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Metric Trees

Mixpanel Metric Tree is a “live” logical decision-making framework used to represent relationships between metrics and show the flow between inputs and outputs. The “live” metrics make it possible to understand the quantitative impact and trace the inputs driving it.
Metric Tree is a paid add-on currently only offered to those on the Enterprise Plan.

Overview

It is one space that simultaneously depicts both quantitative and qualitative data along with additional context, making it possible to discuss insights as a team across functions and make data-driven decisions together.

Use Cases

  • Data-driven decision: Clearly articulate what’s working vs not by looking at how your input metrics and initiatives are impacting your top business outcomes
  • Align with your team: Use this as the codified strategy map from Execs to ICs and across teams on growth strategy & metrics
  • Collaborate on strategy: Leverage this during weekly rituals to identify which areas require more focus, and add those insights in the tree for others to reference
  • Evolve your metric tree: With every planning cycle, update the initiatives and input metrics as goals and focus outcomes change
  • Guide data tracking: Use this as a plan to ensure you have the right data tracked and modeled correctly

Quick Start

1

Create Your Metric Tree Outline

Think through your strategy and the various hypotheses without confusing it with the data available today. Your strategy is more long-term.
  • Add empty state metric cards to the tree by choosing Metric from the toolbar
  • Name these metric cards and link the connections
  • Add strategy cards to show the initiatives in place
2

Connect Metrics with Data

Click on “connect metric” and connect the metric card to the metric with data. This is a regular Mixpanel query panel. You can choose to bring in saved metrics or create a metric.
We highly recommend saving metrics in the metric tree, especially those on the higher levels, so others on the project use only these standardized, verified metrics.
3

Add Context to Your Metrics

Make your tree more actionable for yourself and the team by adding context:
  • Pin content with interesting deep dive reports
  • Examine correlation and find interesting insights to add to the logbook
  • Add owners to keep people accountable for metrics
4

Share Your Metric Tree

Metric Trees have similar permissions to Mixpanel boards. You can share the tree with anyone in the project:
  • Editors get access to edit the definition of metrics, add new metrics, add context, etc.
  • Viewers get access to open and see the underlying formula definitions, and read the context and notes
When you hit undo, you undo only your last action. Also, the last edit on a metric persists for all.

Customize Each Metric

Time Comparisons

To ensure your metric is showing the most apt time comparisons, you can customize at a metric level which time comparisons you want to show in the metric tree view. For example, if you wanted a QoQ view instead of YoY, you would select:
  • Time range: Last 3M
  • Compare to: Previous quarter
  • Interval: week (determines the number of data points displayed in the metric line chart)
Key Points:
  • You can change the default time comparison settings for your tree (all metrics) by clicking on Apply to All Metrics
  • You can add up to 3 time ranges per metric card
  • On the metric card view, when you click on MoM, it shows the absolute value of the metric for the last 30 Days
  • If you switch the default “display” on the metric card, all the other cards that have that time range will also switch

Add Owner

For any eligible metric, you can click on the owner icon and assign an owner.
You can assign an owner only to a saved metric.

Pin Contextual Reports

Click on a metric. When the query panel opens, navigate to the Context tab. Within the Context tab, pin reports and boards in the ‘Pinned’ tab.

Add Insights to the Logbook

Click on a metric. When the query panel opens, navigate to the Context tab. Within the Context tab, add entries into the ‘Logbook’ tab.

Understanding Correlation

Access the 3-dot overflow menu on the top right of the metric tree. Click on Show/Hide > Show Correlation. Correlation numbers will show up across all the edges (the connection between two metric cards). Mixpanel shows Pearson Correlation Coefficient. It measures the strength and direction of a linear relationship between two time-series data sets. It produces a value between -1 and 1. For two metrics, A and B, each return time-series data, we compute Pearson correlation using the following formula: r=(AiA)(BiB)(AiA)2(BiB)2r = \frac{\sum{(A_i - \overline{A})(B_i - \overline{B})}}{\sqrt{\sum{(A_i - \overline{A})^2} \sum{(B_i - \overline{B})^2}}} Where:
  • AiA_i and BiB_i are individual values in the time-series data of metrics A and B
  • A\overline{A} and B\overline{B} are the mean (average) values of metrics A and B over the observed time period
  • rr is the Pearson correlation coefficient
The resulting r-value determines the correlation score displayed on the edge.

Interpreting the Correlation Score

  • (0.6 to 1.0) Strong Positive Correlation: The two metrics tend to move in the same direction strongly. As one metric increases, the other increases.
  • (0.3 to 0.6) Moderate Positive Correlation: Some relationship exists
  • (0.0 to 0.3) Weak Positive Correlation: Some relationship exists, but it is not strong
  • (0.0) No Correlation: Changes in one metric do not seem to have changes on the other
  • (-0.3 to 0.0) Weak Negative Correlation: Some inverse relationship exists, but it is not strong
  • (-0.6 to -0.3) Moderate Negative Correlation: Some inverse relationship exists
  • (-1.0 to -0.6) Strong Negative Correlation: The two metrics strongly move in opposite directions

Correlation Calculation Details

To compute the Pearson correlation, we use:
  • Time-series data from both metrics
  • Matching timestamps: Data points are aligned by timestamp to ensure proper comparison
  • A configurable time window: The correlation is typically calculated over a specified time range (e.g., the last 30 days)
Important Notes:
  1. If 2 time-series data have different lengths, correlations are calculated based on the overlapping lengths between the 2
  2. All correlations are run on a daily granularity, since event data is available on a daily basis
Limitations of Correlation:
  • Correlation does not imply causation: A high correlation does not necessarily mean that one metric influences the other
  • Non-linear relationships: Pearson correlation captures only linear relationships. If the metrics are related in a non-linear way, this score might not reflect the true relationship
  • Data Quality Matters: Missing or misaligned data points can affect the accuracy of the correlation score

Frequently Asked Questions

What does the “As Of” control on the top left of the metric tree do? As of determines the end date reference point for the metric tree. For example, if you want to look at how the metric tree looked at the end of Q1 (March 2025), you could set “As of 31 March 2025”. All the metrics in the metric tree which are based on last 30 Days, or the last 3 months etc, will look at measuring the value as of 31 March 2025. What does Filtering a tree do? Filtering a tree is similar to filtering a board. It filters every metric in the metric tree. If you’re looking to filter only a specific metric, please use inline filters. How do I see the metric trend chart (metric time series)? Access the 3-dot overflow menu on the top right of the metric tree. Click on Show/Hide > Show Metric Chart. If you want to look at a longer time series chart for a particular metric, go to the specific metric card, click on the overflow menu, and choose View Chart. I want to move trees across projects. How do I do that? You can copy a tree and paste a tree in a new project. To select the whole tree, use the select tool in the toolbar below, in the middle of the screen. Then Copy (Cmd + C), and Paste (Cmd + V) in the new project. How many trees do you suggest we create? Create minimal trees so there is a complete map of the strategy in one place vs across disparate trees. Ideally, start with one tree per company, and depending on the size, maybe create separate trees for each function or business line if required. Does the top of a metric tree have to be revenue-related? No, it doesn’t have to. We generally ask people to start a tree at L2 or L3 level where there is more functional ownership, for example, marketing can own Volume of Sign-Ups or Product can own WAU (Weekly Active Users).

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