Understanding Sentiment Analysis in App Reviews

Sukanya Surby 
Content Marketing Manager

8 min read

As an app developer or marketer, you’ll agree that user reviews are a goldmine of useful information. They provide insights into what users love about your app and areas that need improvement.

One of the most effective ways to gain these insights is through sentiment analysis or mining app store user reviews. This process involves  analyzing user-generated content to gain a comprehensive understanding of user sentiment, preferences, and pain points.

In this blog, we’ll delve into the significance of sentiment analysis in app reviews, and how it can be a game-changer for app developers and marketers.

User reviews serve as a direct line of communication between app developers and their users. Positive reviews can boost an app’s visibility and attract new users, while negative reviews may deter potential downloads. Mining this goldmine provides developers with valuable insights into what users appreciate, dislike, and desire in an app.

Let’s dive into why mining app store reviews can be really helpful for you to make data-driven decisions:

1. Understand what users are saying about your app

Developers and marketers can gain a deep understanding of customer sentiments, pain points, and feature requests by mining user reviews. This, in turn, can inform product development and marketing strategies. By analyzing app store reviews, developers can prioritize feature enhancements or bug fixes based on user feedback. This data-driven approach ensures that development efforts are aligned with user expectations, leading to improved customer satisfaction and retention.

For example, when Netflix removed the popular series The Vampire Diaries from their platform, a lot of users were upset. This was reflected in their reviews, where complaints about “removed content” suddenly increased. This highlights the importance of monitoring content releases for app developers and marketers, not just to stay trendy but to address user feedback efficiently.

The removal of "The Vampire Diaries" from Netflix led to a substantial increase in user complaints, highlighting the importance of closely tracking content releases
The removal of “The Vampire Diaries” from Netflix led to a substantial increase in user complaints, highlighting the importance of closely tracking content releases. Source: AppTweak

In another example, when Duolingo, the language learning app, introduced a new hearts system, it led to a significant rise in negative reviews from users who were unhappy with the change. Instead of ignoring this feedback, Duolingo took it into account and made necessary adjustments to the system. Thus, adapting to user feedback is crucial for successful feature releases and layout updates.

Have a look at these handy tips to monitor app reviews and ratings & drive conversion

2. Perform competitive analysis to identify opportunities

Analyzing app store reviews allows for a comprehensive evaluation of competitors’ apps. This can uncover strengths and weaknesses relative to competitors, identify areas for improvement, and reveal unique selling points that can be highlighted in your marketing efforts.

For instance, AppTweak assisted SoundCloud in creating effective custom product pages (CPPs) on the App Store by analyzing customer reviews. Despite concerns about negative impacts, a sentiment analysis revealed overwhelmingly positive feedback. Delving deeper, the team discovered that users appreciated features like unlimited skips and fewer ads, giving SoundCloud a distinct competitive edge. This insight became a powerful tool for shaping successful future campaigns.

Read more on how AppTweak helped SoundCloud launch new CPPs on the App Store

3. Leverage review sentiment to improve marketing

  • Dive into user reviews to find keywords for ASO: Analyzing user reviews can guide your ASO efforts. This analysis helps to find keywords frequently used by users. For example, if your users often use words like “easy to use,” “innovative,” or “smooth,” and express positive feelings about these aspects, it tells you that these are strong points of your app. You can then make sure to mention these strengths when you describe your app on the app stores. On the other hand, if there are certain keywords associated with negative feedback, it’s a sign that those areas might need some work.

This helps you improve your ASO strategy and ensures that the keywords you use in your app store listing matches the terms your users use. By using the keywords you’ve identified in your app store metadata, you can make your app easier to find and attract users who are looking for the kind of features or experiences your current users enjoy.

  • Mine user reviews to optimize screenshots with features user love most: Analyze user reviews to highlight loved features in screenshots. Reviews reveal favorite app features. Showcase these in your screenshots for clear visuals of your app’s unique aspects. This makes your app attractive on its page, helping potential users quickly identify appealing features. It’s a direct way to impress and prompt more downloads.
Headspace showcases its anxiety management feature in its screenshots, following user praises about how the app has helped them handle anxiety
Headspace showcases its anxiety management feature in its screenshots, following user praises about how the app has helped them handle anxiety.

