Welcome to the fifth episode of POD!
Today, our guest is Timo Dechau, Product performance analyst, Event Data Model designer, and Content creator about efficient metrics and event data setups.
Timo started 10 years ago in Product Management. His approach to improve Products was always very Data focused. So his first steps in all his roles was to get the Tracking and Analytics in shape and enrich the Data with additional Data sources.
This is how he built the perfect Data setup for making Product Decisions.
In this episode, we cover :
What is a Data Warehouse? Do all Business Intelligence (BI) teams need a Data Warehouse?
How Product Teams can find the synergy to make effective business decisions while having inputs and insights from various teams?
Data Models for Product Data : What this means and why do we need Data Models?
How do we navigate difficult conversations between the camps of Product & Data? How do we alleviate the pain in stakeholder presentations about BI insights?
Why shadowing cross-functional team members can be super beneficial to improving both your own craft (in either camp) and communication between these two camps.
What are User States? How does this tie into Metric Trees?
How is Product Analytics different from Marketing Analytics? Can we borrow knowledge from the latter to guide the former?
Learn how Metric Trees and User States and Product Analytics can help Product Leaders identify where and when to place their bets on certain features, user cohorts and more!
To dive deeper into Timo’s work, please check out his Substack page below.
https://substack.com/@timodechau
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