What Is a KPI Tree?
A KPI tree breaks your north star metric into the driver metrics that influence it. Learn how to build one and use it to focus your team's effort.
Key Takeaways
- A KPI tree maps the relationship between your north star metric and all the driver metrics that influence it
- It shows every team how their work connects to the overall business goal
- The tree reveals which metrics are levers (you can influence them) and which are lag indicators (they follow from others)
- Build the tree with your team, not for your team — the process is as valuable as the output
What a KPI tree is
A KPI tree (also called a metric tree or driver tree) is a visual representation of how your top-level business goal decomposes into the contributing metrics that drive it. At the top sits your north star metric — the single number that best captures the value your business creates. Below it are the second-level metrics that directly drive the north star. Below those are the third-level operational metrics that teams can directly influence through their daily work. The tree shows the mathematical and causal relationships between every metric in the business.
Building the tree
Start at the top with your north star metric. Ask: what are the two or three most direct mathematical drivers of this metric? For example, if your north star is monthly revenue, the direct drivers are new customer revenue and existing customer revenue. For each of those, ask the same question. New customer revenue is driven by number of new customers and average first purchase value. Number of new customers is driven by website visitors and conversion rate. Keep decomposing until you reach metrics that individual teams or people can directly influence through their daily actions.
An example tree
For an eCommerce business: North star: Monthly gross profit. Level 2: Revenue (Volume x Average Order Value) and Gross Margin %. Level 3: Revenue driven by Sessions x Conversion Rate x AOV. Sessions driven by Paid traffic (Budget x ROAS) and Organic traffic (SEO rank x CTR). This tree shows that the performance marketing team influences gross profit through Sessions and ROAS, the product team through Conversion Rate and AOV, and the buying team through Gross Margin %. Everyone can see how their work connects to the top.
Levers vs lag indicators
A key insight from building a KPI tree is the distinction between leading metrics (things you can change now that will affect future outcomes) and lagging metrics (outcomes that follow from other things). Conversion rate is a leading indicator that your team can influence through UX improvements, pricing experiments, and product photography. Revenue is a lagging indicator that follows from conversion rate, traffic, and AOV. Teams should be managed against leading metrics they can influence, not lagging metrics they can only observe.
Using the tree for focus
Once built, a KPI tree tells you where to focus effort for maximum impact. If your north star is under-performing, the tree shows you which branch of the tree is most responsible. If conversion rate is the problem, the relevant teams investigate and experiment on the metrics feeding into conversion rate. If retention is the problem, a different set of teams and metrics comes into focus. Without the tree, organisations spray effort across many initiatives simultaneously. With the tree, effort concentrates where it matters most.