App Store Listings
Part of App growth localisation
Measuring a localised listing against the right market
Choose the Australian market filter, listing, metric and denominator before judging localised app store content.
Judge a localised listing against the Australian audience the app can actually serve. Before comparing a rate, name the store, market definition, listing version, dates and store action.
A store territory or language segment does not prove that someone is currently in a served area. Treat storefront, language and service eligibility as separate parts of the market definition.
Define the market and page
Define the intended market as Australia-wide or as a narrower service area that product data can identify. Record the store territory and any language filter, but do not use either alone to infer someone’s current location or eligibility for the service.
In App Store Connect Analytics, use the Territory dimension to compare storefront territories. It cannot by itself distinguish service areas within Australia, so use product data to identify eligibility inside the country.
Record when the localised content went live and which listing version was available. Apple’s Product Page filter distinguishes default and custom product pages; Google Play custom store listings can target specific user segments.
Key Measurement Requirements for Localised Listings in Australia
- Market Definition
- Australia-wide or defined service area (e.g. NSW only)
- Store Territory Filter
- Australia (AU)
- Language Filter
- English (en-AU) – not a location proxy
- Listing Version
- Default or custom product page (Apple), custom listing (Google)
- Live Date
- Record date when localised content went live
Pros and Cons of Using Storefront Filters to Infer Market Eligibility in Australia
- ProsProvides broad geographic context; useful for cross-market comparisons
- ConsCannot distinguish between eligible and ineligible users within Australia; does not reflect real-world service eligibility (e.g. ABN, GST, regional restrictions)
Select the store action
In App Store Connect Analytics, use App Store metrics with the relevant filters and dimensions. Impressions include product page views; Product Page Views count views of the product page, including views loaded with StoreKit. First-time downloads and redownloads are separate measures.
Apple’s standard Conversion Rate is total downloads and pre-orders divided by unique device impressions. It is not a product-page-view-to-first-time-download rate; label any separately calculated rate and use compatible records.
Apple’s Metric definitions states that App Store metrics are available after at least five first-time downloads or pre-orders. Usage metrics come from people who opted to share their analytics, so they do not represent every user.
In Google Play Console, compare Store Listing Visits and Impressions using their displayed labels. Do not equate either label with an install unless its metric definition says it counts installs.
Keep with each comparison / Record
- Audience
- Store territory or country definition and any language filter
- Page
- Listing type and content version actually live
- Entry mix
- Traffic sources under the chosen report’s labels
- Outcome
- Exact metric and denominator
- Period
- Before and after dates under the same observation rule
App Store Connect vs Google Play Console: Store Action Metrics
- Metric (Apple)
- Impressions (product page views)
- Metric (Google)
- Store Listing Visits
- Conversion Rate (Apple)
- Total downloads and pre-orders ÷ unique device impressions
- Install Attribution (Google)
- Not directly counted by 'Store Listing Visits' or 'Impressions'
- Eligibility Data Source (Apple)
- Product data (e.g. service availability, ABN, GST registration)
- Eligibility Data Source (Google)
- User segment targeting via custom store listings
Pre-Comparison Checklist for Measuring Localised App Store Content
- Audience: Define store territory and language filterUse AU for Australia; do not assume location from language alone
- Page: Confirm listing type and version liveCheck Apple’s Product Page filter or Google Play custom listing targeting
- Entry mix: Track traffic sources consistentlyEnsure source mix is stable across comparison periods
- Outcome: Use exact metric and denominatorAvoid conflating impressions with installs; use official definitions
- Period: Apply same observation rule before and afterMatch reporting dates and filters exactly
Interpret a change within its limits
Compare periods using the same reporting rules and keep the traffic-source mix visible. A campaign can change who arrives while listing copy changes.
A before-and-after difference is a reason to investigate, not proof that localisation caused it. A listing experiment has its own eligible-audience rules.
Show counts beside rates, especially for a small segment. Leave unavailable cells blank and state why they cannot be read.
Apple’s store metrics do not establish that acquired users completed an in-app task. Its app-usage metrics also reflect only people who opted to share their analytics.
Finish with a bounded finding: which market-defined group saw which page, what store action changed and what remains unknown. If the filter or page exposure cannot be reconstructed, improve the measurement setup before claiming a localisation effect.
