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Customer segmentation for apps: How to build and reach valuable audiences
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Audience segmentation is a key tactic in mobile app marketing. Today, user acquisition and growth teams are focusing on retention, lifetime value (LTV), and return on ad spend (ROAS) alongside install volume. Segmentation helps marketers identify high-value users, tailor messaging, and allocate budgets more efficiently.
High acquisition costs, evolving privacy frameworks and the need to deliver relevant user experiences mean that many teams are now also using automated and predictive methods to build and activate segments based on real-time behavior and performance data.
The APAC region, for example, is projected to surpass 2.8 billion smartphone users by 2025, with mobile internet penetration reaching 61% by 2030. These developments are necessitating increasingly nuanced segmentation approaches across India, China, Southeast Asia, Japan, and South Korea, and more, where each market is shaped by unique user behaviors, engagement levels, and monetization patterns.
This guide outlines how mobile marketers can define, activate, and measure audience segments to drive efficiency, impactful personalization, and return on investment (ROI).
TL; DR
- Segmentation helps marketers personalize campaigns and improve ROI, retention, and LTV.
- Predictive models and first-party data now power segmentation as privacy regulations and frameworks like App Tracking Transparency (ATT) limit user-level tracking.
- Adjust Growth Copilot and Audiences make segmentation easy, combining accurate data, automation, and fast, native-language access to insights.
Mobile app audience segmentation 101
So, what is audience segmentation? Segmentation historically relied on static lists based on broad attributes such as age, gender, or location. These segments were manually built and rarely updated. Now, many segmentation approaches are dynamic and predictive. Marketers use first-party data and machine learning to group users based on behavior, intent, and likelihood to convert, automatically updating as user activity changes.
Privacy frameworks like ATT have limited user-level tracking, making first-party, consented data the foundation of modern segmentation. Automation and artificial intelligence (AI) let marketers build and update real-time segments across channels, improving decision speed and personalization while maintaining data privacy.
Segmentation in action
Here are some common segmentation models that lay the groundwork for today’s dynamic models:
Demographic segmentation (Nike): Campaigns tailored by gender, age, or region, such as Nike’s Greatness ads, demonstrate how even broadly personalized creatives aim to connect more effectively with audiences.
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Psychographic segmentation (Amazon): Using interest, and lifestyle-based targeting, this Amazon example uses refined recommendations to align with customers’ preferences.
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Behavioral segmentation (Just Eat): By analyzing browsing and purchase patterns, Just Eat delivers ads based on cuisine type or past orders, increasing the likelihood of return engagement.
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These are classic (still common) approaches that also form the foundations for today’s predictive segmentation, where machine learning and first-party data personalize user experiences in real time across mobile apps, without relying on static audience lists.
This means you can take the same ideas and make them more specific for far more granular segments. Looking at the JustEat example, instead of three broad buckets (Healthy, Chinese, Burgers) you can display the exact items the user was viewing in a re-engagement context, or more specifically relevant options along with messaging, colors, app screenshots, and more for new audiences.
How segmentation helps with mobile marketing UA performance
Segmentation helps marketers improve personalization, which means better performance and efficiency. It enables teams to target the right users, reduce wasted spend, and increase long-term value. Regardless of the specific goal or KPI, segmentation can be leveraged to target the right audience at the right time with the right message.
Performance and ROI
Segmentation improves campaign performance by aligning messaging with user behavior. Targeted campaigns achieve higher conversion rates and engagement than general campaigns.
Case study spotlight: E-commerce platform Boutiqaat segmented “cart abandoners” with Adjust Audiences, achieving a 3× higher conversion rate and 28% lower cost per order through personalized retargeting.
High-value user groups, such as super-app users (very common in APAC), digital-wallet adopters, and localized language communities, deliver stronger ROI when experiences are tailored to their preferences.
