Resource roundups
Best Measuring Success Resources for Product Managers
This is the reading list Builders Camp's Product MBA points members to for measuring success, in its Product Strategy and Roadmapping week: feature-factory diagnostics, product-market fit tests, and developer productivity debates. Every entry below is verified to exist.
Why measuring success matters for product managers
Measuring product success is the discipline of knowing the difference between shipping and mattering, and it is exactly what the Product MBA's tenth and final content week is built to teach. After nine weeks of building, launching, and iterating, students step back to ask how success itself gets defined and proven, not just delivered. The week's own certification quiz opens with the Sean Ellis Test directly: what percentage of users would be very disappointed to lose your product, and why that threshold, not raw satisfaction, is the number that actually predicts product-market fit.
That same instinct runs through John Cutler's feature-factory essay below, cited as required reading in the module: a team that ships constantly but never measures whether any of it moved a real outcome is not actually further ahead than one that shipped less but knew what worked. The module's live session, delivered by Andre Albuquerque, and its six microlessons cover setting KPIs and targets, avoiding common metric-selection mistakes, and partnering with other functions when the numbers get contested, the same skill First Round Review's Superhuman case study below shows applied at a real company.
How do you know if you've actually found product-market fit?
- How Superhuman Built an Engine to Find Product Market Fit, First Round Review. Covers Rahul Vohra's four-step system for turning the Sean Ellis Test into a repeatable quarterly PMF-improvement process.
- The Sean Ellis Test: A Successful Method to Figure Out Product/Market Fit, Pisano Academy. Explains why the test's negatively-framed question, about disappointment rather than satisfaction, produces a more honest signal than a simple satisfaction survey.
- Don't Scale an Unprofitable Business, Toptal. Argues that scaling before your unit economics work is a strategy risk many teams underweight, since fixed costs and customer loyalty rarely improve automatically with scale.
What are the warning signs you're not actually measuring what matters?
- 12 Signs You're Working in a Feature Factory, John Cutler, Medium. The essay that named the pattern: shipping constantly with no measurement of whether any of it mattered, rapid team reshuffling, and success theater around launches.
- How to Break Free of the Feature Factory, John Cutler, YouTube (MTP Engage Hamburg). A talk unpacking why his own feature-factory essay resonated so widely, landing on psychological safety as the actual prerequisite for outcome-driven teams.
- Measuring Developer Productivity? A Response to McKinsey, Gergely Orosz and Kent Beck, The Pragmatic Engineer. Argues a popular framework for measuring engineering output misses outcomes and impact entirely, which risks damaging engineering culture if adopted uncritically.
Which metrics and frameworks should PMs actually track?
- Net Promoter Score, Explained, HubSpot. Covers how to calculate NPS correctly and what a good score looks like by industry.
- What Are Unit Economics in SaaS?, Paddle. Frames the core SaaS success calculation as LTV divided by CAC, and why that ratio matters more than either number alone.
- OKR Leading and Lagging Indicators, Perdoo. Explains why combining a controllable leading indicator with an outcome-based lagging one makes OKRs both measurable and actionable.
- Christina Wodtke on Lenny's Podcast, Spotify. A Stanford OKR instructor and author of Radical Focus covering the most common mistakes teams make writing and scoring their own OKRs.
How Builders Camp teaches measuring success
Measuring Success is the Product MBA's tenth and final content week, delivered live by Andre Albuquerque with six self-paced microlessons on setting KPIs, avoiding common metric mistakes, and partnering across functions to define what success means for a shipped feature. The Product MBA runs 10 weeks total, 30 hours across live lessons and mentorship, capped at 20 seats per cohort, with Edition 4 running September 14 to November 30, 2026. See the Product MBA for the current edition's dates and seats.
Bootcamps referred in this Guide
Frequently asked questions
What is the Sean Ellis Test, and what score counts as product-market fit?
It asks users how they would feel if they could no longer use your product, offering very disappointed, somewhat disappointed, or not disappointed as answers. If more than 40 percent say very disappointed, Sean Ellis's research found that consistently correlates with having found PMF.
What is a feature factory, and how do you know if you're in one?
John Cutler's essay lists signs including no measurement of shipped work's actual impact, rapid team reshuffling between projects, and success theater around shipping with little discussion of outcomes. The core problem is activity substituting for evidence that anything worked.
How did Superhuman actually use the Sean Ellis Test to improve its product?
First Round Review's writeup covers Superhuman's four-step engine: segment users into the 'very disappointed' group, analyze what that group specifically values, split the roadmap 50/50 between doubling down on what they love and fixing blockers, then repeat quarterly with PMF score as the key OKR.
Is Net Promoter Score still a useful metric for measuring product success?
It is one input, not the whole picture. HubSpot's guide covers how to calculate and benchmark it correctly, but pairing it with a leading indicator like activation rate or a lagging one like retention gives a fuller read than NPS alone.
Can you measure developer productivity the way McKinsey proposed?
The Pragmatic Engineer's response, written with Kent Beck, argues McKinsey's framework measures effort and output but misses outcomes and impact, which is half of what determines whether the work was actually worth doing.
What is the difference between a leading and a lagging indicator, and why do both matter?
A leading indicator is something you can act on directly, like calories eaten; a lagging indicator is the result, like weight. Perdoo's piece explains that OKRs work best when you combine both, since a lagging indicator alone tells you too late to change course.
Sources
Andre Albuquerque
CEO of Builders Camp, SuperOperator, and other companies. Building products.
CEO of Builders Camp, SuperOperator, and other companies. Building products.
LinkedInMore guides by Andre AlbuquerqueLast updated 2026-09-16
Researched from Builders Camp's bootcamp, track and masterclass material and the sources listed on this page, drafted with AI, and fact-checked against every source cited.
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