Winning User Acquisition Strategies in the LLM Era
As large language models (LLMs) increasingly mediate digital experiences, the way users discover and download apps is shifting. Marketers must evolve their UA playbooks to thrive in an AI-mediated environment.
1. Optimize for LLM Discovery Apps are now being discovered through AI assistants like ChatGPT, Gemini, and Siri Pro. These LLMs index metadata and understand natural language queries.
Tip: Rewrite your app descriptions and meta tags to reflect common user intents ("best budgeting app for freelancers").
2. Design Conversational Entry Points Discovery is becoming dialogue-driven. A user might ask "How can I improve my sleep?" and be recommended a sleep-tracking app.
Strategy: Use schema markup, app content indexing, and integrations with AI services (e.g., ChatGPT plugins) to make your app visible.
3. Use LLMs to Generate & Test Creatives LLMs help create hyper-relevant ad headlines, localizations, and visual briefs faster than human teams alone. They also support predictive testing by scoring variants.
4. Rewire Onboarding Around AI Expectations Today’s users often arrive via AI-led recommendations and expect clarity and value upfront. Personalize the onboarding flow based on intent.
Example: If users arrive via "free calorie tracker", show them that path instantly.
Final Thoughts
The LLM era requires more than automation—it requires rethinking how discovery, trust, and UX work. Build UA funnels that speak the language of AI.
Want help adapting your mobile UA strategy for the LLM-first future? Let’s talk.
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