An indie dev pinged us recently, properly confused. Their app's US reviews after a major update were 4.6 stars and warm. Their German reviews of the same release were 3.1 and openly hostile. App Store Connect showed the global average; it did not surface the gap. The reason it's so easy to miss is structural: App Store reviews are local. 175 country storefronts, each with its own review pool, language, and ordering. A German user sees German reviews. A US user sees US reviews. They almost never overlap. If you want to know what's actually happening with your app, you need every storefront pulled separately and stacked in one spreadsheet. This guide walks you through using ExportComments' Apple App Store Reviews exporter to do exactly that — into Excel, CSV, or JSON.

Why export Apple App Store reviews

The App Store's per-country structure is the single most important thing to internalize about its review data. App Store Connect's dashboard shows a global headline that hides the gap between markets, and the public app page only shows you the reviews from your storefront. The pools are separated by country and by language. The other useful structural detail: each review carries the app version it was written against — which is what makes per-version timeline overlays possible, the kind that show you the exact release that knocked the rating off a cliff. Once it's all in a spreadsheet:

  • Per-storefront pivot — pull each country as its own URL and stack them. The country with the worst average is rarely the one your team has been worrying about.
  • Per-app-version timeline — overlay average rating per version against your release calendar. Bad releases show up as a cliff edge.
  • Language-bucket sentiment — pivot rating by language to triage localization. A language sitting a star below the global average usually means the localization broke or the in-app copy stopped landing.
  • Top-reviewer outreach for testimonials — sort by length descending in the 5-star bucket and reach out to the most articulate reviewers for testimonials or beta access.
  • Hidden country-storefront sentiment gap — the gap between US and DE/FR/JP sentiment for the same release is the thing App Store Connect refuses to surface in a useful way.
  • Developer-reply audit — pivot reply rate by storefront. One or two markets get all the attention while the rest go silent.

How to export — step by step

Step 1: Grab the App Store URL with the country storefront

App Store URLs include a country code right after the domain — for example https://apps.apple.com/us/app/example/id1234567890 for the US storefront, https://apps.apple.com/de/app/example/id1234567890 for Germany, https://apps.apple.com/jp/app/example/id1234567890 for Japan. The country code is the part that decides which storefront's reviews you're going to get. Same app, different country — entirely different review pool.

Step 2: Paste the URL into the exporter

Head to the App Store Reviews exporter and paste the URL. For a cross-storefront snapshot — say, US, GB, DE, FR, JP, BR — switch to bulk mode and paste one URL per storefront. Bulk runs return one Excel file per URL bundled in a ZIP, so each country stays in its own file. The most useful country in the batch is often one your team didn't think to look at first.

Step 3: Pick a format

Excel (.xlsx) is the right pick if you're going to pivot rating by version, by language, and by storefront — the three pivots that make App Store data legible. CSV is the safest pick for BI imports and analytics warehouses. JSON if you're piping the export into a sentiment model or running per-language topic analysis in a notebook.

Step 4: Start the export

Click Export. The job runs server-side and paginates through that storefront's reviews for the app — country code, app version each review was written against, developer reply where present, and the body text. Apps with massive review counts take a few minutes; close the tab and the file lands in your dashboard and inbox when it's ready.

Step 5: Open the file

Open the .xlsx in Excel, Numbers, or Google Sheets. Each row is one review, each column is one field. You're ready to filter and pivot.

Inside the export — what fields you get

Each row is a single App Store review. You'll find columns for:

  • Reviewer name — display name shown on the review.
  • Country — the storefront country code the review came from (us, de, fr, jp, etc.).
  • Rating — the 1–5 star score.
  • Title — the headline the reviewer wrote.
  • Body — the full review text in the storefront's language.
  • App version — the version of the app the review was written against.
  • Developer reply — the developer's response text, when present.
  • Developer reply timestamp — when the reply was posted.
  • Created at and Updated at — original timestamp and last-edit timestamp in UTC.

Common workflows

  • Per-version timeline overlay — pivot average rating by app version, chart the result against your release calendar. The release that broke something shows up as a cliff edge. The release that fixed something shows up as a recovery curve. App Store Connect makes this surprisingly hard to do natively, which is why pulling the data offline is usually the fastest path.
  • Cross-storefront sentiment gap — bulk-pull six to ten of your largest storefronts, stack them, pivot rating by country. The market with the lowest average is often a market your roadmap doesn't even mention.
  • Language-bucket localization triage — pivot by language. A language a full star below the global average usually means a localization stopped landing or a feature doesn't fit the local context.
  • Top-reviewer outreach for testimonials — filter 5-star reviews with body length above 200 characters, sort by length descending. The articulate enthusiasts at the top are your best testimonial and beta-cohort leads.
  • Developer-reply audit per storefront — pivot reply rate by country. Almost every team replies to US reviews and almost none reply to JP, BR, or KR — and the silent storefronts often have the worst averages.
  • Bad-release post-mortem — filter to one app version, sort rating ascending, read the top 100 1-star reviews per storefront. Patterns emerge fast: a regression, a scary permission prompt, a confusing copy change.

Plan limits and API access

The Free tier returns up to 100 reviews per export, which is enough to confirm the columns and storefront targeting work for your case. Personal scales to 5,000 reviews per export, Premium to 50,000, and Business to 250,000 — enough to capture every review for the largest free apps on the platform. If you'd rather refresh ten storefronts every Monday morning or trigger an export from your CI on every release, the same job is available through the REST API and via webhooks. See pricing for the full breakdown.

FAQ

  • Why are German reviews different from US reviews of the same app?
    Because App Store reviews are local to each country storefront — there are 175 of them and they don't share review pools. A German user only sees German reviews; a US user only sees US reviews. Pulling each storefront separately is the only way to see the gap.
  • Can I tell which app version a review was written against?
    Yes. The app version is a separate column on every row, which is what makes per-version timeline overlays and bad-release post-mortems possible.
  • Does the export include developer replies?
    Yes — both the reply text and the reply timestamp are included on every row that has one, so you can audit reply rate and time-to-reply per storefront.
  • How do I export reviews for several country storefronts in one batch?
    Use bulk mode and paste one URL per storefront — change the country code in the URL each time (us, de, fr, jp, etc.). The run returns one file per URL packaged into a ZIP, so each country stays in its own file for per-storefront pivots.
  • Can I get the language of each review?
    The body text is in the storefront's primary language; you can detect language with a quick spreadsheet formula or a model pass if you need a clean column. Pivoting rating by storefront country is usually a faster proxy and gets you the same insight.
  • Can I run this on every release?
    Yes. The same export is available through the REST API and webhooks, so a CI step can pull post-release reviews per storefront automatically — useful for the per-version cliff-edge chart.