the Age of AI-driven App Discovery

If you’ve been in app marketing for any length of time, you know the landscape doesn’t stand still. App Store and Google Play algorithms are constantly evolving, user behaviour shifts, and strategies that worked last quarter can lose effectiveness overnight.

We spoke with Product Madness' ASO & ASA Manager, Ezgi Ergüney, about how to detect algorithm changes early, how to push A/B testing beyond surface-level experimentation, and the ways AI is reshaping metadata localisation.

She offers her seven key steps on how to get the most out of ASO and ASA strategies, below.

1. Monitor daily performance metrics and run continuous tests

If there’s an algorithm change, I usually spot it early just by seeing shifts in performance metrics. Daily data monitoring and continuous testing are crucial for detecting these changes. ASO tools also provide alerts, but real insight comes from actively engaging with industry experts and ASO communities. If you're keeping your ear to the ground, it’s almost impossible to miss an update. Algorithm shifts have become one of the biggest factors impacting ASO strategy, so being able to react fast is key.  

Focusing on product performance and conversion, rather than just keyword optimization, is becoming increasingly important for long term success. Recently, app stores have placed a greater emphasis on user engagement, conversion, and overall app quality. Apps with high retention, low ANR (App Not Responding) rates, and strong engagement are more likely to benefit from algorithm changes rather than suffer from them.  

There’s a lot happening in the ASO world right now, especially with the rise of AI. But one of the biggest game changers has been the use of Custom Store Listings, Custom Product Pages, and Promotional Contents. They allow for better audience segmentation, improving conversion rates with tailored messaging. Deep linking further enhances the user journey by directing users to where they need to be. As app stores continue refining personalization and user experience, ASO is shifting beyond rankings to focus on creating seamless, engaging experiences for different audience segments. This not only improves conversions and engagement but also sends strong positive signals to the algorithm and drives long-term organic success.  

2. Test and then retest to get a solid ASO strategy

A/B testing and data analytics are the backbone of a solid ASO strategy. Instead of relying solely on Google Play Console and App Store Connect experiments, we extend our testing to paid traffic to understand how different user segments interact with variations. This approach allows us to compare performance across organic and paid channels, and help us to refine our strategies more effectively.

Our primary focus is conversion and engagement metrics. When a test has a clear winner, we implement it. If results are inconclusive, we analyze the data to refine and retest. Paid traffic tests provide richer insights compared to console experiments, as they allow for quicker validation and a deeper understanding of user behavior. 

Once we roll out a winning variation, we monitor rankings, conversion rates, and retention to measure its impact on both organic and paid channels. It’s a continuous process of testing, learning, and improving to stay competitive in the market.

3. Balance ASA & ASO for unified growth

Here’s the million dollar question! The key to aligning Apple Search Ads with ASO is finding the right balance and leveraging paid visibility without overshadowing organic growth. We continuously track performance and adjust our approach, to ensure that ASA and ASO work together and strengthen overall visibility rather than competing against each other.

Instead of aggressively bidding on keywords that already drive strong organic installs (unless it's part of your brand defense strategy), it's more effective to focus on keywords where ASA can provide the most value and visibility. ASA provides valuable insights for user engagement and keyword performance. High engagement terms would help your app to improve discoverability when used in metadata.  

However overbidding can sometimes hurt conversion rates rather than help them, so be careful monitoring! 

4. Continuously test creatives against UI changes

Regular experimentation helps a lot to refine hypotheses and understand what resonates with our users. Through testing, we are able to make data-driven decisions and iterate based on user behavior. 

One of the key factors in successful ASO creative testing is staying ahead of platform UI changes and ASO trends. App store layouts evolve, and what worked yesterday might not be as effective today. For example, with recent UI updates on Google Play search results, icon optimization has become more critical than ever, as it’s the most visible asset on search results and directly impacts conversion rates. The key is to test, analyze, and continuously refine to stay ahead of changing trends and user preferences.

One of our biggest wins came from adapting to these changes. Icons proved to be the most impactful asset when we aligned visuals more closely with user expectations. Even small tweaks can make a big difference when guided by strong data insights so keep testing. 

5. Leverage AI for region-specific localization

AI has completely revolutionized localization! It made it much faster and easier to generate meta data and ensure a more natural language flow. If you’re not using AI for localization, you’re already falling behind. But localization is more than just translating keywords, it’s about understanding how players search in different regions and optimize accordingly. Competitor research plays a huge role in this. It helps us see what’s working in each market, spot trends, and gather insights for creative strategies. 

One of the biggest challenges was the platform limitations when testing creatives for specific regions. Google Play’s Custom Store Listings have been a game changer when scaling our games globally. It lets us create region specific product pages and test different creatives for each market, language or user state. This makes it much easier to analyze user behavior and shape our approach based on how players engage with our game in different regions. 

The App Store on the other hand has more localization limitations. Unlike Google Play, where we can run direct A/B tests by region through CSL’s, Apple’s Product Page Optimization (PPO) tests only allow testing by locale, which isn’t always helpful for measuring impact in specific countries. That’s why we often rely on paid traffic tests to understand how ASO changes affect different markets.

6. Leverage BI to lead ASO innovation

We use a wide range of BI tools to track and analyze ASO & ASA performance, and I have to say, Product Madness provides incredible resources in this area. This level of support allows us to stay ahead of the competition and continue leading the way in ASO and ASA. I’m really proud of how my team and company approach this. It’s not just about following trends but setting them. We’re always keeping up with the latest ASO innovations, staying on top of trends, and constantly testing new ideas. Our partners provide us with valuable insights and competitive analysis which is a huge advantage especially when working in a highly competitive market. 

That said, we don't just follow competitors. Instead, we focus on deeply understanding industry trends and, most importantly, our players, what resonates with them, what drives engagement, and changes in their behavior. Through continuous testing and analysis, we craft strategies that connect with our audience. We’re always tuned into social casino industry trends and ready to adapt quickly to new features of app stores. Instead of following others we focus on being the first to implement new opportunities, which often leads to others following us instead. 

7. Automate ASA campaigns with machine learning

Thanks to machine learning, optimizing ASA campaigns has become much easier and faster. Before, we were spending hours just adjusting everything, especially when scaling globally or managing tons of campaigns. Automation has taken a huge chunk of manual work off our plates so we can focus more on big picture strategies instead of getting lost in the details. ASA tools have evolved a lot with a strong focus on automation, which allows us to set up different targeting strategies exactly how we want, making the process more efficient than ever.

It also helps us to make better creative decisions. ML analyzes conversion rate trends from store listing A/B tests and predicts what users are most likely to engage with, giving valuable insights into their preferences and helping us make decisions much faster. So it makes the entire user journey from ad impression to install smoother and far more effective.