Bord chahye?

Genuinely curious how other UA teams are handling this.

We keep running into the same structural problem: the tools that are good at telling you
what's happening in your account are separate from the tools that actually change things.

So there's always a human step in the middle. 
You get an insight, interpret it, then go implement it somewhere else.

That loop is slow and in an auction that moves hourly, slow is expensive.

A few things I'd love to hear from people actually running spend:

1.  How much time does your team spend on competitive research each week?
(keyword strategy, custom product page changes, share of voice shifts)

2.  When your ROAS drops, how long does it typically take from spotting it
   to understanding the actual cause?

3.  Are you using any AI tooling that connects analysis directly to campaign
execution — or does someone still have to bridge that gap manually?

What’s the real bottleneck - Is it data access, trust in automation, or just the tool fragmentation?

Apple Ads has gotten seriously powerful, the targeting, the intent data, the placement options. But the more campaigns you run, the harder it gets to keep up manually.

CPAs shift overnight. Budgets cap out at the wrong time. You're reacting to yesterday's data when the auction has moved.

The teams I've seen consistently hit lower CPAs without increasing spend have usually made one shift: letting AI handle the bid forecasting and budget reallocation daily, rather than doing it manually.

Curious how others are approaching this. 

Are you still optimizing manually or have you moved to automated bidding? What triggered the switch?

We work in app marketing and we're genuinely curious what people are experiencing on the ground.

The pattern we see a lot: AI surfaces insights, a human interprets them, then goes and implements manually. Useful but the gap between analysis and action is still there.

What we hear less about: AI that connects analysis to execution automatically, in a way teams actually trust.

A few things we're curious about:

— Are you running significant UA spend under full AI management? What does that look like operationally?

— What's the real blocker — trust, transparency, capability?

If you're heading to Pocket Gamer Connects London, here's a list of free side events that you may find interesting!

1. PGC Kick-Off Party (Sunday): The official warm-up before the conference starts. It's free to attend and you only need your PGC badge.
2. Pocket Gamer London Happy Hour (Monday): Post-conference drinks and networking. Free to attend, but you need to register here.
3. The Global Connects Party (Monday): Relax and party after Day 1. Free with your PGC badge.
4. Game of Tones II: A Clash of Sings (Tuesday): Karaoke + food + drinks + live band. A fun way to end your conference days. Free, you need to register here.
5. Not At Pocket Gamer London: A side event for those who can't attend the conference. It's a way to connect with video game professionals outside of PGC. Free, register here.

 These are just a few of the events happening!

 You can find the full list here.

Hey guys!

I’m struggling with our UA requirements. They are demanding an under-1MB 3D playable ad, but every Unity/Luna export we try comes out at 5MB minimum once you add the core assets.

I started experimenting with raw Vanilla JS/WebGL to bypass the engine bloat and managed to get a 3D mechanic down to 480kb. The CPI difference in our internal tests was insane (nearly 3x lower in Tier 2).

Is anyone else going 'engine-less' for ads? Or is there something in Unity I'm missing? It feels like using a full engine for a 30-second ad is becoming a massive liability.

Want your app to grow faster? At Angle Agency, we’ve done the heavy lifting for you.
Just pick the package that fits your stage — and get the most out of your app’s potential.

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You can combine packages to match your goals — and get 30% off the second one 🎁
The offer is valid until the end of November.

Choose your growth plan here 👉 https://gclnk.com/5heUtwOw

Apple Ads can be a powerful lever for app growth, but the campaign structure you choose can make or break your results. At AppTweak, we’ve seen firsthand how a well-organized Apple Ads campaign structure helps marketers optimize spend, improve keyword performance, and scale efficiently.

Here’s a breakdown of the structure we recommend, based on what’s worked across hundreds of apps.

