Sentiment analysis helps you to better understand the feedback your app receives. If you want to know how users really feel about your app, sentiment analysis should be one of your regular business tasks.
What is sentiment analysis?
Sentiment analysis, also known as opinion mining, is an analyzation process that uncovers the emotions behind the words being used in an app review. These emotions are usually categorized as positive, negative, or neutral.
Sentiment analytics reveal the true opinions and feelings that users have about your app, giving you a better understanding of how your app is being received by the public. How users feel about your app affects its level of success.
There are a few different ways to carry out sentiment analysis:
- Automatically, with the use of machine learning;
- Manually, with a human overseeing the entire process;
- A combination of the two, which involves a human checking and correcting the automated results that sentiment analysis tools come up with. These corrections gradually improve machine learning so that the analysis tools can provide more accurate results.
Why should you conduct sentiment analysis?
There are many benefits to paying attention to sentiment analytics, as seen in the list below.
- Social media monitoring – Sentiment analysis isn’t just for analyzing each app store review. It can also be used when reviewing what is being said about your app on social media, giving you an idea of how the public feels about your app;
- Market research – Understanding how users feel about your app can help you improve it so that your app is more attractive to your target market;
- Discover common problems – Sentiment analysis reveals issues that are most common for your app, guiding you to the problems that should be prioritized and fixed first;
- Prepare for the future – Keeping an eye on public opinion will make you aware of when those opinions start changing. When these changes begin to occur you can get a headstart on updating your app in order to meet the new needs of your target market.
Future of sentiment analysis
Sentiment analysis tools have come a long way, but they aren’t perfect. This is because it can be difficult for a machine to correctly interpret sarcasm, slang, or misspellings.
For example, when an app store review contains positive words that are used sarcastically the analysis software might incorrectly categorize the feedback as positive. But a human is able to consider the context of the message and properly categorize the app review as negative.
As of now, it’s probably best to use a combination of automated and manual sentiment analysi. But tools are constantly improving, as machines are being taught our evolving language.
Sentiment analysis also needs to expand its interpretation of human emotions to reach beyond positive, negative, and neutral. After all, human feelings are far more complicated than those three basic categories.
Although it might seem impossible for emotions like fear, doubt, excitement, and others to be measured by technology, there might be a time when this becomes possible.
Such progress in analysis technology would provide even more insight, helping developers know what improvements need to be made to their apps.
Although sentiment analysis hasn’t yet been perfected, you can start implementing it into your business plan right now. The better you understand how users feel about your app, the sooner you can improve your app and acquire even more users.
Contact an ASO specialist to get help with increasing your app’s visibility and getting more users.