Apple Podcast Reviews Scraper

What does Apple Podcast Reviews Scraper do?

Apple Podcast Reviews Scraper collects public written customer reviews from Apple Podcasts and returns them as a clean Apify dataset. Provide one Apple Podcasts URL or a numeric podcast ID, choose the Apple storefront country and review order, then download structured review data for research, sentiment analysis, audience feedback, and podcast monitoring.

Why use Apple Podcast Reviews Scraper?

• Review research - Gather titles, written feedback, star ratings, authors, dates, and helpfulness votes in one dataset.

• Podcast monitoring - Schedule repeat runs to track new listener feedback over time.

• Country comparison - Compare reviews from different Apple storefronts such as the US, UK, Canada, and Australia.

• Flexible input - Use a full Apple Podcasts URL or only the podcast ID.

• Automation-ready output - Export JSON, CSV, Excel, XML, or connect the dataset to downstream workflows.

• Result control - Limit the number of reviews and pages so test runs stay quick and larger collections remain predictable.

• Extended recent history - mostRecent runs can continue through Apple’s extended review pages instead of stopping at the public RSS limit.

What data can you extract from Apple Podcasts?

Field	Description
record_type	Written review record.
source	Apple source used for the record.
podcast_id	Numeric Apple Podcasts ID.
podcast_url	Podcast URL used for the run or generated from the ID.
country	Two-letter Apple storefront code.
review_id	Unique Apple review identifier.
author_name	Review author name when available.
author_url	Apple review profile URL when available.
title	Review title.
content	Full customer review text.
rating	Star rating from 1 to 5.
version	Podcast version associated with the review when supplied.
updated	Review timestamp in ISO 8601 format.
vote_sum	Net helpful vote count.
vote_count	Number of helpfulness votes.
review_url	Apple Podcasts review page URL.

Empty and null values are omitted from each dataset item, so the output stays compact and useful for analysis.

How to use the Actor

1. Open the Actor in Apify Console.
2. Enter an Apple Podcasts URL or numeric podcast ID.
3. Select a country and review sorting option.
4. Set the result and page limits.
5. Run the Actor and download the dataset or connect it to an integration.

Input Parameters

Parameter	Type	Required	Default	Description
podcast	String	Yes	The Daily example URL	Apple Podcasts URL or numeric podcast ID.
country	String	No	us	Two-letter Apple storefront code.
sorting	String	No	mostRecent	Use mostRecent or mostHelpful.
results_wanted	Integer	No	20	Number of reviews to request.

| max_pages | Integer | No | All available | Optional maximum pages. Leave blank to continue until reviews end; mostRecent can continue beyond the RSS 500-review boundary. | | proxyConfiguration | Object | No | Disabled | Optional Apify Proxy configuration. |

Usage Examples

Collect recent reviews from a podcast URL

This is the simplest run and collects the first 20 recent reviews from the US storefront.

{
  "podcast": "https://podcasts.apple.com/us/podcast/the-daily/id1200361736",
  "country": "us",
  "sorting": "mostRecent",
  "results_wanted": 20,
  "max_pages": 10
}

Use a numeric podcast ID

The podcast name and URL slug are optional when the numeric Apple Podcasts ID is known.

{
  "podcast": "1200361736",
  "country": "gb",
  "sorting": "mostHelpful",
  "results_wanted": 50,
  "max_pages": 2
}

Compare a different storefront

Run the same podcast against another country to collect the reviews available in that storefront.

{
  "podcast": "https://podcasts.apple.com/ca/podcast/the-daily/id1200361736",
  "country": "ca",
  "sorting": "mostRecent",
  "results_wanted": 100,
  "max_pages": 2
}

Sample Output

Written review example:

{
  "record_type": "review",
  "source": "apple_amp_api",
  "podcast_id": "1200361736",
  "podcast_url": "https://podcasts.apple.com/us/podcast/the-daily/id1200361736",
  "country": "us",
  "review_id": "14452700422",
  "author_name": "robdew",
  "title": "This is a great podcast, hosts need to stop saying hmm",
  "content": "Great journalism and great content, but the repeated verbal filler makes some episodes difficult to finish.",
  "rating": 1,
  "updated": "2026-08-20T23:47:26.000Z"
}

Tips for Best Results

• Use the numeric ID when a podcast URL has been copied from a redirect or shortened link.
• Start with results_wanted: 20 to confirm the country and sorting choice before collecting more pages.
• Use mostRecent for ongoing monitoring and for collecting beyond the public 500-review RSS boundary.
• Use mostHelpful when that ordering is more important; Apple currently exposes that ordering through a feed with a 500-review-per-country limit.
• Set the country to match the storefront you want to study. Review availability can differ by country.
• Some reviews do not include a version or author profile. Those empty values are left out of the corresponding item.
• Schedule the Actor for recurring monitoring and compare datasets by review_id to identify new reviews.

Integrations

• Apify API - Retrieve datasets programmatically after a run.
• Google Sheets - Send reviews to a spreadsheet for tagging and analysis.
• Webhooks - Trigger processing when a run finishes.
• Make or Zapier - Route review data into CRM, reporting, or notification workflows.
• JSON, CSV, and Excel exports - Use the format that matches your analysis tool.

Frequently Asked Questions

Can I use an Apple Podcasts URL instead of an ID?

Yes. The podcast field accepts a working Apple Podcasts URL or a numeric podcast ID.

Can I select a country?

Yes. Set country to the two-letter Apple storefront code you want to query. The default is us.

How many reviews can one run collect?

Set results_wanted to the number of written reviews you want. Recent-review pages return up to 20 records per page through Apple’s extended feed. Set max_pages for a page limit, or leave it blank to continue until Apple returns no more written reviews.

Why does mostHelpful stop at 500?

Apple’s public most-helpful feed currently exposes up to 500 written reviews per country. Choose mostRecent to use the extended review endpoint and continue past that boundary. Aggregate star-rating totals are not collected by this actor.

Why are some fields missing?

Apple does not publish every optional field for every review. Missing or empty values are omitted instead of being written as nulls.

Can I run this Actor on a schedule?

Yes. Apify schedules can run it hourly, daily, weekly, or on a custom interval for review monitoring.

Is it legal to collect Apple Podcasts reviews?

You are responsible for complying with Apple terms, applicable laws, and privacy requirements. Use public review data responsibly and only for legitimate purposes.

Related Actors

• Apple Podcasts Scraper - Collect broader podcast information, episodes, and show details.
• App Store Reviews Scraper - Collect reviews from Apple App Store listings.
• Target Reviews Scraper - Collect product reviews for retail research.
• AliExpress Reviews Scraper - Collect ecommerce customer feedback and ratings.

Support

For issues or feature requests, use the Issues tab on the Actor page or contact the developer through Apify.

Legal Notice

This Actor is intended for legitimate collection of publicly available review data. Users are responsible for complying with Apple terms of service, applicable laws, privacy rules, and any restrictions on storing or redistributing collected content.