Turn Events into Answers

About this webinar

Your event data is immaculate. Marketing touchpoints, product clicks, support interactions—all flowing into a perfect clickstream, ready to analyze.

And then what?

You can query it. You can count events. You can build a funnel that shows the happy path. But when someone asks "why did this account churn?" or "what's the actual pattern here?" you're stuck between two bad options: overwhelming spaghetti diagrams that show every possible path, or oversimplified funnels that miss the real story.

The fundamental problem is that event data lives in two worlds at once. You need to understand the individual journey (what did this customer actually do?) while also seeing the aggregate pattern (what do successful customers tend to do?). And most analysis tools force you to pick one or explain one to get to the other.

In this short, focused webinar, we'll look at how to turn event streams into actual insight—and how to make that insight something stakeholders can explore themselves, not just something you have to explain over and over. This is practical technique you can use immediately, not theory.

We'll cover:

1. The individual-to-aggregate gap — why it's hard to learn meaningfully from a single user journey among thousands, and how to draw patterns that help you understand specific actions
2. Beyond funnels and spaghetti — what actually useful user journey visualization looks like, and how to avoid the extremes
3. Building explorable explanations — using Count's canvas and flexible visualization system to create journey analysis that stakeholders can navigate and question themselves, not just nod along to

We'll work with real event data live, building visualizations that connect the dots (literally—we'll be combining marks like lines, dots, bars, and labels) between individual behavior and broader patterns.

Who should tune in?

• Product analysts and growth teams drowning in event data but struggling to extract insight from it. You'll leave ready to try these approaches on your data this week.
• Marketing and ABM teams who have journey data but can't quite turn it into something decision-makers can act on. You'll leave with specific techniques to apply immediately.
• Data teams supporting product, marketing, and CS stakeholders who are tired of rebuilding the same analysis every time someone asks a follow-up question. You'll leave with practical ways to make your journey analysis self-serve and collaborative.
• CS and account teams trying to understand account health through behavior. You'll leave knowing how to actually use that event data you keep hearing about—starting now.