Reviews

Enable the ability to retrieve individual download-level data for iOS and Android apps through the AppFollow API, rather than only daily aggregated totals. The goal is to access more granular information for each individual download (e.g., per-download entries instead of per-day aggregates) to support user-level journey analysis. Currently, the API provides only daily aggregates by channel, which limits deeper analysis. Users would benefit from an endpoint or parameter that returns download events individually, including any possible identifiers or metadata available from the stores.

APIs to get the user device ID, device model, etc., of users who have downloaded the application API to get user device ID, device model details, etc., of users who have provided feedback on the app in the public stores.

You can now view the number of reviews for each app in the system, but graphs only show one product at a time — you need to manually switch between apps. This makes it impossible to see the overall dynamics and compare the load between all products at the same time, especially when there are a large number of applications. We would like to be able to: compare the number of reviews between multiple apps, assess the overall and relative workload on the team, see trends and plan resources based on a complete picture of all products.

We're using Gorgias (kind of like Intercom, Zendesk), it would be great with an integration!

Find issues faster and set automation (tags/replies) Give me report for [app] [period of time]

I would like to have an API endpoint that allows me to retrieve the current API credit balance of my account. This feature would be beneficial for integrating the balance check into our automated systems, ensuring we can monitor and manage our API usage more effectively.

Weekly report detailing review rating and star rating by devices (top device for 1 star ratings, top device for 5 star ratings, etc.)

Lang is detected, but sometimes it's wrong.

We created different 3 rules for a single topic: with keywords, with tags and with semantic tags, semantic tags prioritized. But only the rule with keywords generated replies, even though it has the lowest priority among all 3

Implement a new automation action that enables users to automatically send customer reviews to various helpdesk platforms including Zendesk, Helpshift, and other help desk services.