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Product Management

Product Analytics

185 people are learning this skill right now!
Our learning guide for product Analytics covers what metrics to track (including how to pick a north star or core action metric), how to set up, structure, & refine event Analytics, the pitfalls of working with data, and product Analytics case studies.
  1. Learn Product Analytics with the Practica AI Coach

    The Practica AI Coach helps you improve in Product Analytics by using your current work challenges as opportunities to improve. The AI Coach will ask you questions, instruct you on concepts and tactics, and give you feedback as you make progress.
  2. Intro to Product Analytics

    Product Analytics is the process of collecting and analyzing data to understand how users interact with a product, and how to improve it.
  3. Common Product Analytics Challenges

    These are common challenges people face when gaining expertise in product analytics. Tackling these challenges head-on can help you learn this skill quicker.

    I'm a product manager at a startup and have been asked to work on our product analytics. This is a new area for me, so I'm not sure what are the right metrics to track. Can you give me some ideas of the most impactful metrics to track and how I should get started tracking them?
    I'm a senior PM at a mid-sized tech company, and I'm responsible for product analytics. I'm encountering some problems with data quality. The data I receive is often incomplete or inconsistent, making it difficult to draw meaningful conclusions and insights that we can pass to the product team. What steps should I take with our team to improve the situation?
    Work on your own challenge with the Practica AI Coach
  4. What Metrics to Track

    Metrics to track depend on the product's goals and can include user acquisition, retention, engagement, and revenue.
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  5. How to Set Up Product Analytics

    Setting up product Analytics involves identifying the right tools, defining events to track, and integrating with the product.
  6. Pitfalls of Working With Data

    Pitfalls of working with data include misinterpreting results, biased data collection, and privacy concerns.
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  7. Product Analytics Case Studies

    Product Analytics case studies highlight how companies have used data to drive product decisions.