For an online education provider, traditional monthly reporting was masking a much longer customer journey. By analyzing cohorts and the time between key actions, we found that students could first visit the website nearly a year before starting a course and register as much as four months before the course began. These insights changed how the organization could approach marketing timing, course planning, and demand forecasting.

A Working Planet client thought they had it figured out: a finely tuned predictive model delivering real-time performance insights. But after months of testing, we uncovered gaps in what looked, on paper, like a perfectly sound approach.

Predictive models are powerful tools for making smarter marketing decisions, but as with any model, the details matter. One common consideration is whether to include source as a variable. At first glance, it makes sense since different audiences generate different types of leads. But when predictive values are used not just for reporting, but for network optimization, including source as a variable can introduce risks that undermine campaign performance.

Are first-party data tools and GA4 interchangeable for tracking customer behavior? Short answer: Not even close. While both aim to shed light on how users interact with your site or product, they operate on fundamentally different levels and serve different purposes. Here’s how they break down.