Using Apxor’s Habits Framework, Samosa sought to understand Habit Trends and Habit Strengths. Here’s what came to light – After the introduction of Video feature, many users started using it more and more. The number of times Audio feature was used by existing users remained the same, however, the number of users using the feature decreased.
GiFs feature showed a decrease in both Habit Trends and Habit Strengths. GiFs now became a front heavy feature, which worked well only with D0 users. User Engagement with videos remained constant from D0 – D30. Users watching Videos were retained better.
Samosa now understood that the Video feature was a great feature for its App. To create more Engagement and Retention, Samosa needed to promote the Video feature.
To understand what categories of videos worked the best, Samosa used Apxor’s Behaviour Correlation Framework to study the behaviours of D30 users. They correlated the week wise behaviour of these users and understood that – Movie clips and Viral videos were doing well, while videos shot with personal cameras were not performing well. Samosa sought for more granular data for the kind of Movie clips that were performing the best. It understood that Movie clips related to Comedy and Love Quotes were most popular. Samosa started promoting trending videos of popular categories on the app’s landing page to D0 users.
These granular analyses and insights into Samosa App’s features, helped it gain an all rounded improvement in Retention, Engagement, and overall App performance. While only 10% of D30 users were still watching GiFs and listening to Audios, 80% of D30 users continued watching Videos.
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