In this session, we answer these key question:

• How can you map the user journey to pinpoint conversion and drop-off points?
• Which funnels should you focus on to improve user activation?
• Rocking your world when you start with a Journeys chart (and not Funnel!) 
• What's the base line conversion for our core funnel(s)?
• How to identify and resolve friction points that hinder user conversions?
• How to measure "time to convert" to optimize onboarding and activation strategies?

Get the full recording here: 

Kill your assumptions. Start with Journeys to discover what user journeys look like in the wild.

• Instead of a pre-determined idea of your users’ journeys, start with choosing a key starting point to see which steps users actually take to get from point A to point B. 

• This helps in understanding what users actually do, rather than assuming a specific funnel.
• And use the ‘historical count=1’ filter for signup events to focus on new user behavior.
• Also try working backwards. View which (many winding) steps users took to get to a key product moment like the a purchase moment.

Historical Count Feature

• The 'historical count' feature in Amplitude tracks how many times a user has performed an action. (e.g. historical count = 1 shows the first time a user performed an action, historical count = 3 shows the third time a user performed an action, etc).

• This feature is useful for analyzing user behavior patterns, such as how many times a user engages with content before making a purchase.
• One interesting use case is building a cohort of users who used a feature x# times and are nearing a paywall. Could be an interesting cohort to dig into in monetization plays.

Building Funnels

• Build the simplest path from your starting to ending point, starting with key actions like signup, content engagement, and purchase.

• Rather than building a funnel that follows the UX, start by keeping funnels simple to zoom in on key milestones in the user journey.
• Quick demo of how to analyze funnel conversion rates and drop-offs
• How to use time to convert in your funnel analysis.
• Comparing different user segments within a funnel, including both successful and unsuccessful conversion paths. And going from the cohort of users that didn’t convert and viewing which journeys they took instead.

• The use of conversion drivers to identify actions correlated with successful funnel completion is demonstrated.

Retention Analysis

• How to compare retention rates for users who engage with specific features versus those who don't.

• Connecting different new user cohorts, their activation activity, and how that correlates with long-term retention is discussed.

Compass Feature Introduction

• Using Compass feature in Amplitude to explore correlations between user actions and desired outcomes like retention.

• An explanation of how Compass differs from conversion drivers is provided, offering a more open-ended exploration of user behavior patterns.

Cross-Project Data Analysis

• Is it possible to have data from different Amplitude projects at the in the funnel chart or mobile app is tracked on a different project?