Intent analysis is a natural language processing technique that classifies text based on what the author intended to convey with their review.
Intent analysis is a natural language processing technique that classifies text based on what the author intended to convey with their review. Not every review is actually conveying something useful that you can act on, so we have predefined eight categories of intent that cover the most useful review feedback.:
- Design: Reviews that mention the design and navigation of an app. This also includes reviews speaking to the frequency or obtrusiveness of advertisements in the app.
- Service: Reviews that mention the core service offering provided by the app and whether the services rendered through the app were valuable or useful to the end user. An example of core services offered is the quality or number of matches on a dating app.
- Performance and Bugs: Reviews that mention the technical performance of the app, good or bad. An example of strong performance can be an app that is smooth, fast, and reliable. An example of poor performance can be an app that is slow, buggy, and crashes often.
- Login: Reviews that mention user registration, setup, and login.
- Feature Requests: Reviews in which the user describes, requests, or comments on the absence of features or additions to the app.
- Support: Reviews that mention services or offerings provided by the customer support team associated with the app.
- Payment: Reviews that mention the how payments are processed through the app or the price of goods/services associated with the app.
- Notifications: Reviews that mention notifications and alerts that the user receives through the app.