Efficiency and spend optimization
By identifying high-value or high-intent users, marketers can allocate budgets more efficiently. Segmentation reduces wasted impressions and prevents duplicate targeting across channels, leading to a lower cost per acquisition (CPA) and higher ROAS.
Personalization and user experience
Segmentation supports context-aware communication using behavioral and event data. It helps marketers tailor content, timing, and channels. Recent research shows that personalization can reduce customer acquisition costs by up to 50% and increase marketing spend efficiency by up to 30%, making it a key driver of growth for mobile-first brands.
Retention and lifetime value
Segmentation sustains engagement throughout the user lifecycle. Teams can identify users at risk of churn and re-engage them or reward loyal users with personalized offers to encourage retention.
Case study spotlight: Akbank segmented active users based on credit scores and app activity to target qualified loan applicants through Facebook campaigns.
Result: Facebook’s share of loan conversions grew from 5% to 45%, while unit cost per loan decreased by 60%.
Pivoting back to APAC, In markets like Japan and South Korea, segmentation emphasizes personalization and loyalty, while markets such India and Indonesia often focus on regional language and device-based segmentation to craft messages that increase retention.
How to build and activate audience segments
Follow these steps to design, activate, and refine segments that improve campaign performance and efficiency.
Step 1: Define campaign goals
Set measurable objectives before creating segments. Clarify whether the focus is retention, re-engagement, or conversion to ensure alignment with metrics like ROAS, LTV, or retention rate.
Step 2: Identify high-value cohorts
Analyze user data to determine which groups generate the most value. Compare cohorts by engagement, spending, or churn risk to identify shared traits such as device type, location, or in-app behavior.
Tip: Start simple. Focus on a few core user groups before expanding to predictive segmentation.
Step 3: Build segments based on behavior
Create segments that reflect actual usage patterns. Examples include:
- Device or OS: Tailor messages for iOS and Android users.
- Behavioral patterns: Segment by purchase frequency, activity, or milestones.
- Acquisition source: Separate organic from paid users to guide budget allocation.
- Lifecycle stage: Target new, active, or dormant users with specific campaigns.
Segments should update automatically as behavior changes. Predictive segmentation uses machine learning to forecast churn or purchase likelihood, allowing marketers to act proactively.
Tip: Use real-time data to keep segments accurate and privacy-compliant.
Step 4: Activate across channels
Deploy segments across paid, owned, and earned channels to deliver consistent, relevant communication. Match messages to each group—for example, loyalty offers for frequent buyers or win-back campaigns for inactive users.
Tip: Test and iterate. A/B test messaging and creative across segments to improve performance.
Step 5: Measure and refine
Monitor performance by audience type to identify segments that drive the strongest results. Adjust budgets, creative, and targeting based on data. Over time, refine or merge similar segments to maintain efficiency.
Case study spotlight: Adidas Runtastic used Adjust Audience to target active users across its fitness apps, increasing ROAS by 179% and reducing cost per purchase by 61%.
Customer segmentation with Adjust
Accurate measurement turns segmentation into a growth engine. Adjust helps marketers connect audience insights to outcomes like installs, engagement, and retention.
Case study spotlight: ALive Powered by AIA used Adjust’s Fraud Prevention Suite and Audiences to eliminate fraudulent leads and improve audience quality, saving $60,000 and increasing conversion rates by up to 60%.
With Audiences, marketers can define user groups, share them securely with partners, and measure their performance at campaign level. Real-time updates and behavioral filters help teams test and refine audiences while protecting user privacy.
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At the analytics level, Adjust Growth Copilot, our AI assistant, can analyze campaign and segment performance in real-time to reveal insights and optimization opportunities, presented in an easy-to-use, natural language interface. Together, these solutions make segmentation continuous and data-driven, linking analysis, activation, and results to support smarter marketing decisions.
Ready to get started with your app’s own customer segmentation? Request a demo today to see how Audiences works first hand, and how we can help grow your app business.
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