It can be difficult for an app publisher to promote your app and acquire new users. This can be overcome by using paid user acquisition, viral mechanisms, or a variety of other methods.
Your ultimate goal is to drive visitors to the Play Store so they can download your app. But have you ever considered why visitors choose to download the app? What factors influenced their decision?
Assume you're looking for an app. Following the search, there are two apps that "appear" to be good. Which would you download if one had a 3.8 rating and the other had a 4.5 rating? The answer is obvious.
Today this post will explain how we improved a calling app's ratings and reviews. After ASO World's optimization, this app has increased by 75% of app ratings and reduced by 70% of negative feedback.
This calling app is a mobile application that provides caller ID, call blocking, and call recording. It uses the user's community-generated content and social networking services to provide background information about the entities behind incoming or outgoing calls.
The app‘s name remains anonymous here to protect the privacy of our customers. To give you a better idea of the app's story we're sharing, we show one of its competitors on the Google Play Store
App Store Optimization challenge
Before we started ASO, this calling app's rating was 3.9, with only 8k ratings on average per month. Their rating used to be about 4.3 but had dropped.
App Store Optimization solution
We began with this assumption
Our initial assumption was that most users only rate the app when asked to do so. We decided to test the following parameters based on this assumption:
● When we display a rating popup to users (timing)
● The frequency
● Design of popup & UI (user interface)
We also took a step back and examined the following data from the Google Play Console:
● Countries of users who rated and reviewed
● Rating Errors in Languages (see below)
● The number of people who rated the app
● Reviews - what our customers had to say about us, both positive and negative.
We came to a few conclusions after analyzing this data. We then began to implement tests and monitor the results based on these findings.
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Conclusions for Popup Optimization
Here are the specific optimizations we tested and the results.
We examined the app and attempted to define the value it provides to the user. We defined three scenarios:
● Detecting a caller
● Detecting a Spam Call
● When a user sends a friend an app invite
Simple questions with a clear call to action (Call to Action)
We discovered that you should not ask lengthy questions. Instead, ask simple questions and, more importantly, let your customer know what you expect from them (a rating in the store).
Every 14 days, we asked our users to rate the app. If the user interacts with the popup, it will not be displayed again.
It is critical to remember not to push your luck too far. Being overly aggressive can have the opposite effect.
Do not put it off too long. We used to ask the user for a rating after only 10 days of use, "letting" he get used to the app. We've discovered that users form opinions about the app much sooner, sometimes within a day.
App Review optimization tips
● Not all users from all geos behave in the same way! We discovered that we have some problematic countries where users tend to give us a negative feedback. In these genes, we delay the popup and give the user more time to experience the app before asking for a rating.
● Translate your messages into all of the languages supported by your app. Especially at this critical juncture, you must "speak" the user's language.
● We discovered that there is one country where we have 40% "wrong" ratings. This means that a review may say "great app," but it only has one star. In these countries, we try to explain the ratings better by showing the user a 5-star image that represents the expected result.
● Make certain that your app description is completely accurate. We discovered that if there is a small gap between expectations and the actual app, users will leave a negative review.Related reading: Case studies about how we work with App Reviews:
What We Did and How We Got
To summarize, here is what we did to improve our results.
● Improve popup design by including images, clear and concise messages, and translating the messages into the user's language.
● Popup Timing- Making the user see the popup at an earlier stage.
● In some countries, the rating popup will be delayed.
● Customer service entails responding to all users who contact you via the app.
● Finally, and perhaps most importantly, we listened to our users by working to resolve issues that arose, and as a result, we improved the app significantly.
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App Store Optimization result
After our optimization, we've got a total of 350k app ratings, 150k ratings this year, and 90k the year before. This calling app reduced 70% of negative feedback.