Sentiment Analysis tool for app reviews & Amazon reviews, powered by AI
Appbot's online sentiment analysis tool helps you identify issues early and measure improvement.
Sentiment Analysis across all app stores and countries
Leverage AI-powered sentiment analysis and see what your customers really think of your apps and products.
Appbot automatically fetches your reviews to provide you with near real-time sentiment analysis across all stores. Our app review tools track all countries for all stores, right out of the box.
Appbot also offers insights into the keywords and topics that are powering customer sentiment for your brand, without reading each review manually.
Get answers faster.
Appbot's Sentiment Analysis AI has been specifically trained on large data sets of reviews and has been tested by teams from the world's top brands. Our algorithms can handle the nuanced language that is commonly used in reviews - everything from emoji to abbreviations.
Our Sentiment Analysis AI can help you to answer questions like:
- How did our recent app update affect sentiment?
- What do customers think of our new feature?
- What phrases are most common in our 1 & 2 star reviews?
- What are the word, phrases and topics most common in our 5 star reviews? What about for our competitors?
Analyze sentiment by keywords, topics, tags and more
Sentiment Analysis is vital for teams to understand how users feel about their apps, but that's only the part of the picture. Appbot also makes it easy to understand why your customers feel the way they do about your apps, with advanced text analytics.
Appbot reads all of the app reviews and Amazon product reviews that you connect to your account. Our bots group pieces of feedback together according to sentiment, topics and keywords. Use the Words tool to see what the most commonly used keywords in your reviews are, use Topics to see what themes are popular with customers. Appbot even makes it possible for you to design your own automated Custom Topics or create Tags to apply to chosen reviews manually.