Dynamic segmentation for app marketers 101: A guide to real-time targeting

Changing user behavior, fragmented engagement patterns, and complex privacy frameworks and regulations make it challenging for marketers to rely on static audience lists for segmentation. Static lists, as used in traditional segmentation, cannot adjust as users move across different levels of interest, intent, or activity. Dynamic segmentation addresses this problem by updating audiences automatically based on real-time behavior

This article outlines how dynamic segmentation works, the key benefits of this approach, and real examples of how app marketers are using it to drive measurable growth.

Traditional segmentation groups users by demographics or device attributes, resulting in fixed lists that can lose accuracy as user behavior changes, making them less responsive or applicable for real-time personalization efforts.

Dynamic segmentation, on the other hand, works by using recent activity, behavioral context, and intent indicators to keep audiences up to date. Segments update automatically as users take actions, change engagement patterns, or show new interests.

How segmentation has evolved

When targeting is aligned with real-time user behavior, teams are able to make more informed decisions much faster and reach audiences at all funnel stages with precision. When this approach is up-and-running, it results in measurable value across three critical areas:

• Performance and acquisition efficiency: Using indicators of immediate intent, marketers can reduce wasted spend and allocate budgets to users most likely to engage or convert. This improves return on ad spend (ROAS), lowers acquisition costs, and enhances channel efficiency by ensuring each campaign targets users in the appropriate stage of the lifecycle.
• Retention and lifetime value (LTV): Declines in usage patterns or engagement provide early indicators of churn risk. Adaptive audience lists enable teams to proactively deliver personalized offers or prompts to re-engage users, increasing long-term value.
• Enhanced personalization and user journey: Live segments support advanced personalization throughout the user experience, from initial onboarding to product recommendations. This behavioral relevance increases user satisfaction, strengthens brand trust, and drives both engagement and monetization across a more cohesive user journey.

The following workflow outlines the simple, five-step process for building and activating dynamic segments:

Step 1: Pinpoint high-value data inputs

Begin by identifying the pieces of user information most critical to your app's success. These are the fundamental rules for segment entry and exit. These may include:

• In-app events: Specific actions like "purchase completed" or "subscription started."
• Engagement metrics: Session frequency, recency of login, or feature interactions.
• Predictive indicators: AI-driven scores revealing the likelihood of churn or conversion.
• Zero-party data: User-submitted preferences (e.g., favorite sports team, dietary goals).

These key data points determine how users transition between segments and ensure audience definitions remain aligned with actual engagement.

Step 2: Define logic that responds to activity

Establish clear, automated criteria for how users move into or out of a segment. For instance, the rule might be: "Move a user into the 'high-risk churn' segment if they haven't opened the app in 30 days." As soon as this action occurs, segment membership updates immediately, keeping your audience cohorts relevant without manual list management.

Step 3: Incorporate predictive modeling

Go beyond basic actions by integrating predictive modeling. AI-driven predictions identify patterns and expected outcomes, like which users are likely to upgrade or lapse, that aren't obvious from raw actions alone. This intelligence is crucial for enabling marketers to act early and tailor strategies with maximum precision.

Step 4: Activate cohorts across all channels

Cohorts differ from segments by grouping users based on behavior and lifecycle stage. Activating cohorts across user acquisition (UA), customer relationship management (CRM), retargeting, connected TV (CTV), email, and other channels ensures each group receives messaging appropriate to where they are in the journey—such as onboarding, activation, or re-engagement. This alignment keeps communication consistent and avoids conflicting messages across touchpoints.

Step 5: Monitor, test, and optimize

Dynamic segmentation is an ongoing process. As user engagement patterns shift, your segments must also evolve. Regular performance reviews enable teams to refine criteria, incorporate new indicators, merge overlapping groups, or adjust activation strategies, ensuring optimization preserves clarity and precision.

Leading apps across industries use dynamic segmentation to enhance personalization, optimize spending, and achieve measurable results. Here are some examples from app businesses that work with Adjust: 

Boutiqaat

Boutiqaat used behavior-based segments to identify users who viewed items or added products to their cart. Retargeting the cart-abandoner segment with relevant ads resulted in a threefold increase in conversion rate and a 28% reduction in cost per order.

Because user interactions and monetization models differ across app categories, the key indicators used for dynamic audience logic naturally vary by vertical. Leveraging specific behavioral cues allows marketers to tailor strategies to each unique use case.

• Gaming: Patterns such as session cadence, level progression, and spending reveal engagement intensity. These signals help teams target players with relevant offers, reactivation prompts, or cross-promotional content.
• Finance: Updates to financial profiles, transaction activity, or tool usage helps identify users who may qualify for specific products or require targeted messaging. These inputs support accurate, compliant targeting as financial needs change.
• Food delivery & marketplaces: Browsing patterns, cart contents, and product views highlight user preferences and near-term intent. These insights inform recommendations, promotional timing, and personalized outreach.

Subscriptions: Changes in content consumption or feature use can indicate satisfaction or potential churn. Identifying these shifts early enables teams to tailor retention efforts and reinforce long-term value.

Adjust provides marketers with industry-leading solutions for accurate segmentation that adapts to changing user behavior. With Adjust Audiences, teams can create flexible, behavior-driven segments using data such as in-app events, feature engagement, and lifecycle milestones. Audience lists update in real time based on the conditions you set, automatically adding or removing users as their attributes change. Adjust also offers secure integrations to share these segments with paid and owned channels, ensuring partner platforms always receive up-to-date lists for activation.