The Quest to Understand Metric Movements
Suppose you just saw an interesting rise or drop in one of your key metrics. Why did that happen? It’s an easy question to ask, but much harder to answer.
Showing 20 of 122 articles (Page 1 of 7)
Suppose you just saw an interesting rise or drop in one of your key metrics. Why did that happen? It’s an easy question to ask, but much harder to answer.
Coinbase fine-tunes network calls to make their app feel snappier for users.
Meta fine-tunes Threads on iOS to keep it fast and frustration-free.
Grab speeds up their GrabX SDK startup to get users rolling quicker.
Our GrabX clients noticed that the GrabX SDK tended to require high memory and CPU usage. From this, we saw opportunities for further improvements that could:
DoorDash uses deep learning to nail ETA predictions with precision.
It’s a difficult decision deciding whether your company’s mobile app should be a true native application or employ a cross platform approach like React Native or Flutter.
Slack traces performance across mobile and desktop to catch every snag.
Swiggy tunes their restaurant app to perform better for partners.
Gojek tells how they upgraded from basic bid alerts to the slick ‘Courier’ system.
Reddit looks back at untangling old code and going native with their apps.
Mercari tracks mobile app performance live to stay quick and steady.
A quick dive into why app size matters, how it affects users, and tricks to keep it lean.
Swiggy uses Litho to make scrolling smooth and fast in their apps.
DoorDash uses Flink to spot user sessions and send timely notifications.
Gojek’s ‘Courier’ service makes push notifications quicker and more reliable.
Glance scales their Game Centre to handle 100 million daily players.
Swiggy handles media in their apps with finesse and speed.
Instagram tunes DMs to be quick and trustworthy for every user.
Skeelo tunes Node.js concurrency to keep their app humming along.