If you’re lying awake at night staring at your phone, you’re not alone! We dug into user behavior and device profiles across North America to see how consumers connect, what devices are most popular, and more. We’ve organized all of this information in one handy infographic!
With a presence in more of the Top 1000 apps than anyone but Google, we’re able to surmise a lot about general user behavior and trends just by looking at ad requests.
Apple Outpaces Google & Size Isn’t Everything
In addition to users generally favoring wifi for their app usage, Apple continues to outperform Android when it comes to publisher monetization.
While it’s too soon to see the impact of the iPhone X or iPhone 8, it’s clear that many users are using and monetizing on older devices. The iPhone 5S and Samsung Galaxy S5, released in 2013 and 2014 respectively, both had strong showings for monetization. Even after a year, the iPhone 7 was still only the number 5 iPhone.
Likewise, more expensive phones with larger screens may deliver a bigger picture, but they don’t necessarily have the market penetration we assume. The now almost-standard 4.7-inch to 5-inch displays ousted most larger devices from the top 5 on both Android and iOS.
Larger screens are popular, but they’re still far from standard.
Evenings are Mobile Primetime
Once people wake up in the morning, mobile device usage rises steadily as the day goes on. The rise sharpens a bit as people get home from school (3 pm) and again from work (6 pm) Usage continues to climb until 9 pm, when it begins to decline as users get ready to head to bed.
There’s oodles of information on how consumers are engaging with their devices in the full infographic, including connectivity method, more device breakdowns, and more.
Check out the whole infographic below (click for the full-size version!):
About the Data
All figures and data were sourced from the AdColony platform from April through June 2017. Activity and engagement were gauged on ad requests received by ads using the AdColony SDK. All ad requests were analyzed in aggregate and contain no identifying information for individuals.
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