How to build a culture of data-driven decision making across your entire organization.
Design a modern go-to-market stack with integrated analytics workflows.
How to build workflows that automatically move users from segments to targeted campaigns.
Learn how to build automated workflows that collect, analyze, and act on product feedback using analytics.
Build automated revenue reporting workflows that pull data from analytics and billing systems and deliver formatted reports to stakeholders on schedule.
What's covered:
The Hidden Cost of Manual Revenue Reporting
Designing a Report Automation Workflow
Pulling Data From Analytics and Billing Systems
Formatting Reports Automatically
Scheduling Delivery: Email, Slack, and Dashboards
Executive vs. Operational Reports
Handling Ad-Hoc Requests Without Breaking Your Flow
Measuring the Time You Get Back
Key Takeaways
A complete A/B testing workflow that uses behavioral analytics to form hypotheses, segment audiences, measure impact beyond clicks, and feed learnings back into the next test.
What's covered:
Why Most A/B Tests Fail
Using Analytics to Form Hypotheses
Designing Tests with Behavioral Segmentation
Running Tests with Statistical Rigor
Measuring Beyond Conversion Rate
The Learning Loop: Test, Learn, Test
Building an Experimentation Culture
Tools and Integration
Build automated post-purchase workflows that use behavioral data to time review requests, cross-sells, replenishment reminders, and loyalty program enrollments.
What's covered:
The Post-Purchase Opportunity
Mapping the Post-Purchase Journey with Analytics
Timing Review Requests with Analytics
Cross-Sell and Upsell Based on Purchase Behavior
Replenishment Reminders
Loyalty Program Enrollment Triggers
Win-Back Sequences for Lapsed Buyers
Measuring Post-Purchase Workflow ROI
How to set up AI-powered anomaly detection workflows that monitor behavioral analytics metrics and automatically alert, diagnose, and respond to sudden changes.
What's covered:
Why Manual Monitoring Fails
Types of Anomalies in Analytics Data
Statistical Methods vs. Machine Learning
Building an Anomaly Detection Pipeline
Automated Diagnosis: What Changed and Why
Alert Routing and Escalation
Auto-Remediation for Known Issues
Measuring Detection Effectiveness