How are LLMs transforming mobile user acquisition? | Adjust

Summary

The article explores how large language models (LLMs) such as ChatGPT, Google's Gemini, and Anthropic's Claude are transforming mobile advertising and user acquisition. Traditional search engine usage is projected to drop 25% by 2026, with organic traffic declining up to 50% by 2028 as users increasingly rely on AI for direct, personalized answers. Key data points include: ChatGPT reached 100 million users in two months, nearly 60% of U.S.

searches result in zero clicks, and over 80% of search users rely on AI summaries for at least 40% of queries. Mobile marketers face a new channel where LLMs provide few but highly valuable recommendation slots. Platforms like Perplexity are testing native ad formats such as sponsored follow-up prompts, while Gemini supports ads within its Search Generative Experience, and OpenAI is expected to launch conversational native ads.

Unlike traditional search, LLM ads rely on semantic intent and session context rather than keyword bidding and behavioral data. Actionable takeaways include: refining app store content and metadata for natural-language queries, strengthening app reputation across reviews and third-party sources, tracking AI-referred traffic via UTM parameters, and testing queries on LLMs to monitor brand positioning. Advertisers who adapt creative strategies for low-volume, high-impact placements will gain a competitive edge.

The article emphasizes an integrated approach across ASO, SEO, and LLM optimization to ensure consistent messaging and maximize discoverability in AI-driven environments.