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However, if we built an event funnel in our product analytics, one that examines what users are doing several steps before potentially reaching the chat feature, we might find that the engagement drop-off was actually happening a screen or two earlier, maybe due to a poorly designed series of buttons or UI flow. Create counter metrics.
As data-driven product development continues to balloon in popularity, so does the need for accurate and sophisticated implementation of analytics tracking in software products. And this pattern creates lots of problems —both for the engineering team and the product itself. But what if you could save everyone from this insidious peril?
When engineers implement features, they write code. When engineers add analytics events to new features, they add additional analytics code to their new feature code. This is when they should make changes to the code like implementing analytics because this is when their understanding of the code is at its peak.
So it’s tempting to think the additional add-on of measuring user events in your code (i.e., At the same time, when you review the product analytics, you notice four out of five are using the biggest feature incorrectly. Say, for example, you just launched your app with three features that you believe are going to be a big hit.
That starts with hiring seasoned experts, even if only for review of more junior work. He’s been developing apps for almost as long as the App Store has existed—wearing every hat from full-time engineer to product manager, UX designer, founder, content creator, and technicalcofounder. Prioritize UX.
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