How Apptonomy works
Four steps: connect an app, audit it on a schedule, review one revision plan, then publish the changes and see the movement after each one.
Connect
Paste an App Store or Google Play link, enter an app ID or search by name to run a free audit. On every plan, connecting App Store Connect adds the keyword field to the audit. On Pro, Elite and Enterprise, connecting App Store Connect adds listing analytics, connecting Play Console adds listing analytics with search terms, and either connection enables publishing to its store.
Audit
Each audit runs the engines its plan includes, up to all ten, against the live listing, its competitors and AI assistants' answers. The plan sets which engines run and how often; the pricing table lists them.
Plan
The findings are ranked in a revision plan. Each recommendation states what to change and why. Nothing changes until it is approved.
Publish and measure
On Pro, Elite and Enterprise, approved changes are sent to both stores from the product, where they go through each store's review. Later audits and store analytics show the movement after each change.
The engines and their data sources are on the methodology page. Work in development is on the roadmap.
The schedule
How often each part runs
Audits run daily on Elite and Enterprise, twice a week on Pro, weekly on Basic and monthly on Free.
Each audit re-reads the app's listing and its competitors' listings and scores the result, with four pillar scores: Discoverability, Conversion, Trust and AI Discoverability. Successive audits can be compared on the same scale.
On Pro, Elite and Enterprise, connected store accounts are read every day. App Store Connect: impressions, product page views, first-time downloads and conversion rate. Play Console: store listing visitors, acquisitions and conversion rate.
The revision plan collects the findings into one ranked list. It changes nothing in the stores until its rows are approved.
Choose the app
A store link, an app ID or the app name is enough for the first audit. Store accounts can be connected later.
What the user does
- •Paste the App Store or Google Play link, enter the app ID, or search by name. The first audit needs no account.
- •Optionally, connect App Store Connect or Play Console. On every plan, App Store Connect adds the keyword field. On Pro, Elite and Enterprise, connecting App Store Connect adds listing analytics, connecting Play Console adds listing analytics with search terms, and either connection enables publishing to its store.
What Apptonomy does
- •Apptonomy reads the current listing from the store.
- •Keyword volume is an estimate: Google Ads monthly searches converted to a store popularity scale with a curve fitted to Apple Ads search popularity. Difficulty comes from the strength of the apps ranking in live App Store and Google Play search results.
- •The competitor set is built from store search results for the listing's keywords, the store's similar-apps list (the App Store's “You Might Also Like”, Google Play's “Similar apps”) and the sub-genre's top charts. Apps outside the app's sub-genre are dropped, except for non-game apps on Google Play, where the language-model rating decides instead. On Google Play, and in several App Store categories including games, a language model keeps the candidates it rates as direct rivals or adjacent apps, direct rivals first. The publisher's own other apps are dropped, except in games, where one of its titles is kept when it is rated a direct rival; for an App Store game filed under a non-game primary genre, only when its title or subtitle also names a subject of the audited app's title or subtitle. The set is ranked by chart position and install volume. Their listings are read the same way.
Keywords, creatives, competitors, reviews and AI answers
The audit reports how the listing performs today and where the largest gaps are. The plan sets which modules run; the pricing table lists them.
How language models are used
- •Each engine follows a written methodology, maintained by an in-house ASO practitioner.
- •Language models apply that methodology to the data collected in step 1. They do not decide what the engine checks.
- •Each engine returns structured fields, so every recommendation can cite the data behind it.
Semantic clusters
- •Groups keywords into semantic clusters by topic, such as "Music", "Podcasts" or "Audiobooks".
- •Shows which clusters the listing's metadata currently signals.
- •Rates each cluster by volume, difficulty, rank and trend as strong, an opportunity or underperforming.
- •Checks that the indexed fields signal the same priority clusters: title, subtitle and keyword field on the App Store; title, short description and full description on Google Play.
Keywords and visibility
- •How the current metadata ranks for the relevant search terms.
- •Which terms the listing ranks for, which it ranks poorly for and which it misses.
Competitors and positioning
- •The listing's messaging and positioning compared with its competitors'.
- •Themes the category covers heavily and themes it leaves open.
Icon, screenshots and copy
- •Icon, screenshots and copy scored against the category's conventions.
- •Problems with visual hierarchy, the sequence of screenshots and the clarity of the value proposition.
Reviews
- •Review themes by market and by rating.
- •Themes the listing can address, separated from issues for the product team.
In the report
- •An ASO Readiness Score from 0 to 100, with a score for each of the four pillars.
- •The main problems and opportunities, grouped by engine.
One ranked revision plan
The findings become one ranked list of changes, each with its reasoning. Nothing is published until it is approved.
Ranked recommendations
- •Changes to keywords and metadata, messaging and screenshots, and localization, in order of expected effect.
- •Each recommendation states what to change, why, and which pillar it is expected to move.
Reasoning
- •Each recommendation traces back to the finding and the data behind it.
- •The reasoning is written to be shown to a client or a manager.
Approval
- •Each row can be approved, edited or declined.
- •Changes can be applied through the store consoles and an existing release process instead of sending them from Apptonomy.
PDF reports and share links
- •A full PDF report of an audit, with the score, the pillar scores and the ranked recommendations.
- •A public share link per audit, created on request.
Publish the plan, then see the movement after it
On Pro, Elite and Enterprise, approved changes are sent to both stores from the listing editor. Later audits and store analytics show the movement after each change.
Publishing
- •On the App Store, approved changes are written to the app version being prepared for submission and go live with that version after Apple's review. On Google Play, they are committed as a listing edit, which Google reviews. Nothing is re-entered in either console.
- •Teams that release through the store consoles can apply the plan there instead.
Score history
- •Each later audit re-scores the listing, so the score and the pillar scores show whether a change landed.
- •Successive versions of the listing can be compared side by side.
Store analytics after each change
- •On Pro, Elite and Enterprise, daily figures from the connected store accounts: impressions, product page views, first-time downloads and conversion rate from App Store Connect; store listing visitors, acquisitions and conversion rate from Play Console.
- •Installs and conversion rate before and after each published change are shown against the date it was published. Paid campaigns, featuring and seasonality move the same figures.
What each engine checks, and how, is on the methodology page.