Blocks Basics
Outline
Welcome
In this module, you'll learn how to use Blocks in Optimizely Analytics to create reusable, logic-driven building components that enhance report consistency and efficiency. You’ll explore the different types of blocks, how they work within datasets, and how to manage and reuse them across your analytics workspace.
After completing this lesson, you should be able to:
Define what a block is in Optimizely Analytics
Understand the benefits of using blocks
Use Block Editor to configure blocks
Identify and create different types of blocks
Apply blocks to datasets and analysis
What is a block?
Blocks in Optimizely Analytics are reusable logic components that simplify complex calculations, reduce repetition, and ensure consistency across your datasets, reports, and dashboards. Think of them as modular "building blocks" oflogic that can be defined once and reused throughout your workspace—helping you accelerate analysis and maintain alignment across the workspace.
What is the purpose of blocks?
Blocks allow you to:
Reuse logic across multiple datasets and visualizations
Reduce the need for repetitive formulas
Ensure consistency across your analytics workflows
Save time on repetitive tasks and reduce errors
For more a detailed breakdown of blocks and a complete guide to all types of block in the library, you can refer to the Blocks documentation.
What is Block Editor?
Block editor is a visual interface that provides a set of building blocks that you can combine to perform complex data computations and create dynamic properties.
The block editor is where you define how your data is processed and transformed. By linking different blocks together, you can create sophisticated calculations, define derived columns, build custom metrics, or specify inline cohorts for your analyses.
Watch the interactive demo for a step-by-step guide on using on block editor: https://optimizely.navattic.com/9plo0ve5
