Growth marketing for mobile apps: What is actually working in 2025?

The mobile growth landscape in 2025 is fundamentally different from even two years ago. Ad costs are up, attention spans are down, and user expectations are higher than ever. However, for teams that understand the current toolset and deploy it intelligently, this is a moment of major opportunity.

Thanks to AI technology’s rapid maturity and adoption, growth marketing has become less about brute-force spending. The techniques that work now are centred on operational efficiency, adaptability, and hyper-personalised user journeys.

Here’s how to avoid letting this momentum slip, with actionable steps.

Adaptive onboarding that learns all day, every day

For apps that track the right data, user intent is clearer than ever. Why? Employing ML models during onboarding can help your app adapt its flows to every new user in real time. If a user skips the initial goal-setting, fast-tracks to a specific feature, or hesitates, the experience adjusts. Sometimes the adjustment is about reducing friction, simplifying UI, or improving guidance.

Systems like this do not just segment users by demographics but classify behaviour types and re-route users accordingly. As a result, conversion rates improve, but more importantly, time-to-value shrinks, which is critical for long-term user retention. Needless to say, churn rates decline too. In fact, adaptive onboarding reduces day-1 churn by 20 to 35%, depending on category.

Build onboarding like a decision tree, not a funnel. Let user actions shape the journey immediately.

AI assistants embedded in core ux

When Meta introduced a built-in AI assistant into their apps, the market was not particularly happy about it. However, for applications where users need to make decisions, adjust the difficulty of the task, and get regular follow-ups, integrated AI assistants are a game-changer. This is especially true for categories like fitness, mental health, personal finance, and education, where embedded AI serves as a dynamic UI/UX layer.

In fitness apps, for instance, AI models can adjust daily training plans based on recovery data, sleep, and sentiment inputs. Context-aware interventions, such as recommending rest time or changing workout intensity, allow apps to significantly improve retention rates.

AI often feels out of place when it is added as just another feature. Instead, it should be part of the interface, driving real-time, seamless personalisation.

Community-driven growth that is actually useful

The hype around community building is finally being operationalised. However, instead of just creating new platforms, growth marketers are embedding lightweight social layers into core app experiences. Often, it goes hand in hand with gamification. Think of app dynamics like shared goals, passive group challenges, and cohort-based nudging.

This approach works very well for fitness, productivity, and habit-building apps. Before, companies were building standalone forums. Now, leading apps are integrating with Discord, Telegram, and even Reddit via shareable statistics, AI-generated summaries, or structured discussion prompts. Apps with embedded social mechanics show higher 90-day retention compared to solo-use models.

It is time to forget building a community feature and start designing experiences that are inherently shareable, comparable, and talked about.

Precision notification strategy

Push notifications are not dead. If anything, they are getting smarter. With sentiment tagging, energy-level detection (via voice or motion), and context-aware timing, push notifications can finally lose the synthetic chore-reminder vibe.

Using LLMs to generate push copy based on user mood or usage history is becoming standard among growth teams. For instance, if a user skips a workout session, they might get an empathetic AI-generated push such as “Rough week? We will hold your spot for tomorrow. Ready when you are.” Tone-matching is key: it converts far better than generic reminders. Contextual push strategies see two to three times the click-through compared to generic nudges.

Your push strategy should reflect user state, not just product logic. To get there, personalise notifications beyond user activity: tailor the contents of the notifications with AI based on data relevant to the user journey.

Iterative, creative and messaging

Talking about tailored content: generative AI allows teams to test dozens of iterations of copy, visuals, and CTAs, then train models on engagement data to refine messaging over time. While creatives stay creative, the performance of your messaging is now a data science function.

Your creative team should be training on performance data weekly, and GenAI is a great partner in that loop. Everything from visual tone to CTA length can be optimised based on cohort performance.

Growth in 2025 is technical

The concept of hacks is very 2022. In 2025, growth is more about infrastructure: the best-performing apps are shipping faster, testing smarter, and personalising more deeply. AI can be a key enabler of all that, but never the story itself. The real value comes from how you architect your data flows, connect systems, and design for adaptability.

If you are building or scaling a mobile app right now, focus on these fundamentals: real-time personalisation, adaptive onboarding, and natural social mechanics. Growth is all about building systems that learn as fast as your users do, so that users can enjoy your application even more.

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