Top 5 Fashion Games on Android in El Salvador - Q1 2022

In the first quarter of 2022, the top 5 fashion games on the Android platform in El Salvador showcased varying trends in weekly downloads, revenue, and active users. Here’s a closer look at how each app performed.

Project Makeover from Magic Tavern, Inc. experienced fluctuations in its weekly downloads, which started at 2.2K and saw a peak of 3.5K in mid-January before tapering off to 1.1K by the end of March. Revenue for the game showed a consistent upward trend, starting at $111 and peaking at $216 in the last week of March. The weekly active users also saw a slight decline over the quarter, starting at 12.1K and ending at 11K.

Crowdstar Inc's Covet Fashion: Dress Up Game had modest weekly download numbers, oscillating between 55 and 87 throughout the quarter. Revenue for the app spiked significantly to $328 in mid-February but generally hovered around lower values, such as $56 and $145. Active users saw a gradual decline from 398 to 332 over the three months.

Pocket Styler: Fashion Stars by Nordcurrent Games showed a steady pattern in weekly downloads, maintaining numbers around 400 to 600, with a peak of 685 in late January and another peak at 576 at the end of March. Revenue remained relatively stable, starting at $114 and ending at $75. Active users increased from 877 to 1.3K, indicating growing engagement.

Love Nikki-Dress UP Queen from Elex had minimal weekly downloads, with numbers mostly below 10, except for a few sporadic increases. Revenue also showed low values, peaking at $103 in mid-February. The number of active users saw a slight fluctuation, starting at 237 and ending at 190.

Super Stylist Fashion Makeover by CrazyLabs LTD saw varied download rates, peaking at 3K in early March before stabilizing around 2.3K by the end of the month. Revenue showed a general downward trend, starting at $55 and dipping to as low as $13 before a slight recovery to $46. Active user numbers grew from 8.7K to 10.8K by the end of the quarter.

These insights are based on data from Sensor Tower. For more detailed information and further insights, visit Sensor Tower's website.