# Interpret your Compass chart, part 1 Source: https://amplitude.com/docs/analytics/charts/compass/compass-interpret-1 --- On this page - [Before you begin](#before-you-begin) - [How to read your Compass chart](#how-to-read-your-compass-chart) - [Choose a different metric](#choose-a-different-metric) - [View statistical significance](#view-statistical-significance) # Interpret your Compass chart, part 1 Amplitude's **Compass** chart shows how a new user firing an event correlates with that user retaining. Understanding which user events lead to retention is critical to driving sustainable product growth. ## Before you begin Refer to the article about [building a Compass chart](/docs/analytics/charts/compass/compass-aha-moment) before you start to interpret one. ## How to read your Compass chart When you first launch a Compass chart, you might have a specific hypothesis about which events are likely to drive retention. Even if you don't, Compass can help you develop one. In the previous article, you saw how Compass generates a heat map of user events and correlations by default when you select *Any Event*. This is a quick summary of the events most correlated with members of a base cohort converting to a target cohort. It's a good place to start if you don't have much data yet. You can sort the table in ascending or descending correlation for a given day by clicking the day labels across the top. Clicking a specific cell displays a popup with more detailed information about the event/day combination you selected. This summary report is useful for looking at your data from a bird's-eye view, for example, identifying events that should rank at the top but don't. After you choose an event to focus on, Compass replaces the heat map view with a more detailed breakdown. As an example, look at how triggering the event `Social Action: Add Friends` within the first seven days of becoming a new user correlates with second-week retention. The following sections walk through the different components of the reports Compass generates. On the left, you see the **correlation scores** of that event, sorted by the frequency with which your users have triggered it. By default, the report shows you the frequency with the highest correlation. Users who triggered `Social Action: Add Friends` at least once had the highest correlation score, and are most likely to have ended up in the second-week retention cohort. The correlation between triggering `Social Action: Add Friends` and second-week retention is weak. Correlation and causation aren't the same thing. A high correlation score may suggest a causal relationship between two events, but it can also mean that each of those events is highly correlated with another, as-yet-unidentified event. Click any of the buckets to view a detailed breakdown of that event/frequency combination, particularly when looking at smaller numbers of initial days for each user. Amplitude categorizes correlation scores like this: - **Highly Predictive**: correlation >= 0.4. - **Moderately Predictive**: 0.3 <= correlation < 0.4. - **Slightly Predictive**: 0.2 <= correlation < 0.3. - **Not Predictive**: correlation < 0.2. ### Choose a different metric Compass defaults to showing correlation scores. You can select a different metric if it better suits the needs of your analysis. Select the metric you want from the *Correlation* dropdown menu, such as [Positive Predictive Value](/docs/analytics/charts/compass/compass-find-inflection-metrics). ## View statistical significance Compass lets you toggle the 95% confidence interval of the correlation on and off. Click the blue numerical text on the right side of the table to display the interval on the left-side bar chart. [Read on to learn more about how correlation is used in Compass, and how to create a cohort from your results](/docs/analytics/charts/compass/compass-interpret-2). Was this helpful?