bigfunctions > get_appstore_reviews
get_appstore_reviews¶
Call or Deploy get_appstore_reviews
?
✅ You can call this get_appstore_reviews
bigfunction directly from your Google Cloud Project (no install required).
- This
get_appstore_reviews
function is deployed inbigfunctions
GCP project in 39 datasets for all of the 39 BigQuery regions. You need to use the dataset in the same region as your datasets (otherwise you may have a function not found error). - Function is public, so it can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
- You may prefer to deploy the BigFunction in your own project if you want to build and manage your own catalog of functions. This is particularly useful if you want to create private functions (for example calling your internal APIs). Discover the framework
Public BigFunctions Datasets:
Region | Dataset |
---|---|
eu |
bigfunctions.eu |
us |
bigfunctions.us |
europe-west1 |
bigfunctions.europe_west1 |
asia-east1 |
bigfunctions.asia_east1 |
... | ... |
Description¶
Signature
get_appstore_reviews(url)
Description
GET Apple App Store Reviews of an app
given its url
Examples¶
Get customer reviews of Nickel App in App Store
select * from bigfunctions.eu.get_appstore_reviews('https://apps.apple.com/fr/app/nickel-compte-pour-tous/id1119225763')
select * from bigfunctions.us.get_appstore_reviews('https://apps.apple.com/fr/app/nickel-compte-pour-tous/id1119225763')
select * from bigfunctions.europe_west1.get_appstore_reviews('https://apps.apple.com/fr/app/nickel-compte-pour-tous/id1119225763')
| ---------------------------------------------------|
| rating | content |
| ---------------------------------------------------|
| 5 | Very simple to use |
| | |
| 5 | I advise you perfectly, |
| | I have been with them for 5 years now, |
| | I have never had a problem. |
| | |
| 5 | Really great. I opted for the black card. |
| | |
| | ... |
| ---------------------------------------------------|
Need help using get_appstore_reviews
?
The community can help! Engage the conversation on Slack
For professional suppport, don't hesitate to chat with us.
Found a bug using get_appstore_reviews
?
If the function does not work as expected, please
- report a bug so that it can be improved.
- or open the discussion with the community on Slack.
For professional suppport, don't hesitate to chat with us.
Use cases¶
A market research team wants to analyze user sentiment towards a competitor's mobile application. They can use the get_appstore_reviews
function to retrieve all user reviews for the competitor's app from the Apple App Store. The team can then perform the following actions:
- Sentiment Analysis: Process the text of the reviews to determine the overall sentiment (positive, negative, neutral) expressed by users. This can provide insights into the strengths and weaknesses of the competitor's app as perceived by users.
- Feature Analysis: Identify frequently mentioned features or functionalities within the reviews. This helps understand what users like or dislike about the competitor's app and can inform feature development for their own app.
- Issue Tracking: Detect recurring complaints or issues reported by users. This can help the team understand potential problems with the competitor's app and proactively address similar concerns in their own development.
- Competitive Benchmarking: Compare user ratings and reviews of the competitor's app with their own to gauge their relative performance and identify areas for improvement.
- Marketing & Strategy: Understand the language and tone used by users in their reviews. This can help craft more effective marketing messages and target specific user needs.
Example: Let's say the competitor's app is "Fitness Tracker X" and its App Store URL is known. The market research team can use the BigQuery function like this (using the US region as an example):
SELECT *
FROM bigfunctions.us.get_appstore_reviews('https://apps.apple.com/us/app/fitness-tracker-x/some_app_id')
This query will return a table with the reviews and ratings for "Fitness Tracker X." The team can then further process this data for sentiment analysis, feature analysis, etc. They could also store the results in a BigQuery table for ongoing monitoring of user reviews over time.
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