Text analytics designed specifically for app reviews

Automatically categorize reviews by phrase, word or topic with Appbot's intuitive tools.

Natural Language Processing illustration

Top apps use text analytics to stay in front

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Example of natural language text analysis

The importance of text analytics for apps

Text analytics refers to automated techniques for aggregating and understanding the thematic trends in a body of text. Text analytics tools offer actionable insights into the themes that are powering customer sentiment for your apps, without the need to read each app review manually.

Appbot's text analytics tools highlight things that delight your customers, what frustrates them and how the changes you make to your apps are perceived by your users. Get instant, useful feedback from your own customers and improve faster than ever.

Examples of different classification types

Text analytics power better roadmap decisions

Appbot's text analytics tools are designed specifically for the nuanced language used in app reviews. Think emoji, abbreviations, or shouty reviews full of capitalization or punctuation. Appbot's text analytics tools can help you to answer questions like:

  • What is the sentiment for reviews that mentions our new feature?
  • What do customers think of our app's new design?
  • Are bug reports trending up or down in our reviews?
  • What is our most popular feature request?
Supported app store channels

Spot trends in app reviews
before they affect star ratings

Focus on improvement, not data analysis. Appbot saves your team hours every week by automatically aggregating and analyzing your customer feedback from all major app stores:

Illustration of sentiment breakdown

More than just text analytics

Appbot's algorithms automatically aggregate and analyze your app reviews and ratings, using a series of techniques. Appbot's suite of app review analysis tools let you dive deep into:

  • Sentiment
  • Ratings
  • Words, Phrases, Topics, Custom Topics & Tags
  • Emotions
  • ... quickly and easily.