How Apptonomy works

Four steps: connect an app, audit it on a schedule, review one revision plan, then publish the changes and measure what they moved.

Connect

Paste an App Store or Google Play link, enter an app ID or search by name to run a free audit. Connecting App Store Connect and Play Console adds search-term and analytics data and enables publishing.

Audit

Each audit runs ten engines against the live listing, its competitors and AI assistants' answers. The plan sets how often.

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 publish to both stores from the product. Later audits and store analytics show what each change moved.

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 on four pillars: Discoverability, Conversion, Retention and Trust. Successive audits can be compared on the same scale.

On Pro, Elite and Enterprise, a connected App Store Connect or Play Console account is read every day: impressions, product-page views, installs and conversion rate.

The revision plan collects the findings into one ranked list. It changes nothing in the stores until its rows are approved.

Step 1: Connect

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 and Play Console to add search-term and analytics data and to publish from Apptonomy.

What Apptonomy does

  • •Apptonomy reads the current listing from the store.
  • •Keyword volume comes from Google Ads, calibrated against Apple Search Ads popularity. Difficulty comes from live App Store and Google Play search results.
  • •The competitor set is built from the apps that rank for the same keywords, and their listings are read the same way.
Step 2: Audit

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 by search intent into clusters, 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 title, subtitle and description signal the same priority clusters.

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.
Step 3: Plan

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 made through the store consoles and an existing release process instead of publishing 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.
Step 4: Publish and measure

Publish the plan, then see what it moved

On Pro, Elite and Enterprise, approved changes go to both stores from the listing editor. Later audits and store analytics show what each change moved.

Publishing

  • •Approved changes go to the App Store and Google Play without re-entering them 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 and attribution

  • •On Pro, Elite and Enterprise: daily impressions, product-page views, installs and conversion rate from the connected store accounts.
  • •Install and conversion-rate movement after each published change is shown against that change.

What each engine checks, and how, is on the methodology page.