AI Insights · Timothy · January 2023
Top 5 Fashion Games Performance in Guatemala - Q4 2022
Explore the performance of the top 5 fashion games in Guatemala for Q4 2022, including trends in downloads, revenue, and active users.
In the fourth quarter of 2022, the top five fashion games on a unified platform in Guatemala showed varied performance in terms of weekly downloads, revenue, and active users. Here's a closer look at how each game fared.
Project Makeover from Magic Tavern, Inc. saw a steady increase in weekly downloads, peaking at approximately 3.7K in the final week of December. The game's weekly revenue also showed an upward trend towards the end of the quarter, reaching around $494. Active users fluctuated throughout the quarter, ending with a high of about 23.5K in the last week of December.
Crowdstar LLC's Covet Fashion: Dress Up Game experienced a notable increase in weekly downloads, starting with 80 and growing to 295 by the end of December. Weekly revenue peaked at $246 in mid-December. The game also saw a rise in active users, ending the quarter with 654, up from 395 at the start.
Super Stylist Fashion Makeover from CRAZY STYLE LTD had a strong performance in weekly downloads, peaking at around 6.1K in the last week of December. The game's weekly revenue also increased significantly, reaching $245 in the same period. Active users saw a substantial rise, ending the quarter at approximately 30.1K.
Love Nikki-Dress UP Queen by Galaxy Play Technology Limited had modest weekly revenue, peaking at $69 in mid-November. The game’s active users remained relatively stable, fluctuating between 255 and 409 throughout the quarter. Weekly downloads were minimal, with occasional spikes, but no data was recorded towards the end of December.
Pocket Styler: Fashion Stars from Nordcurrent UAB saw a gradual increase in weekly downloads, with a peak of 184 in the final week of December. The game's weekly revenue peaked at $79 in late November. Active users fluctuated slightly, ending the quarter at 794.
These insights are based on data from Sensor Tower. For more detailed analytics and insights, you can visit Sensor Tower.