Startup & GTM Terms

A working glossary of the strategy, unit-economics, go-to-market, and funnel vocabulary that recurs across the teardowns. Built for engineers: each entry is a tight definition and, where it helps, a one-line example or test — not an essay.

Strategy & positioning

Wedge — the one sharp capability you use to enter a market and earn a foothold before expanding. Narrow enough to actually win, expandable enough not to dead-end. Stripe: developer-friendly payments. Figma: browser-based real-time collaboration.

Beachhead — the first narrow segment you fully dominate before expanding outward. The wedge is the capability; the beachhead is the market slice it wins you.

Moat — a durable competitive advantage that makes you hard to copy or displace. Common types: network effects, switching costs, economies of scale, brand/trust, proprietary tech or data. Test: if a funded competitor tried to copy you, what stops them? If the answer is “just time,” it’s not a moat yet. The wedge gets you in; the moat keeps you in.

Defensibility — whether that advantage actually holds over time. A feature is a head start; defensibility is what stops it from being competed away.

PMF (product-market fit) — the product solves a real problem well enough that the market pulls it from you (usage, retention, word-of-mouth) rather than you pushing it.

ICP (ideal customer profile) — the precise customer type you’re built for: industry, size, role, pain. Sharp ICP makes targeting, messaging, and CAC efficient; a fuzzy one leaks money.

TAM / SAM / SOM — market sizing, narrowing down: Total addressable (everyone who could use it) → Serviceable (those you can actually reach/serve) → Obtainable (the slice you can realistically win near-term).

Unit economics & metrics

CAC (Customer Acquisition Cost) — what it costs to land one customer. Total sales + marketing spend ÷ new customers acquired in the period.

LTV (Lifetime Value) — total profit expected from a customer over the whole relationship. ≈ avg revenue per customer × gross margin × avg lifetime (or revenue ÷ churn rate).

LTV:CAC ratio — the headline health check. <1:1 loses money per customer (dead); ~3:1 is healthy for SaaS; >5:1 often means you’re underspending on growth and could acquire harder. Watch the trap: cheap early CAC from founder network/organic doesn’t scale — the ratio at scale is the real story.

CAC payback — months of revenue needed to recover CAC. Under ~12 months is good for SaaS; under 18 is acceptable.

ARR / MRR — annual / monthly recurring revenue: the predictable subscription run-rate (ARR ≈ MRR × 12). The default scoreboard for SaaS.

Gross margin — revenue left after the direct cost of delivering the service (hosting, inference, support). High margin is what makes LTV work — and why per-request inference cost matters so much for AI products.

Churn — the rate customers leave. Logo churn = accounts lost; revenue churn = dollars lost. Low churn is the foundation of high LTV.

NRR / NDR (net revenue retention) — revenue from your existing customers a year later, including expansion and net of churn. >100% means you’d grow even with zero new logos — the strongest single SaaS health signal.

Burn rate / runway — cash spent per month / months of cash left at that rate. Runway = cash ÷ burn; it sets the clock on the next milestone or raise.

Magic number — sales efficiency: net new ARR ÷ prior-period sales & marketing spend. >~0.75 suggests spending more on growth pays off; well below means fix the funnel before pouring in money.

Go-to-market motion

GTM (Go-to-market) — the plan for how you actually reach and sell to customers: who you target, how you find them, how you price, and how the sale happens (self-serve vs. sales-led).

PLG vs. sales-led — product-led growth: the product itself acquires/converts users (self-serve signup, free tier, bottom-up adoption). Sales-led: reps drive deals top-down. Many AI startups run a hybrid.

Land and expand — win a small initial footprint (one team, one use case), then grow seats and usage inside the account. Cheap to land, expansion does the heavy lifting.

Expansion revenue / upsell — additional revenue from existing customers (more seats, higher tier, usage). The engine behind NRR >100%.

Design partner — an early customer who co-develops the product with you in exchange for influence, access, and pricing. Source of real requirements before you have a market.

North star metric — the single number that best proxies the value customers get (e.g. weekly active documents signed). Aligns the team on outcomes, not vanity counts.

Funnel & growth

Conversion funnel — the staged path visit → signup → activated → paid → retained. A leaky funnel brings traffic in but drops people before they convert; the fix starts with finding which stage leaks worst relative to benchmark.

Top-of-funnel / bottom-of-funnel — TOFU = awareness and traffic (lots of people, low intent); BOFU = the revenue end (fewer people, high intent). A TOFU/BOFU mismatch is heavy traffic that never reaches paid.

Activation — reaching the “aha” moment that makes the product click (e.g. sent first signature request). Signups that never activate are an activation problem, not an acquisition one.

AARRR (“pirate metrics”) — the funnel as five measurable stages: Acquisition, Activation, Retention, Referral, Revenue. A checklist for where to instrument and where to look for leaks.

Cohort analysis — group users by signup week/source and watch their behavior over time. Separates an acquisition problem (bad cohorts coming in) from a retention problem (good cohorts leaking out later).

Retention curve — the % of a cohort still active plotted over time. A curve that flattens above zero = genuine stickiness; one that decays to zero = no durable value yet.

Funnel diagnostics

When traffic rises but users/paid users don’t, the name of the problem depends on where it leaks — and the fix follows the location.

Traffic-quality problem — the wrong visitors arrive (bad targeting, misleading messaging) and convert near zero. High traffic, low conversion by source is the tell — a marketing problem, not a product one.

Monetization / paywall friction — people use the product but won’t pay (the active→paid step leaks). A pricing, packaging, or value-capture problem rather than acquisition or activation.