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The good news is that many technical quirks tend to follow certain patterns that can be easily spotted—even by non-engineers. Here are four technical hiccups associated with corrupt event tracking data, how to spot them, and what to do about them. As they say—garbage in, garbage out. Event stuttering. Disjoint event duplicates.
UX design, branding, feature-set, nuanced differences in user perspectives, and a million other variables can impact (with varying levels of influence) whether our products get used or ignored. Never before has there been better access to rich and nuanced data about the ways your users engage with your products. Pulling it together.
Analytics should be tested alongside features. In order to effectively test whether a feature has been implemented correctly, a QA engineer needs to understand the feature inside and out. You work like heck to get everything implemented and tested on time and get a brief moment of celebration…then surprise!
So it’s tempting to think the additional add-on of measuring user events in your code (i.e., implementing product analytics) is something that can wait until your team is bigger, until you have more users, or until you have more money. You know where users clicked and didn’t click, when they clicked, and in what order.
The point is that some of these might be catchable by non-technical team members whose job it is to analyze the data, but a lot of cases could only ever be noticed by someone who understands how the implementation actually works on a technical level: an engineer like yourself. Keep the product folks technically up-to-date.
Rather than a UITableViewController with accompanying storyboard and custom UITableViewCell subclasses, all we need now is a binding to a list of tasks and 10-ish lines of actual code: struct TaskListView: View {. Use custom event initializers to reduce footprint. Use custom view modifiers for more logical grouping. onDrag {. }.onDrop
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