Semantic Analysis: how to analyze customer reviews
Sentiment analysis of app reviews allows you to quickly detect user-impacting issues that lead to user dissatisfaction, lower app ratings, and uninstalls. Semantic Analysis toolkit is designed to provide a helicopter view on customer experience and detect the app’s potential lacks before they got critical. ML algorithms in the core deeply analyze the meaning of all reviews no matter how many of them an app gets or what rating they have.
AppFollow Semantic Analysis toolkit consists of 5 tools:
- Positive vs Negative — arranges app reviews depending on their emotional tone;
- Topics & Bugs — gives you a quick overview on customers current and potential issues;
- Sentiment Score — shows the overall satisfaction level;
- Feelings Chart — visualizes and groups the topics and questions that customers are talking about;
- Wordcloud — shows the most popular words from app reviews together with their emotional tone.
This is where you can find the Semantic Analysis toolkit:
Positive vs Negative
The graph shows user attitude toward the app: positive, negative, neutral, and mixed feelings of users that haven’t chosen the sides.
This tool helps you get the emotional tone of reviews and doesn’t cover the ratings of these reviews. If a user rates an app with a 1-star review and asked a question there, it won’t be counted as negative.
By hovering over the columns, you will see how many reviews each of them has and the average rating of these reviews.
Topics & Bugs
These two pie charts group reviews in accordance with the topics, customer concerns and complaints. By clicking each of the colored piece you will be redirected to the list of app reviews gathered by the topic.
The chart shows the ratio between reviews with positive and negative emotional tone where 100% means the exceptional user satisfaction, and 0% — very poor results.
This chart groups questions and concerns depending on the topic, not the rating. Sometimes the groups will consist of reviews with different emotional tones (red and grey, yellow and green, etc), this means that they’re gathered by a common issue or question. In the example below the lower group is united by the registration issues.
By clicking the review bubble you will be redirected to the page where you can reply to this customer.
This tool displays the most common words that customers use in their reviews.
The color is related to the emotional tone used in a review: red is negative, green is positive, and grey is mixed or neutral reaction. The word can be used several times in different colors: “voice calls” can be an issue, and in this case they will be red. When users are satisfied with them, the word will be green.
The size of words shows how frequently they are used. The bigger a word is, the more often customers mention it.
By hovering over a word you will see how many times it was mentioned and the average rating of the reviews with this word. Click on the bubble to see the whole list of these reviews and be able to reply to them.
You can also export the Wordcloud to use in the reports or share on public. There are 2 varieties available: the regular one (like in the example) and the Export 3 that groups the words into the rounded bubble. If you have thousands of reviews and over 200 popular words, you will have the Export 2 option made of AF letters bubble.
How to set up
If you happen to see a splash screen like in the example below, click the button “Yes, please notify me”, and you will get the access to it within a few hours.
You don’t need any further settings, the data about favorite apps will be gathered and updated automatically.
How to filter
There are several filters you can use:
- Select reviews: shows critical (one- and two- star reviews); favorable (four- and five- star reviews); and featured ones;
- All versions: allows you to analyze different app versions separately;
- Select country: new filter to analyze customer sentiments in different countries. Will be available in the next update;
- Date: by default the data is displayed for the previous 30 days. By clicking the dates you can choose the time period you need.
Need help? Hit the chat button — we’re all ears!