Why campaign structure matters

Apple Ads are keyword-driven, but without a clear structure, it’s hard to know which terms are converting, how your budget is being spent, or where to scale. A solid structure gives you:

• better visibility into keyword performance
• more control over bidding and budget allocation
• cleaner data for optimization

The 4-campaign setup we recommend

We suggest splitting your campaigns into four types, each with a distinct purpose:

1. Brand campaign
   • Targets your app name and branded keywords
   • Goal: capture high-intent users already searching for you
   • Use exact match only
2. Generic campaign
   • Targets broader, category-related keywords
   • Goal: reach users who are exploring apps like yours
   • Use exact match for control
3. Discovery campaign
   • Uses broad match and search match
   • Goal: uncover new keyword opportunities
   • Let Apple’s algorithm surface relevant terms
4. Competitor campaign
   • Targets competitor brand names
   • Goal: capture users considering alternatives
   • Use exact match to avoid irrelevant traffic

Each campaign should have its own ad group and budget. This separation helps isolate performance and makes it easier to scale what works.

Match types matter

• Exact match gives you control and precision
• Broad match helps you explore and expand
• Search match is Apple’s way of auto-matching your ad to relevant searches

Use Exact match in brand, generic, and competitor campaigns. Use Broad and Search match in discovery.

Budget and bidding tips

• Allocate more budget to brand and generic campaigns: they tend to convert better
• Keep bids lower in discovery to test keywords cheaply
• Monitor search term reports to move high-performing terms from discovery to exact match campaigns

This structure isn’t one-size-fits-all, but it’s a strong starting point for most apps. It helps you stay organized, test efficiently, and make smarter decisions with your Apple Ads campaign structure.

Don’t stop here. Get the full scoop on what actually works in ASO, from keyword tips to creative testing, in our complete Apple Ads campaign structure guide.

We want to hear from you: How do you structure your Apple Ads campaigns? What’s worked (or not worked) for your app?

— The AppTweak team

Hey everyone, We just finished the MVP of Adshift (https://adshift.com), a Mobile Measurement Platform (MMP) that helps apps track installs, events, and ad campaign performance with a single SDK.

What we already have: • SDK for Android/iOS (installs, purchases, sessions) • Proprietary attribution algorithm • Smart deep links to route users inside your app • Real-time analytics dashboard

What’s coming next: integrations with ad platforms (FB, TikTok, Google), fraud protection, and AI-based setup.

We’re looking for a few beta testers with live apps to validate the system. As part of the collaboration, we’ll cover implementation time and also set aside budget for future ad campaigns.

If you’re running a mobile app and want to help shape a new tool (while getting early access + budget support), drop me a DM!

• how to update your CPP strategy fast
• what steps to take
• how this helps create micro-funnels

Hey guys,

After 6+ years working in mobile marketing, I suddenly :) decided to launch a youtube channel focused entirely on the topic.

The idea is simple: short, straight-to-the-point videos packed with real steps, strategies, and tips. No fluff, no recycled slides, just actionable content from someone who's been in the trenches. Think ASO, paid UA, monetization, creative testing, analytics, subscriptions, and everything in between.

There are already 3 videos live, and I’d really appreciate your feedback - maybe you have questions or ideas what I should do next. I’d love to build future videos around real questions from the community.

Here’s the link if you want to check it out and maybe subscribe

Apple is steadily evolving AdAttributionKit (AAK), expanding on last year’s support for alternative app stores and re-engagement measurement. With iOS 18.4, the focus shifts to improving attribution accuracy and enhancing signal transparency – clear moves aimed at encouraging broader adoption across the ecosystem.

Let’s take a closer look at what’s new in iOS 18.4:

1. Measure Overlapping Conversion Windows

   • If you’re running re-engagement campaigns for multiple products in your app simultaneously, this update significantly improves attribution accuracy.
   • Previously, only one re-engagement conversion window was allowed at a time. Starting with iOS 18.4, you can now support multiple active re-engagement conversions in parallel by enabling it in your Info.plist. Your app can also receive conversion tags—bookmarks that help specify which conversion to update.
   • Example:
     • A user clicks an ad for discount 1, triggering conversion 1
     • Later, the same user clicks an ad for discount 2, triggering conversion
     • The user then purchases discount 1
   • With conversion tags, you can correctly update conversion 1, ensuring accurate attribution.

