Product
Use data to build a better product.
-
50:55Watch VideoModern Product Data Workflows 1: Products for Product People: Best Practices in Analytics
Who builds products for the product people? As a product manager, you know how helpful custom tailored data solutions can be to doing your job well. But proper data analytics solutions take work to de
-
1:07:10Watch VideoModern Product Data Workflows 4: How King Crushes New Product Development using Data-Driven Insights
Product Managers looking to leverage data to make informed product design decisions can learn a lot from renowned gaming company King, maker of Candy Crush and many other games - even if their product
-
57:23Watch VideoModern Product Data Workflows 2: Iterate Your Way to a Top Product Experience
Mark43 is on a mission to bring public safety data management into the 21st century. To fix traditionally paper-heavy and error-prone processes, they needed a secure and easy-to-use product experience
-
1:03:07Watch VideoModern Product Data Workflows 6: Harness Your Product Data: Better Understanding User Behavior Across Channels and Devices
As a product leader, you are tasked with collecting and synthesizing your customer’s interactions with your product.The great news is that there are many tools used across your company which collect u
-
58:58Watch VideoModern Product Data Workflows 5: How Product Managers can Learn to Love Reporting
For a long time, Product Managers have found it challenging to design interfaces inside their products that users could use for reporting. It seems like PMs and engineers have grown to hate embedded r
-
20:14Watch VideoJOIN 2017: Customer Retention
Whether your product focuses on gaming apps or an ecommerce solution, customers matter. Apply retention analysis to provide comprehensive data around customer retention and factors that affect retenti
-
Read FlipbookLooker for Product Analytics
-
View PresentationData Stack Considerations: Build vs. Buy at Tout
In this webinar we see why and how Tout – a fast-growing video platform – made the jump to Looker and Treasure Data, and solved their data stack issues. Slides cover: -The pitfalls of in-house solut
-
Loading More...
