From the course: Becoming an AI-First Product Leader
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Quality data collection
From the course: Becoming an AI-First Product Leader
Quality data collection
- Let's talk data. Specifically, why as a product leader, it's a critical component of your job. In AI, collecting quality data is potentially the biggest mover in building an amazing algorithm and a great product. Let's start with the primary types of data available to us. First, user activity data. This is data you collected by capturing how users interact with your product. For example, what they clicked on, what did they not click on. Note that negative signals can be as powerful as positive ones. Second, user feedback data. This is data you collected explicitly from users who provided feedback about your product. I'm not referring to net promoter score, or customer satisfaction surveys, I'm talking about in product, in context prompts, to get direct explicit feedback from your users. The third bucket is offline or third party data. This is data you collected outside of the scope of your own product. And it…
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