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.
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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
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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
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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
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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.
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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.
- 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?
