Product glossary
The language of modern product teams.
Clear, citable definitions of the concepts, metrics and methodologies that run product orgs — written by the team building the product operating system. Filter by type; each term links to a full explainer.
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Connected vs Consolidated Product Stack
A connected product stack keeps specialist tools in place and joins their data on a shared spine; consolidation replaces them — connection scales better because it follows the work rather than forcing teams to abandon the depth they depend on.
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Customer 360 (Account 360)
A Customer 360 is only genuine when revenue, usage, support, and in-progress work are joined at the data level — not when they are displayed in separate tabs that happen to share a customer name.
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Product Operating System
A product operating system turns a product team's fragmented tool stack into a single joined record — so customer, revenue, feedback, and work data all live in one place and inform each other in real time.
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Product Spine
A product spine eliminates the context loss that comes from siloed tools by joining customers, revenue, feedback, and product work into a single shared data layer that every team workflow can read from in real time.
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Product-Led Growth (PLG)
Product-led growth lets the product itself acquire, activate, and expand users through self-serve onboarding — it scales by improving the product experience rather than by hiring more sales reps, and it fits products that deliver value to a single user fast.
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Product-Market Fit
Product-market fit is when a defined segment retains, refers, and pulls harder than you push — and you measure it with retention curves and the Sean Ellis 40% test, not vanity sign-ups.
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Single Source of Truth for Product
A product single source of truth is not about using fewer tools — it is about ensuring customer, revenue, feedback, and work records are joined in one authoritative layer so every decision reads from the same data.
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Dual-Track Agile
Dual-track agile is two parallel tracks — discovery to validate what to build, delivery to build it well — owned by one team feeding one backlog, not two separate teams handing work over a wall.
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ICE Scoring
ICE Scoring gives product teams a fast, consistent way to rank initiatives by multiplying Impact, Confidence, and Ease — surfacing high-value, low-risk work without heavyweight estimation.
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Jobs To Be Done (JTBD)
Jobs To Be Done shifts the unit of analysis from who the customer is to the progress they are trying to make, so teams build for real situations of need rather than idealized personas or feature lists.
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OKRs (Objectives and Key Results)
OKRs align teams by pairing one ambitious Objective with measurable Key Results — but they only work when Key Results track outcomes, not outputs, and grading stays decoupled from performance reviews.
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Opportunity Solution Tree
An opportunity solution tree turns a desired outcome into a branching map of customer opportunities, solutions, and experiments, so every build decision traces back to a real need and a measurable goal.
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Revenue-Weighted Prioritization
Revenue-Weighted Prioritization replaces subjective impact scores with real ARR figures tied to requesting accounts, so product teams build what moves the business forward — not just what gets the most votes.
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RICE Scoring
RICE scoring gives product teams a defensible, data-groundable way to rank unlike bets on a single scale — but only when the inputs are driven by evidence, not advocacy.
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RICE vs WSJF
RICE ranks items by output potential divided by effort and suits discovery-stage product teams, while WSJF ranks by economic cost of delay divided by duration and suits program-level sequencing — the right choice depends on your planning cadence and whether you can measure delay cost in real terms.
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WSJF (Weighted Shortest Job First)
WSJF prioritizes the work that delivers the most value per unit of time by making Cost of Delay — including urgency and risk — an explicit part of every sequencing decision.
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Activation Rate
Activation rate measures how many new users reach a defined first-value moment within a set window, making it the highest-impact early signal of whether users will stick around.
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Net Revenue Retention (NRR)
NRR tracks how much recurring revenue a fixed cohort of existing customers generates over time — expansion minus contraction and churn — and crossing 100% is the line between a base that shrinks and one that compounds on its own.
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North Star Metric
A North Star Metric is the single leading indicator of delivered customer value that a whole team optimizes toward — not a revenue number, and never a vanity count like total signups.
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Build vs Buy Product Stack
Buy commodity product tooling and reserve engineering investment for capabilities that directly differentiate your product — but account for integration debt when counting the true cost of a fragmented stack.
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Continuous Discovery
Continuous discovery turns customer research from a periodic project into a weekly team habit, ensuring product decisions stay connected to real evidence rather than internal assumptions.
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Feedback-to-Revenue
Feedback-to-Revenue closes the loop between what customers ask for and what building it is actually worth by joining feedback, product work, and revenue data into a single traceable chain.
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Now-Next-Later Roadmap
A Now-Next-Later roadmap trades false date precision for honest confidence horizons — communicating sequence and intent around outcomes, so changing plans read as progress rather than missed deadlines.
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Product Analytics vs Web Analytics
Web analytics tells you how people find and browse your site; product analytics tells you whether users get lasting value from what you built — and product teams need both, joined at the user level, to make sound decisions.
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