Review sentiment analysis on AppTweak

With AppTweak’s AI-powered App Reviews Manager, you can easily gain invaluable insights into user feedback to help you gauge customer satisfaction and identify areas for improvement. Armed with this data, you can craft more effective strategies, make informed decisions, and ultimately create apps that truly resonate with your audience.

Sentiment analysis in ASO

AppTweak’s Sentiment Analysis lets you see which keywords are most repeated across your app’s reviews. This helps capture what your users are mostly talking about when referring to your app. For each keyword in the analysis, we show the average rating of the associated reviews, so that you have a sense of users’ sentiment regarding that word and a trend over time so that you can see if the use of this keyword is quite recent or stable over time.

Most repeated keywords across Gardenscapes latest reviews (Play Store)
In this example, we see the most repeated keywords across Gardenscapes’ latest reviews (Play Store). Source: AppTweak

Already, we can see that there are few highly repeated keywords associated with a high average rating, only the words “best game”, “awesome” and “amazing” come out with an average above 4. Among the keywords associated with most negative ratings we find “money”, “impossible,” “pay”, and “spend.”

For each keyword in the analysis, AppTweak gives a shortcut to directly access the corresponding reviews in order to better understand the context in which users are using these words. For instance, upon analysis for the keyword “money,” it was evident that users expressed dissatisfaction with the game’s pervasive prompts for spending money to buy items or to go to the next level.

Based on this feedback, the game’s product team could identify the specific concerns about the frequent in-app purchase prompts and make necessary adjustments to the game’s design.

Classify reviews with tags in App Reviews Manager

In an effort to streamline your team’s review management process, App Reviews Manager incorporates templates and tags. These allow you to save and repurpose effective replies for similar use cases in the future, for example, adapt responses for specific languages or cultural references, address recurring bugs, maintain a consistent tone post-issue resolution, and prompt users for additional information.

In our Tags section, you’ll get an overview of all your tags, their frequency, and the average rating of tagged reviews. You can also leverage tags to sort reviews by topics, such as “bug” or “feature request.” For broader categories, you can tag individual reviews or use “tag all.”

Review Management with GPT-4

Centralize all your app store reviews & increase efficiency with GPT-4 reply suggestions, templates, Zendesk integrations, and more.

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Machine learning with AppTweak’s data scientists

With our home-grown Atlas AI at the heart of AppTweak’s platform, our data scientists were quick to leverage machine learning to analyze a vast database of app store reviews. We experimented with smart techniques that focused on word frequencies and their associated semantics.

Our team chose a set number of unique topics for the machine learning model to find. The model then figured out the most distinct topics in all of the reviews it was given. It could also look at any specific review and score it based on each topic it found.

This method helped us overcome some limitations we had faced with ChatGPT:

  • We can now link any topic back to a group of reviews that the model analyzed
  • Every review, whether old or new, can get a score for each topic
  • We can find more than one topic in a single review, track how a topic changes over time, and receive alerts if a new topic suddenly pops up

Learn more on how we studied the potential of a dedicated AI model to extract valuable insights from app store reviews


In short, sentiment analysis in app reviews is an invaluable tool for app developers and marketers. It provides an in-depth understanding of user sentiments, allowing you to identify areas of improvement and user satisfaction. By strategically leveraging this insight, you can enhance your app’s features, rectify issues, and ultimately boost customer satisfaction. Remember, every piece of feedback is an opportunity to improve and grow.

Interested to perform a keyword analysis on your app store reviews to identify what users are talking about? Schedule a demo now!

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Sukanya Sur
by , Content Marketing Manager
Sukanya is Content Marketing Manager at AppTweak, creating intriguing content for app marketers. She possesses strong editing skills, delights in storytelling, and holds a deep appreciation for classic literature.