How to export Google Play and App Store reviews to CSV (both stores, one format)
App reviews are the cheapest user research you'll ever get: thousands of people telling you exactly what's broken and what they want. The problem is getting them out. App Store Connect and Google Play Console only show reviews for your own apps, in two different formats, with clunky exports. Apple's old RSS review feed that many tutorials still point to now returns nothing. Most scraping tools…
Exporting Google Play and App Store reviews to a CSV file is a valuable way to gather user feedback from both platforms. App reviews provide honest opinions on app issues and desired features. However, manually exporting reviews from each store can be cumbersome, especially when you want to compare data side-by-side. The App Reviews Scraper tool on Apify simplifies this process by pulling reviews from both Google Play and App Store consoles in one run.
To use the tool, you need to provide the app package names or links for Google Play and App Store links/IDs. The tool can handle mixed lists of these identifiers, making it convenient to work with multiple apps and stores simultaneously. Each review returned by the tool includes key information such as store, appId, country, rating, title, text, date, appVersion, thumbsUp votes, developer replies, developer reply date, username, and review URL.
The tool is designed to be fast and efficient, pulling up to 4,200 reviews from 7 apps across 2 countries in under 11 seconds during testing. No browser or proxy is required, resulting in quick execution times. To see the output before running any code, you can use a pre-filled one-click example that retrieves the 500 newest reviews for Duolingo from both stores. Simply open the example, click 'Start', and review the results.
To start the export process in Python, you'll need to install the `apify-client` library and `pandas`. After installation, import the required modules and create an instance of the ApifyClient using your API key. Then, call the App Reviews Scraper actor with the desired input parameters, including a list of apps, countries, the maximum number of reviews per app per country, and the sort order (newest in this case).
The results are then processed into a DataFrame using Pandas, which is saved as a CSV file named 'duolingo_reviews.csv'. The script also calculates the average rating for each store using the `groupby()` method on the 'store' column. This CSV can be easily shared or imported into other tools for further analysis.
To monitor new reviews regularly, you can adjust the sort order to 'newest' and include a 'since' parameter to specify the date from which reviews should be fetched. By running this script daily, you ensure that only new reviews are retrieved, optimizing costs and minimizing data repetition. The resulting CSV can then be used to identify common issues, track feature requests, and analyze whether app updates have resolved or introduced new problems.
Remember to aggregate and analyze reviews carefully, focusing on aggregate insights rather than individual reviewer names to maintain user privacy.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
