BitMango increased the response rate by 2.3 times in 3 days with AppFollow's Auto-replies

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Mary Kulikova
BitMango increased the response rate by 2.3 times in 3 days with AppFollow's Auto-replies

BitMango is one of the largest global mobile puzzle game publishers. It has grown from 40 million downloads in 2015 to 420 million at the end of 2017 and is now getting about 6 million monthly downloads. Supporting over 100 apps in the App Store and Google Play Store, BitMango gets up to 400 reviews daily.

Challenge

The Customer Support team strives to address each and every customer’s feedback. But with this significant amount of user feedback, they used to spend their time on repetitive replies to typical reviews, including "Thank you" notes, or common reviews about ads. App Store Connect and Google Play Console couldn’t provide BitMango with the right tools to organize reviews and so react swiftly to the ones that matter most. To improve their support efficiency, BitMango turned to AppFollow and its support solution, Auto-replies.

Solution

AppFollow Auto-replies were intended to free up the team from replying to the majority of positive reviews and common complaints so that the Customer Support Managers could focus on the reviews that require a personal touch. 

Results

Using 10 Auto-reply rules, the team covered over 2,000 reviews in just three days, increasing the response rate by a record 2.3 times. Not only has the response rate increased, but the response time has also changed — now there were no reviews left unanswered within 24 hours.

How did it affect the Rating?

Often developers decide not to automate their replies or even use templates, thinking that their robotic replies will scare users off. As a result, this approach would lead to only manual replies, lower response rates, and more spending on staff. AppFollow’s Auto-replies addresses this issue through its randomization algorithm. While setting up the auto-replies, BitMango created over 15 templates for each typical issue, e.g., 15 different templates for reviews about ads. Auto-replies publishes these templates randomly, so the team doesn’t look like a robot.

Instead of the rating drop that is usually expected from reply automation, BitMango actually saw rating growth. The team has been using Auto-replies for about a month until now, and the average rating hasn't decreased at all. One of the reasons for this was a faster reaction to the reviews as the majority of replies were processed automatically. With Auto-replies, BitMango managed to reduce Response time by at least 60%.

BitMango’s support team gave us highly valuable feedback on how to improve the randomization algorithm. Our development team has included these suggestions in our roadmap for the next version of Auto-replies. We are most thankful to the support team at BitMango for their help in conducting this research.

BitMango Support Team in Korea

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