# Journeys: Discover what's making your users convert or drop off Source: https://amplitude.com/docs/analytics/charts/legacy-charts/legacy-charts-journeys --- On this page - [Who should use Journeys](#who-should-use-journeys) - [A Journeys use case](#a-journeys-use-case) - [View user conversion paths with Journeys](#view-user-conversion-paths-with-journeys) - [Journeys vs Pathfinder: when to use each](#journeys-vs-pathfinder-when-to-use-each) # Journeys: Discover what's making your users convert or drop off Amplitude is merging this feature into the new Journeys experience. This article remains live as long as legacy Journeys charts remain accessible. [Learn about the new Journeys experience here](/docs/analytics/charts/journeys/journeys-understand-paths). Modern digital experiences are complex, which makes it difficult for teams to get a comprehensive view of what users do in the product. Amplitude's **Journeys** feature helps you understand how users convert—or fail to convert—between key transitions within a 60-day conversion timeframe. With Journeys, you can: - See step-by-step breakdowns of all paths converted and dropped-off users take between two funnel steps in a single chart. - Uncover the paths most likely to accelerate conversion. - Identify what users do instead of converting. - Identify the experiences that lead to conversion fastest, and those that take the longest. - Understand the friction points in your customer experience, and develop a strategy to fix them. ## Who should use Journeys Journeys delivers the most value to Amplitude users who want to understand how conversions happen in their product, and to those who know user friction exists but don't know the cause. ### A Journeys use case A product manager wants to understand the initial activation flow her product's users take. She sets up a funnel analysis in Amplitude with a starting and ending event, then opens Journeys. She finds an unexpected path, so she clicks it to dig deeper. Journeys shows her the average time it takes a user to convert, plus specific paths individual users take. From here, she might develop a hypothesis about user behavior that has implications for the flow's design, which she can take to the product team for discussion and iteration. She might spot friction in the flow, which leads to further questions and new explorations. Or she notices that many users drop off before a critical step in the conversion process, so she saves them into a cohort and shares it with the marketing team for targeted messaging. Journeys surfaces these patterns for you. Follow the insights and keep asking follow-up questions. ## View user conversion paths with Journeys To see the details of users' conversion paths with Journeys, follow these steps: 1. Create a funnel analysis with one starting and one ending event. For the event order, select "in this order." Journeys doesn't support any-order funnels, exact-order funnels, or funnels with properties held constant. 2. In the chart, click the ending event to open the [Microscope](/docs/analytics/microscope). Click *Show User Journeys*. The Journeys chart appears. 3. By default, Amplitude displays user paths that resulted in conversions. To view user paths that result in drop-offs instead, click *Drop off paths*. 4. Adjust your **auto-filter** settings to set the level of granularity you need: - Click the gear icon to open the auto-filter panel. - Use the slider to adjust how aggressively the auto-filter removes unimportant events. The Journeys auto-filter uses the [TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf) heuristic to algorithmically remove noisy events from the analysis. Amplitude sorts events based on how likely they are to appear in user streams; the slider position determines what percentage of the events Amplitude excludes from the analysis. As you drag the slider toward *Signal*, the filter removes more of the obvious events, and only shows those less likely to appear in user timelines. - If the auto-filter isn't right, add specific events to always exclude or always include in the custom overrides boxes. - Click *Hide* to close the auto-filter panel and return to the chart. Check your results as you do this: it's easy to set the auto-filter so strict that it excludes events you're interested in. 5. In the chart, you can now see several distinct event paths bridging the starting and ending events. This is where your analysis begins. If no events appear in your sequence, it means one of two things: the auto-filter or a custom filter override removed the events, or your users performed no more events. To view the details of a specific path, or to save the users who took a particular path as a cohort for later analysis or targeting, click the path. - Remove it from your analysis. - Expand the event by properties. This counts each event with a different property value as a different event, and Amplitude reloads all the paths based on this new set of events. - Only include certain property values in your analysis. ## Journeys vs Pathfinder: when to use each Journeys and Pathfinder have some similarities, but the two features are different. Pathfinder analyses are unbounded (requiring only a starting **or** ending event), can't display drop-offs or explore alternative paths users take, and don't provide detail at the individual user level. Journeys requires **both** a starting and ending event, provides insight into what users do instead of following a specific path, and can drill into detailed streams of individual users. **Use Pathfinder to:** - Measure the top common paths users take in your product. - Compare properties of events in the paths. - Understand the top paths before or after a specific event. **Use Journeys to:** - See how users transition from state A to state B. - Understand your best-performing experiences, and use them to shape your future roadmap. - See which experiences create high-performing customers, and which result in drop-off. - Identify users who had high intent but encountered friction, and retarget them. Was this helpful?