Your store listing is your most-tested ad. Most teams don't test it.
A store listing is what someone sees before they download your app — the icon, screenshots, title, and description. In app stores, it determines whether someone taps Install or keeps scrolling.
App Store Optimisation (ASO) is the practice of improving that listing to get more downloads. Traditional ASO means periodic audits, occasional experiments, and slow iteration.
Agentic ASO is the same goal — but the agent runs the experiments. No briefing cycles. No waiting for bandwidth. The loop runs continuously.
App stores are not static. Neither is your competition.
Store algorithms shift. Seasonal trends arrive. What converted in January does not convert in July. Testing only works if you do it before the change happens.
Competitors update their listings. New entrants appear. Standing still is a choice to fall behind.
An experiment that does not win still tells you something. Continuous testing builds a library of what your audience responds to. One-off tests leave that knowledge on the table.
Manual ASO depends on when your team has time. Agentic ASO runs on its own.
Manual ASO works. Teams who do it consistently improve conversion. The bottleneck is always the same: someone has to write the brief, commission the asset, launch the test, read the result, and apply the learning.
At one app in one market, that is a few hours a month. At five apps across ten markets, it becomes a dedicated team — and the tests still move slower than the market does.
Agentic ASO hands the loop to an agent. The agent identifies hypotheses, generates assets to brand guidelines, runs experiments, and applies what it learns — without waiting for a human at each step.
Your team sets the guardrails. The agent does the work.
Agentic ASO doesn't replace expertise. It frees it.
Four steps. No waiting.
Link your app and set your guardrails. PressPlay indexes your store listing and starts building the baseline.
→ Try Instant Preview to see your listing analysisThe agent analyses top-performing listings in your category, generates creative variations to your brand guidelines, and prepares the experiment brief — automatically.
Experiments go live in the store. The agent tracks impressions, conversion, and install rate. No manual monitoring required.
Winners are applied. Learnings are logged and feed the next hypothesis. Each cycle makes the next one smarter.