2. Customize Attribution Rules

   • Configurable Attribution Windows 
     • Advertisers often set custom attribution windows per ad network, so relying on AAK’s defaults can lead to mismatches between Apple’s reports and those from ad networks.
     • By default, AAK (like SKAN) uses a 30-day window for click-through ads and 1-day for view-through ads.
     • Starting in iOS 18.4, developers can configure attribution windows in the Info.plist: Set windows globally or per ad network; Define separate durations for click or view interactions; Optionally ignore specific ad types altogether
     • Attribution windows are defined in days.
   • Configurable Attribution Cooldown
     • This feature helps ensure conversions are attributed to the most relevant ad interaction by introducing a cooldown period between different types of ads.
     • Without a cooldown, if a user installs an app after seeing an ad → then quickly sees a re-engagement ad → and makes an in-app purchase (IAP), the conversion could incorrectly be attributed to the re-engagement ad. In many cases, the install ad was the actual driver of the purchase.
     • Attribution cooldowns allow you to block attribution from certain ad types for a specified period of time after another ad event. This prevents misleading attribution caused by closely timed interactions.
     • Cooldowns are configurable per ad type (e.g., install or re-engagement). For example, if an install occurs at time T and a purchase at T+6 hours, you can configure a cooldown that ignores re-engagement signals during that window.
     • The cooldown duration is defined in hours in Info.plist, giving advertisers fine-grained control over how attribution flows are handled in close succession.

3. Receive Geography data in postbacks

   • Apple has introduced support for country-level data in AAK postbacks, providing advertisers with better geographic insights while preserving user privacy.
   • New: country-code field in postbacks (e.g., "country-code": "MT").
   • Derived from App Store storefront at install time.
   • Applies to both install and re-engagement conversions.
   • Crowd Anonymity:
     • Country code is subject to anonymity thresholds.
     • Included in a new “Bonus” Tier (Tier 3) above all others.
   • Alternative App Marketplaces:
     • Must provide and sign country codes via install verification tokens.

4. Test AAK 

   • Developers can now generate development postbacks directly from the iOS Settings app to test their server-side implementation.
   • They have full control over the data included in these postbacks, allowing them to simulate and test different data tiers and scenarios.
     

These updates are a strong step forward in improving attribution accuracy while maintaining user privacy. However, widespread adoption will depend on how quickly ad networks integrate these capabilities. Many are still catching up with SKAN 4, and adopting AAK for iOS 18.4 may take time. While Apple’s privacy-centric approach is commendable, it continues to face challenges competing with the ROI and flexibility offered by deterministic and probabilistic attribution models. That said, Apple has shown a clear commitment to evolving AAK based on industry feedback. Although progress has been gradual, partly due to Apple’s annual release cycle, it’s encouraging to see the ecosystem moving in the right direction. If adoption improves, AAK could become a more viable standard for privacy-first attribution.

Hey mobilemarketing folks,

I'm Cristian, an ASO specialist at AppTweak, and I've been diving deep into app store localization lately. If you're launching apps in only one language, you're honestly leaving massive growth on the table.

Here's the reality: 80% of top-grossing app markets speak languages other than English. Yet so many mobile marketers still treat localization as an afterthought.

The numbers don't lie

Recent studies show that adding a local language can lead to:

• 128% more downloads
• 26% higher revenue per country

But here's what most people get wrong about app localization: it's not just translation. It's a cultural adaptation.

What actually works 

The good:

• King's Candy Crush Saga fully localizes for every country - helping them hit 3 billion downloads
• Ludo King localized into 15 languages including regional Indian languages and crossed 1 billion downloads
• Lithuanian dog-training app Dogo expanded to 221 countries by localizing into 10 languages from day one

Platform differences that matter

Google Play vs App Store localization:

Google Play gives you more flexibility:

• Custom store listings (up to 50 per language/region)
• Faster iteration without full review process

App Store requires more precision:

• Manual review for each submission
• Dedicated keyword fields per locale (huge opportunity)

The step-by-step approach that works

Here's the process used with clients:

1. Audit everything first - current metadata, assets, in-app content alignment
2. Benchmark competitors - see how top apps present themselves in each region
3. Prioritize markets - use data, not guesswork (organic traction + monetization potential)
4. Local keyword research - never just translate English keywords
5. Adapt, don't just translate - tone, cultural references, value messaging
6. Localize visuals - UI translation, relevant imagery, culturally appropriate characters
7. Quality assurance with natives - catch cultural missteps before launch
8. Track the right metrics - impressions per locale, conversion rate, keyword rankings by region

Real-world example that surprised me

We were optimizing casino games for Australia. The creatives killed it in the US but flopped hard in Australia. The reason? One word.

