Metrics That Actually Matter at Head of Product Level
The metrics that matter for an individual PM are not the metrics that matter for a Head of Product. Here is how the measurement framework needs to shift — and three metrics that indicate whether a product organization is operating at the level it should be.
Velocity. Story points. Features shipped. These are the metrics of product execution. They measure whether work is being done.
At Head of Product level, these metrics are important but insufficient. They tell you whether the engine is running. They do not tell you whether it is going in the right direction.
The metrics that matter at the product leadership level are different in kind, not just in scope. They measure the quality of the system that produces product decisions, not just the output of that system.
Here are the metrics — and the reasoning behind each — that I believe should sit at the center of a Head of Product’s measurement framework.
Revenue Per Product Manager
Revenue per PM is a blunt metric, but it is one of the most useful for assessing whether a product organization is operating efficiently.
The calculation is simple: total annual recurring revenue (or, for growth-stage companies, total annualized bookings) divided by the number of product managers.
Industry benchmarks vary, but in B2B SaaS, a healthy revenue per PM for a mature company is in the range of $5M–$15M ARR per PM. Early-stage companies operate below this range as they build. Companies operating consistently well below $5M ARR per PM are likely overstaffed in product management relative to their revenue traction, or have a product management function that is not operating as a strategic revenue driver.
Why this metric matters: it forces the question of whether the product organization is generating revenue value commensurate with its size. A product team of ten PMs that manages a $20M ARR business differently than one that manages a $100M ARR business — and the difference should show in product focus, decision quality, and strategic contribution.
This metric should not be used punitively or in isolation. It is most useful as a diagnostic: when revenue per PM is declining over time despite growing ARR, it suggests the product organization is growing faster than its revenue traction justifies. When it is growing, it suggests the team is becoming more efficient — building things that generate more revenue value per person.
Strategic Initiative Throughput
This metric is harder to define precisely but more directly relevant to product leadership quality: how many significant, strategically meaningful product bets does the organization complete, test, and learn from in a given year?
Not features shipped — strategic initiatives. A strategic initiative is a product investment designed to move the product into a new capability tier, a new customer segment, or a new competitive position. It has a clear hypothesis, a defined success metric, and a conclusion: either it worked (and gets expanded) or it did not (and gets killed or redirected).
A healthy product organization at 40–80 engineers should be completing the cycle on three to five significant strategic initiatives per year: forming the hypothesis, building the minimum viable test, measuring the outcome, and reaching a clear decision.
Organizations with lower strategic initiative throughput are typically spending most of their capacity on execution — building features, maintaining existing systems, serving customer requests — without generating the strategic learning that determines what the product becomes in three years.
Tracking this metric requires defining “strategic initiative” clearly enough to count it, which is itself a useful forcing function. If you cannot enumerate the three to five strategic bets the organization tested last year and the conclusions reached, you likely do not have a strategic initiative process — you have a feature factory.
Retention Leverage
Retention leverage measures the product’s contribution to customer retention: specifically, what percentage of customer retention is attributable to product depth — the depth of product adoption by each customer — versus relationship or contract factors.
The proxies:
Feature adoption breadth: How many of the product’s core features does the average customer use? Customers who use five features of an eight-feature product are more retained than customers who use two. Feature adoption breadth is a leading indicator of retention.
Workflow integration depth: How embedded is the product in the customer’s actual work? Products that sit in the center of daily workflow have much lower churn than products that are accessed occasionally or consulted periodically. This is harder to measure but can be approximated by daily active use rate among seat holders.
Stickiness vs. switching cost: Is the customer retained because they find genuine value in the product (stickiness) or because switching is painful (switching cost)? Both retain customers, but they have different trajectories. Switching-cost-driven retention is fragile — it erodes when a competitor reduces switching costs or when customers reach a frustration threshold. Value-driven retention compounds — customers who are retained because they find genuine value tend to expand.
At Head of Product level, retention leverage is the most important long-term metric because it determines the durability of the business model. A product organization that consistently improves retention leverage is building compounding value. One that relies on relationship retention or contract lock-in is building fragility.
The Composite View
These three metrics together paint a picture of product leadership effectiveness:
- Revenue per PM answers: Is the product organization generating business value commensurate with its size?
- Strategic initiative throughput answers: Is the product organization learning fast enough to keep the product competitive?
- Retention leverage answers: Is the product organization building a product that customers genuinely value and cannot easily replace?
No single metric captures everything. Taken together, they describe an organization that is efficient, learning, and building durable product value.
The typical product organization that lacks these metrics does not lack measurement entirely — it has plenty of velocity charts, sprint burndowns, and shipped feature counts. What it lacks is the higher-order measurement that connects product execution to business outcomes and strategic direction.
Building these metrics into the Head of Product’s regular reporting is not just a measurement decision. It is a statement of accountability: this is what we believe our product organization should be responsible for, and this is how we will know whether we are achieving it.