Stage 04
In this section:- Introduction to Expert product analytics maturity
- Common markers of Expert stage
- Example of Expert product analytics maturity
- How to move on from Expert
Introduction
In the final stage of product analytics maturity, the entire product development team has access to a full set of accurate data and uses it in every part of product development. The company has unified goals — and everyone is in lock step trying to move the needle on them. The available metrics and analysis aren’t just occasionally consulted, but consistently used, sought out, and considered. Every team member knows how to use the tool and does so regularly. In this stage, you go from a gym membership to also hiring a personal trainer to teach you new techniques and exercises you’ve never tried. You’ve even challenged yourself by signing up and training for your first half marathon. No product development decision is made without the use of product analytics.
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Common markers of Expert stage
At this stage, data can come from a multitude of sources, from cloud imports to customer data platforms. Your product analytics tool is part of your stack, not outside of it. At its core, building out robust product analytics capabilities is about more than engagement and growth. Because expert product analytics maturity allows in-depth time-series and cohort analysis, teams can start to use the insights to align their product roadmaps with customer priorities, experiment with new features, and more.Example of Expert product analytics maturity
Questions you can answer
Consider the questions that can be answered in the Expert stage:- What’s my product’s equivalent of Facebook’s “7 friends in 10 days”?
- How do various combinations of user behaviors and user attributes affect engagement and retention?
- How do marketing launches cause changes in specific user behaviors or my primary metrics?
- How quickly do users reach my activation metric? What actions are likely to convert activated users to power users?
- How do all my A/B tests affect key metrics over time, and which of them are worth continuing?
- How many times do users repeat a given step in a funnel before moving on to the next step, and how does that affect conversion rates?