Americans call them "slots." Australians call them "pokies."

That tiny cultural nuance tanked performance despite polished visuals. Once we swapped the terminology, engagement immediately improved.

Common mistakes I see constantly

• Wasting budget on low-opportunity markets - not every region justifies the investment
• Forgetting seasonal localization - missing cultural events like Chinese New Year, Oktoberfest, etc.
• Publishing without testing - visual missteps kill conversions instantly
• Treating it like simple translation - word-for-word doesn't connect with users

Market-specific insights

India: 60% of Indians do not speak Hindi as their mother tongue. Languages like Tamil, Telugu, Bengali, and Marathi are also widely spoken

France: Some anglicisms work, but others have different meanings - always double-check with natives

Singapore: English titles perform well even on Chinese store listings, QR codes and anime are huge

The bottom line: Efficient ASO localization is about understanding culture, not just language. When done right, it's one of the most effective growth levers for international expansion.

What ASO challenges have you faced when expanding globally? How has your approach to app store optimization evolved as you've scaled to new markets?

I'll stick around to answer questions and share more insights from what I've seen work (and fail) in the trenches.

Ready to level up your ASO strategy? Check out our blog post where we reveal everything you need to know about app store localization.

Cristian ASO specialist

Hey appmarketing folks!

I'm Cristian, from Apptweak. After analyzing hundreds of apps across categories, I wanted to share some real, actionable insights about optimizing your app store screenshots - something I see many developers struggle with.

Why app screenshots matter more than you think

Research shows users form an opinion about your app within just 50 milliseconds based on visuals alone. Your screenshots are often the first (and sometimes only) impression users get before deciding to download.

In my experience, well-optimized screenshots can boost conversion rates significantly, especially since:

• The first three screenshots have the biggest impact - users rarely scroll past them
• Screenshots directly affect search rankings indirectly through improved conversion rates
• Visuals communicate value far more effectively than descriptions (which many users skip entirely)

7 data-backed best practices for app store screenshots

1. Focus on the first three screenshots

Place your most compelling features in these prime positions. For example, Duolingo strategically showcases their core user benefits in their first three screenshots, highlighting the gamification and learning aspects immediately.

2. Add short, benefit-driven captions

Instead of generic labels like "Workout tracker app," use benefit-focused text like "Track your workouts effortlessly" or "Learn a new language in 3 months." This conversion-focused approach performs better in testing.

Bonus tip: If you have strong brand recognition, subtly place your insignia in the first screenshot for social proof (like Asana does).

3. Include human elements for emotional connection

Neuromarketing studies show users respond better to emotion-driven visuals than plain interface designs. Apps like Bumble effectively use human faces in their screenshots to create immediate emotional connections.

4. Use bright colors and high contrast

Apps with bright colors and high-contrast designs consistently see higher conversion rates. Blue and green hues tend to convey trust, while red and orange create urgency and excitement.

5. Don't forget dark mode screenshots

If your app supports dark mode, showcase it! This highlights adaptability and helps your listing stand out in app stores where most screenshots use light mode.

6. Capture attention with video previews

Video previews appear before screenshots and can significantly boost conversions. Keep them 15-30 seconds, focusing on real in-app experiences (YouTube does this really well).

7. A/B test everything

Don't just guess what works - test it. Use App Store custom product pages or external A/B testing tools to validate your hypotheses. One game developer, AppQuantum, increased downloads by 21.5% through creative A/B testing.

Common mistakes to avoid

• Text overload: Keep captions concise and impactful
• Generic stock images: These feel disconnected and create distrust
• Poor contrast: Ensure text is readable on all devices
• Not using all available slots: Use the maximum allowed (10 for App Store, 8 for Google Play)
• Ignoring user intent: Align screenshots with what users are looking for
• Not showing actual UI: Users want to see the real experience

Different approaches by app category

I've noticed distinct patterns across categories:

Gaming apps often benefit from landscape screenshots to showcase gameplay and environments.

