DXO Classroom Trainings
Engaging hands-on training workshops hosted by Optimizely's expert training team


Strategic Track

Strategic Track Day 1 - Web Strategy Experimentation Foundations

Learning Objectives:


1. How to Build an Experiment in Optimizely X Web

  • Defining experiment components: Pages, Events, Audiences
  • Activation Modes and URL Targeting for Pages
  • Click, Pageview, and Custom Events
  • Building experiments from components
  • Using metrics builder
  • Setting traffic allocation
  • Creating variations using Visual and Code Editors
  • All Visual Editor functionality including mobile view, interactive mode, and redirect tests
  • Basic experiment QA using the Previewer

2. Goals and Metrics for Web Experimentation

  • How to connect revenue to experimentation
  • How to define primary, secondary, and monitoring metrics

3. Experiment Ideation

  • How to use direct and indirect data to develop experiment ideas
  • How to define strong problem statements
  • Crafting hypotheses using the Problem > Solution > Result framework
  • What makes a great hypothesis that’s designed to yield valuable insights

4. Stats Engine & Optimizely Results

  • What is statistical significance and how it is used in experimentation
  • How Stats Engine is different from other statistical models
  • How to use Stats Accelerator/Multi-armed bandits to get results more quickly
  • How to read the Optimizely results page, including segmentation and graphs
  • How to interpret key metrics to use in decision-making including Visitors Remaining and the Confidence Interval
  • How to take action on winning, losing, and inconclusive results

Strategic Track Day 2 - Managing Your Experimentation Program

Learning Objectives:


1. Experiment Prioritization, Roadmapping, and Optimizely Program Management

  • Documenting and collaborating on hypotheses in Optimizely Program Management or another roadmapping tool
  • Calculating sample sizes and estimate how long to run an experiment
  • Prioritizing ideas with a defined framework
  • Viewing reporting in Program Management to measure your team
  • Organizing and running experiment review meetings
  • Managing a roadmap as your experimentation program grows

2. Experiment Design

  • How to build out your hypotheses using a Business Requirements Document
  • Learn which details to document to prepare an experiment for development
  • Identify Page targeting and Audiences for a hypothesis
  • Identify primary and secondary metrics to measure impact of an experiment
  • When to use MVT and funnel tests

3. Team Structures and Governance Models

  • Pillars of success for experimentation programs
  • Common organization models for experimentation programs
  • How to identify which model is best for your organization
  • Common tools used by experimentation programs

Strategic Track Day 3 - Full Stack Strategy for Product Managers and Strategists

Learning Objectives:


1. Goals and Metrics for Full Stack Experimentation

  • Aligning experimentation goals with product and business goals
  • Connecting revenue to experimentation
  • Primary, secondary, and monitoring metrics
  • Setting North Star metrics for product teams

2. Full Stack Experiment Ideation

  • Using direct and indirect data to develop experiment ideas
  • Defining problem statements
  • Crafting hypotheses using the Problem > Solution > Result framework

3. Full Stack + Feature Management Strategy

  • Incorporating experimentation into the product development process
  • When to use experiments and features
  • How to strategically roll out features
  • Experimenting within Agile

4. Stats Engine & Optimizely Results

  • What is statistical significance and how it is used
  • How Stats Engine is different from other statistical models
  • Stats Accelerator
  • Reading the Optimizely results page
  • Taking action on winning, losing, and inconclusive results


Technical Track

Technical Track Day 1 - Full Stack Technical Training

Learning Objectives:


  • Optimizely X Web and Full Stack Compared
  • Implementing Full Stack SDK’s
  • How to make Full Stack architectural decisions
  • Implementing in mobile apps and server-side
  • Building Full Stack experiments
  • Targeting with Audiences
  • Tracking Events/Metrics
  • Controlling traffic
  • Using Full Stack activate calls
  • Using the REST API
  • Feature Management best practices for technical users

Technical Track Day 2 - Web Technical Training Foundations

Learning Objectives:


1. Technical Set-Up of Optimizely X Web

  • Account structure
  • Setting up projects
  • Project and account settings
  • Setting up Program Management teams and touchpoints
  • Using standard analytics / audience integrations

2. Building Experiments in Optimizely X Web for Developers

  • Optimizely's order of executions
  • Running code in Optimizely
  • Cookies and local storage
  • Advanced QA using test cookies, and the developer console
  • Building extensions
  • SPA concepts
  • Event API
  • REST API
  • JavaScript API
  • Extensions

Technical Track Day 3 - Web Enterprise Advanced Technical Training

Learning Objectives:


1. Building Personalization Campaigns for Developers

  • Defining campaign components (Pages, Events)
  • Implementing Tags
  • Creating behavioral Audiences
  • Leveraging 3rd party analytics integrations
  • Building campaigns with those components
  • Creating variations using Visual and Code Editors
  • Basic campaign QA using the Previewer

2. Advanced Features of Optimizely X Web for Enterprise Customers

  • Advanced Tagging Strategy for Personalization
  • Uploaded Audiences
  • Dynamic Customer Profiles
  • Stats accelerator
  • Custom snippets / Cross-Project Events
  • PCI Compliant Snippet
  • Custom TTL for datafile and snippet


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