## Product Analytics Analytics is, simply put, the study of data. **Product Analytics** - which is the activity of creating metrics to understand **how much value a product delivers to its users**. When we have good measurements in place, we can see where our product works well, and where it doesn’t. We use this information to inform **_how_** and **_where_** we should invest our time and resources to improve the products we make. We don’t want to build features in our product that no one will use, and in order to make sure that doesn’t happen, we need to look at the data! #### Prerequisites: - Manipulating CSV files and spreadsheets - Building dashboards - Common counting math (uniques, averages, median, percentiles) ## Getting Started: Setting up Mixpanel for Learning **Note:** Just like with a Google sheet or Excel file, _you_ are the one who decides which object and event data to send to Mixpanel as part of your **implementation spec**. Mixpanel does not automatically track events (also known as implicit event tracking), and instead works with customers to manually define them based on the goals and metrics outlined in their tracking plan. As with most things in life, some upfront planning here will pay dividends in the long run! ![[PMing_Analytics_Getting Started.png]] **Step 1:** Setting Up Mixpanel **Step 2:** Loading data into Mixpanel (requires one time configuration process) #### To Learn: - Learn about the differences between object data and event data - Learn to ask questions from your data and get answers quickly - Practice asking good questions from your data - Choose the right data visualization for any metric - Merge different metrics together into an actionable dashboard #### What to expect? - A strong understanding of the advantages/limitations of event data & object data - A customized dataset loaded into Mixpanel - A framework for phrasing a question about data - A meaningful dashboard of behaviours ## Behavioural Metrics - Behavioural data is event data and object data joined together - Behavioural metrics are critical to product analytics; when we want to understand the “health” of our business, we need to examine end-user behaviours. - Metrics are only impactful if other people can understand them; analysis (by itself) is not enough—we need to build dashboards and reports that are intelligible to others.