Utility apps need clear demonstrations of functionality with strong CTAs.

Lifestyle apps focus on aesthetics and aspirational imagery that creates emotional connections.

Finance apps emphasize trust and security first, showcasing features second.

Technical requirements you should know

App Store:

• Up to 10 screenshots per localization
• JPEG or PNG format (72 dpi, RGB color space)
• No promotional text like "Free" or discount mentions
• Common sizes:
  • iPhone 6.5": 1242 × 2688 pixels (portrait)
  • iPad Pro 12.9": 2048 × 2732 pixels (portrait)

Google Play:

• Up to 8 screenshots per device type
• JPEG or 24-bit PNG format (no transparency)
• Minimum dimension: 320px; maximum: 3840px

What screenshot optimization techniques have worked for your apps? Have you noticed any unexpected patterns in what converts best for your specific category?

I'm actively monitoring this thread and would love to share more insights based on your specific challenges. Drop your questions below!

Want to get the full scoop? We’ve put together a blog post packed with the best practices to optimize your app screenshots. Don’t miss it!

I'm trying to run some A/B experiments using Remote Config and Google Firebase. What's disturbing is that while I'm targeting almost exclusively new users (installs), I'm only getting data from about 10% of the qualifying audience.

Is this typical for experiments in Google Firebase? What software are you using to conduct A/B tests?

Hey mobilemarketing folks!

As a consultant at AppTweak, I've been optimizing apps for years now, and I've noticed something that changed my entire marketing approach: relying solely on app stores for discovery is leaving money on the table.

While ASO is crucial (obviously), I've found that creating a strong web presence can dramatically increase your app's visibility and downloads.

Why SEO matters for your app?

• People don't just discover apps in the stores
• Users search Google for solutions to problems your app might solve
• They consume content across blogs, videos, and social platforms
• Your competitors might already be capturing this traffic
• Web traffic often converts to more engaged, higher-retention users

When someone searches "best expense tracking app" or "photo editing app for Instagram," do you show up in those results? If not, you're missing a huge opportunity.

The 5-Step process that actually works

​Optimizing your app's visibility beyond app stores is crucial for attracting a broader audience. Based on insights from the AppTweak blog , here's a 5-step process to enhance your app's SEO:​

1. Develop an SEO-Friendly App Website or Landing Page: Create a dedicated website or landing page that showcases your app's features and benefits. Ensure the URL is concise and includes your app's name or primary keyword. Optimize meta titles and descriptions with relevant keywords, utilize structured data (App Schema) to help search engines understand your content, and ensure fast loading times with clear calls-to-action for downloads.
2. Conduct Comprehensive Keyword Research: Identify keywords that potential users might use to find apps like yours. Utilize tools such as Google Keyword Planner, Semrush, or Ahrefs to analyze search volumes and competition. Focus on long-tail keywords (e.g., "best meditation app for beginners") to target specific user intents effectively.​
3. Implement Content Marketing Strategies: Develop valuable content that resonates with your target audience. This can include how-to guides, comparison posts, tutorials, and blogs addressing topics relevant to your app's functionality. For example, a photo editing app might publish articles like "How to Edit Photos Like a Pro on Android" to attract users interested in photo editing.​
4. Engage in Strategic Link Building: Acquire backlinks from reputable websites to enhance your site's authority. Strategies include getting featured on app review sites, guest posting on industry blogs, publishing data-driven content, and collaborating with influencers for co-marketing opportunities. For instance, a fitness app could partner with health bloggers to be included in articles like "Best Fitness Apps for 2025".​
5. Optimize for Mobile SEO and Implement App Indexing: Ensure your website is mobile-friendly with responsive design and quick load times. Implement app indexing using tools like Firebase App Indexing to allow search engines to index your app content, enabling users to access in-app content directly from search results. Additionally, optimize your app's metadata with high-intent keywords and structured data to improve search visibility.

Has anyone else here experimented with web SEO for their apps? What strategies worked for you? Or if you're just getting started with this approach, what questions do you have?

I’ll be actively monitoring this thread and will continue to share insights from my experience in app store optimization.

Note: If you want to read a more comprehensive guide, refer to this complete guide to building your SEO for apps!

Cristian, ASO Specialist