Category choice
Which app should I use for this job? Best app for… · Top apps for… · App recommendations
AI DISCOVERY
Make your app easier to understand and recommend.
We review how assistants describe your app, inspect the sources behind their answers and improve the product information you control.
QUESTION → SOURCE → PRODUCT FACT
Can the source support the answer?
Product capabilityDocumented feature and limitations
Source freshnessUpdated help article and store listing
Answer accuracyVerified against the current product
Source notes retained for the next review.
THE WORK
Start with the questions people ask
Comparison and alternatives
Which app fits a must-have, like free or offline? X vs Y · Alternative to X · Free, private, offline
Capability evidence
Can the app actually do the specific thing the user needs? Feature depth · Compatibility · Workflow proof
Trust and safety
Is the product credible enough for the category? Privacy · Regulation · Expertise · Reviews
Local context
Does the answer change by market or language? Availability · Currency · Local behaviour · Culture
Device and mode
Does the app work where and how people will use it? iOS and Android · Offline · Network · Accessibility
Improve the information behind the answer
Store listing
Availability, category, metadata, screenshots, ratings, release notes and in-app events are the source you control most. The listing has to be clear first; outside evidence cannot make up for it.
Owned sources
Product, help, comparison and category pages can explain features, limits and trust facts in far more depth than a store field. Every claim needs a named owner and a supporting source.
Earned sources
Editorial, expert, publisher and review coverage adds authority when the relationship is genuine. We never present paid placements or fake reviews as independent evidence.
Accuracy QA
We check every observed answer for accuracy on features, availability, price, platform and important caveats. Being recommended for the wrong thing can cost more than not appearing at all.
QUESTIONS
Before we get started
Can you get my app into ChatGPT, Gemini or Perplexity?
No outside provider controls inclusion. We make the store listing and sources easier to read and the evidence stronger, then check results with a documented sampling method.
How many prompts are enough?
There is no universal count. The panel must cover what people use the app for, the comparisons they make, their must-haves, your markets and their language. Repetition and sampling design matter more than a big number.
Do you scrape private model data?
No. We record the answers and sources anyone can see, in the modes we state up front. We do not claim access to training data or private ranking factors.
Can recommendation visibility be attributed to installs?
Sometimes, and only in part. We can track direct links, referrals, rises in branded search and assisted journeys, but untracked and cross-device behaviour sets limits, and we state them.
What is the difference between a mention and a recommendation?
A mention names the app. A recommendation puts it forward for what the user wants to do. Citations and links are counted separately.
How often should the panel be rerun?
Often enough to spot lasting change without overreacting to daily swings. Ongoing programmes usually rerun a fixed core panel on a schedule, with extra checks after major events.
Does GEO content mean creating hundreds of thin answer pages?
No. Source quality, explicit product facts, useful category education and genuine authority matter more than mechanically producing pages around every prompt.
What is the fastest first step?
The AI Discovery Sprint sets the baseline, compares you with competitors, finds the source gaps and delivers a prioritised 90-day plan to close them.
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