Where does product analytics fit in the realm of analytics tools on the market? What makes product analytics different from marketing analytics? How are product teams using analytics in their day-to-day work?
These are just some of the questions our Director of Product, Sandhya Hegde answered in a recent interview with Ryan Koonce, the CEO of Mammoth Growth, a growth agency that works with companies like DoorDash, Tile and Rinse.
I am always a little disappointed by S1 filings. As a VC investor, ex-engineer and product leader, I am trained to look for the secret sauce in every business – the leading indicators of future outcomes that forecast what success could look like. However, most S1 filings just present the standard wall street analyst metrics like year-over-year growth, gross margin and cost of revenue.
“Data validation is fun!” – No one ever
Data validation. Two incredibly important words, yet one of the most painful parts of any analytics instrumentation. Whether you’re getting started with product analytics for the first time, or releasing a new feature and making updates to your current implementation, ensuring that the data you collect is accurate can be a nightmare for large organizations and small startups alike.
An introduction to product strategy with examples of north star metrics across industries
The product north star is easily the most powerful and misunderstood product strategy framework in use today. More product teams are dealing with the consequences of not defining it at all or defining it the wrong way and leading their team down an unintended path.
Our March 2018 product update includes new features to:
- Make Amplitude easier to learn
- Help product teams measure the impact of feature releases
- Support instrumentation and data governance
Only two years old, letgo is already the biggest and fastest growing app to buy and sell locally in the US and other countries with over 75 million downloads, 200 million listings and 3 billion messages sent in its first two years. Its team moves quickly, so they needed a tool that could keep up with their rigorous A/B testing and analysis.