Your next customer may be asking ChatGPT which app to download, but will your app make the list? AppTweak’s CMO Alexandra De Clerck draws on more than eight years in app store marketing to explain how LLMs interpret user intent, combine internal knowledge with live web retrieval, and use “query fan-out” to decide which apps deserve a recommendation. She reveals why app store descriptions have become critical AI discovery assets; how detailed reviews and community conversations help validate an app’s positioning; and why smaller apps have a rare opportunity to compete for AI visibility before the market becomes saturated.
Questions Alexandra answered in this episode:
What’s the biggest shift in app store marketing you’ve seen in the last three years?
How are consumers using ChatGPT and other LLMs to discover new apps?
How does an LLM decide which apps to recommend for a specific prompt?
What is ‘query fan-out’, and why does it matter for app marketers?
How can marketers determine whether their app is visible in AI-generated recommendations?
Why are app store descriptions becoming more important in the age of AI discovery?
What helps an app appear among ChatGPT’s first sourced recommendations?
Why do games receive more citations from Reddit and Wikipedia than other app categories?
How can smaller apps compete against brands with larger budgets and more downloads?
Can app reviews and developer responses influence how LLMs understand an app?
How should marketers measure AI visibility when most app discovery journeys are zero-click?
Timestamp:
00:23 – Introducing Alexandra De Clerck and AI app discovery
00:43 – About AppTweak and Alexandra’s journey to CMO
02:50 – How app discovery has changed in the past three years
04:06 – How ChatGPT and other LLMs choose which apps to recommend
06:11 – ‘Query fan-out’ and how AI interprets complex prompts
07:17 – Why most app marketers do not yet have an AI visibility strategy
09:27 – The first steps marketers should take to improve LLM visibility
09:38 – Why app store listings are such important AI citation sources
11:59 – How apps can reach the first five or six sourced recommendations
13:28 – Why AI discovery works differently for games and non-game apps
15:41 – How smaller apps can outperform larger competitors in AI search
17:25 – Using app reviews and developer responses to reinforce positioning
18:48 – Measuring AI visibility in a mostly zero-click user journey
21:28 – The long-term advantage of investing in AI visibility now
22:56 – Rapid-fire questions with Alexandra
25:30 – Where to connect with Alexandra and learn more about AppTweak
Quotes:
(6:07) “An important concept to understand in AI search is how AIs actually interpret the prompt.”
(9:48) “What we’ve seen from our research is that actually almost 50% of all citations in ChatGPT are app store listings.”
(10:19) “LLMs really look at app store listings to understand what an app is about, who it’s for, and what the main use-cases are, so that’s the highest leverage opportunity for app marketers getting started with an AI search strategy.”
(12:22) “So we see when ChatGPT makes a recommendation [for a mobile app], usually the first five to six answers are sourced. So that means that they actually did a live web retrieval to find information about this. And for where it's not sourced, it actually means that they looked into their internal knowledge base to build the answer.
(22:11) “If you start now by optimizing your intent coverage around the web and really helping ChatGPT and other LLMs understand what your app is and what your app is about, build that context into their internal knowledge base as well, then you have an edge up compared to people who are still exploring or discovering or wondering whether or not it's worth it to get started.”
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