NLP at the Core of App Review Insights

The average Android app has over 2,500 reviews. These reviews help to influence consumer purchasing behaviour, with nearly 60% of users checking the rating of an app before downloading it. With this in mind, it is of vital importance to app developers to understand the content of their reviews.

However, it isn’t always feasible to read and comprehensively understand app reviews, especially for popular apps with thousands of detailed reviews. That’s where NLP-powered app review insight tools such as NetGeist come into play.

Challenges faced in analyzing app reviews

The content within app reviews can help to guide product development, marketing strategies and to maximise user retention. It is easy to understand why businesses and app developers are keen to analyze their app reviews, but many face difficulties doing so manually.

The sheer volume of reviews can represent a challenge, especially if the reviews are written in a variety of languages. Some reviews will be detailed and comprehensive, whereas others will be short and ambiguous. The context that has inspired a user to write a review may not always be clear, which poses problems even to a human trying to understand the review. 

As apps update, introduce new features whilst sunsetting others, the sentiment towards an app can change, which can be difficult to analyse qualitatively. In the early iterations of an app, it could be praised heavily for a feature that later becomes a major weakness. Think of the iPhone camera, what was once heralded as one of the main selling points of the Apple smartphone has become a bone of contention compared to rivals with more advanced offerings. 

These challenges can all be overcome by use of an NLP-powered app review insights tool.

What is NLP?

NLP, or natural language processing, is a subfield of AI. It bridges the gap between human language and computer processing. NLP solutions, such as chatbots and virtual assistants, enable computers to understand, generate, analyse and respond to human language.

By combining linguistics with machine learning, NLP solutions can process vast amounts of textual data, making it ideal for extracting valuable insights from app reviews. 

Key uses of NLP for app review analysis include:

• Sentiment analysis will determine whether the review is positive, negative or neutral. More specifically, aspect-based sentiment analysis will provide insights into the emotions expressed about specific aspects of the app, such as the customer support
• Named entity recognition will extract specific entities, helping app developers to analyze mentions of specific features, functions or even competitors
• Text summarization can condense lengthy reviews into actionable summaries, making it easier for developers to analyze key themes
• Topic modelling will segment common topics discussed within the reviews into categories, information that is sometimes then presented as a wordcloud

How do NLP app review analysis tools work?

Step One

As with every NLP project, the first stage of model development is to collect the data. In this case, the data is the reviews. These can be collected from various sources, including app stores, social media and user forums. The data should include a diverse selection of reviews, ranging from positive reviews from your advocates, through to negative reviews from your biggest critics, and everything in between. 

Step Two

The data will then be cleaned and processed, removing irrelevant content such as emojis and HTML tags. An important part of training an NLP model will be normalization of the data, converting it all into a standardized format such as lowercase. This data will then be tokenized, breaking down the text into individual words or phrases.

Step Three

The text will then be labeled, with relevant tags such as the sentiment or topic added. This will create a training dataset for the model to learn from.

Step Four

Once the data has been labeled, the model training will begin. Choosing the appropriate model will depend upon the desired accuracy and complexity of the required task. The model will be optimized to improve accuracy, precision and recall, and then will be thoroughly validated and tested on unseen data to evaluate its performance.

Step Five

If the NLP model is deemed accurate enough, it can be rolled out to process real-world app reviews!

Benefits of using NLP for app review analysis

NLP automates the extraction of useful insights from text, helping developers to make informed decisions to improve the user experience, improve engagement, boost engagement and to introduce valuable new features. 

It does so by spotting trends and patterns within big data. These patterns are supported by a deep contextual understanding of the reviews, helping stakeholders to truly understand the opinions of their users. Sentiment analysis data can be used to track user satisfaction over time, helping developers to understand how the changes they are making to their app will affect the user experience. 

By categorizing reviews into common themes, NLP-powered app review analysis tools can help developers identify key areas that either require attention or should be championed. If a certain feature is mentioned positively within a large quantity of reviews, this could be important information for the marketing team to capitalize upon. On the other hand, if negative reviews regularly refer to a specific part of the app, this should be the area where changes may be necessary. By doing so, these insights could help app developers to increase signups in the first place, whilst maximising user retention and satisfaction.

Introducing NetGeist App Review Analysis

At the forefront of app review analysis tools is the NetGeist tool known for providing clever app review monitoring. This NetGeist tool helps you to gather, analyze and monitor what customers are saying about your app in real-time. 

The tool enables you to discover what people are saying about your app, presenting the data in easy-to-understand charts and customizable reports. 

It isn’t just your app either, NetGeist can be used for competitor analysis to find out what users are saying about your competitors.

Whether you are a solo developer or part of a wider team, NetGeist will provide you with the actionable recommendations you need to improve your app. Trained on over 10 years of data and 500 million reviews across over 200,000 apps, it is the powerful tool you need to understand your user like never before. 

Whilst NetGeist is developed with app developers in mind, it is also proving popular with marketing agencies and in-house teams. When the raw quantitative data of platforms like Google Analytics is not enough, marketers are turning to tools such as NetGeist to learn about their products and where they should focus their efforts.

NetGeist NLP solutions are developed by Neurotechnology for businesses and government entities. Request a demo to see how the NetGeist app review will help your business to grow in 2025.

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