Semantic Analysis: how to analyze customer reviews
IN THIS ARTICLE
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.
We now support 20 languages. There are 3 language groups that can be added to the tariff plan:
- English and Russian;
- Portuguese, German, Italian, Spanish, French, Dutch;
- Arabic, Indian, Chinese (s), Japanese, Korean, Bengali, Hindi, Thai, Vietnamese, Turkish, Urbu and Persian.
To activate the feature and add a group to your tariff plan please reach our support team.
AppFollow Semantic Analysis toolkit consists of 4 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;
- Wordcloud - visualizes the most frequent words users use in their.
This is where you can find the Semantic Analysis toolkit:
You can use the tool to analyze your favorite apps only. To gather an app’s data, please mark the app as favorite. The data will be gathered within the next 24 hours.
Positive vs Negative
The chart 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.
By looking up by specific words you may find the reviews and statistics for reviews with that words.
The chart shows you how the reviews and their mood have been changing during the chosen period.
Topics & Bug
These two pie charts group reviews in accordance with the topics, customer concerns and complaints. By clicking each of the coloured piece you will be redirected to the Ratings&Reviews page with the list of app reviews filtered by the semantic tag. The list of semantic tags is available here.
Wordcloud lets you quickly get the feelings of your users. It gives you a quick glimpse on what the most frequent words and the tone are used to describe the experience with the app.
Wordcloud supports 18 languages (all languages available on the Semantic Analysis, except for Arabic and Benghali).
Wordcloud could be used to create baseline for auto-reply/auto-tag rules and filter by most common topics on Reply to Reviews page.
How to set up
If you happen to see a splash screen like in the example below, click the button “Enroll beta”, and you will get a 10-days trial 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 is a bunch of filters you can use:
- Filter by review content: use it to filter out reviews by specific words. Note: If you'd like to include several words, apply '' | '' (e.g. bank | account to see the reviews that contain bank OR account) or '' & " (e.g. bank & account will show those reviews having bank AND account together in one review)
- Select reviews: shows critical (one- and two- star reviews); favourable (four- and five- star reviews); and featured ones;
- All versions: allows you to analyze different app versions separately;
- Date: by default, the data is displayed for the previous 30 days. By clicking the dates, you can choose the time period you need.
- All languages: filter to evaluate customer sentiments by language.
Report Semantic Tag as Incorrect
If you have noticed that the semantic tag was assigned to the wrong review, now it is possible to report Semantic Tag as incorrect.
By clicking on 'Report as incorrect', the semantic tag will be removed from the review, so that you can see only correct reviews by applying the filter.
The information about the reported tag will be used in the future to update our Semantic model to make it more accurate.
Export reviews with semantic tags
With the method 45. Reviews Semantic Tags you can export all the reviews with the semantic tags via API. You can get semantic insights without entering your AppFollow account and optimise the process of analysing your app reviews.
Need help? Hit the chat button — we are all ears!