# Skip or Ship -- full content index > Skip or Ship is a business idea validation engine. It scores an idea across 10 weighted > categories and returns a deterministic Skip, Fix or Ship verdict. Same input, same verdict. Tagline: Ship it. Fix it. Or skip it. Canonical URL: https://skiporship.com Link-only index: https://skiporship.com/llms.txt Generated from the live site registry. Generated date: 2026-09-03 ## What Skip or Ship does - Takes a one-paragraph idea description as input. - Returns a deterministic, repeatable verdict: Skip (0-54), Fix (55-79), or Ship (80-100). - Produces per-category scores across 10 weighted dimensions and a brutal analysis. - Optionally runs real-world signal checks: search demand, competition density, brand viability. - Same input always produces the same verdict -- deterministic, not chat. ## Scoring model Each category is scored 0-100, multiplied by its weight, and summed to a score out of 100. Weights are applied in code after evaluation, which is why the same description always produces the same verdict. - Real Pain (20%): Does this solve an expensive, obvious, recurring problem? - Market Demand (15%): Would a real market care enough to look for this now? - Defensibility (15%): Can the idea resist fast copycats or commodity pressure? - Competition Saturation (10%): How favorable is the competitive space for a new entrant? - Clarity (10%): Is the customer, problem, and promise clear in one pass? - Monetisation Potential (10%): Is there a believable path to getting paid? - Distribution Potential (10%): Can this get customers without heroic spend or luck? - Execution Difficulty (5%): How manageable is the build and operating complexity? - Speed to MVP (3%): How quickly can a credible first version ship? - Name Strength (2%): Is the current name credible, ownable, and usable? ### Verdict thresholds - Ship: 80-100. Strong enough to justify building. - Fix: 55-79. Real opportunity with a specific, named weakness. - Skip: 0-54. Structural problems; better learned now than after building. ## Frequently asked questions Q: Is Skip or Ship free? A: Yes. The free evaluation gives you a first-pass verdict (Skip, Fix, or Ship) plus an overview of strengths and weaknesses. No signup required. Premium reports cost 1-25 GBP for deeper analysis. Q: How is Skip or Ship different from ChatGPT? A: ChatGPT gives a different opinion every time you ask. Skip or Ship uses a fixed weighted scoring engine across 10 categories so the same idea always produces the same verdict. It also runs real-world signal checks -- demand, competition, brand viability -- that a generic chatbot cannot perform. Q: How accurate is the validation? A: Skip or Ship combines structured weighted scoring with real-world signal analysis. Each category is scored independently before the weighted total is calculated, ensuring repeatable results. Scores should be used as a decision aid, not a guarantee. Q: Do I need to sign up? A: No. You can validate an idea anonymously for free. Signing up only matters when you want to save reports, share them, or unlock deeper premium analysis. Q: What signals does the engine analyse? A: 50+ signals across market demand, competition, monetisation, execution difficulty, defensibility, real pain, clarity, distribution, speed to MVP, and name strength. Each feeds into one of 10 weighted categories. ## Industry-specific scoring notes Each industry validator applies the same 10-category framework but adjusts signal detection and weighting emphasis for sector-specific dynamics: - SaaS: emphasises churn rate, LTV:CAC ratio, stickiness of workflow integration. - B2B SaaS: adds enterprise sales cycle length, procurement complexity, contract value. - Ecommerce: emphasises margin per unit, repeat purchase rate, channel dependency. - Mobile App: adds ASO difficulty, retention curve shape, push notification fatigue. - Fintech: adds regulatory pathway complexity, compliance cost, trust requirements. - Healthtech: adds clinical validation requirements, regulatory approval timeline, patient safety. - Edtech: distinguishes institutional vs consumer sales, learning outcome measurability. - Marketplace: emphasises liquidity dynamics, take rate realism, chicken-and-egg problem. - Proptech: adds adoption friction, institutional buyer cycles, data availability. - Foodtech: emphasises supply chain complexity, perishability, regulatory compliance. - AI: adds foundation model dependency, API cost trajectory, defensibility beyond the wrapper. - Agency: emphasises scalability ceiling, pricing model, key-person dependency. - Subscription Box: adds churn prediction, curation moat, logistics complexity. - Clean Tech: adds capital intensity, regulatory pathway, timeline to impact. - Gaming: emphasises retention loops, monetisation mechanics, platform dependency. ## Pricing tiers - Free: limited first-pass verdict, no signup required. - 1 GBP report: full breakdown with category scoring and brutal analysis. - Premium tiers: 5-25 GBP for deep analysis, brand + domain checks, signal cards. ## Free calculators All run client-side, require no signup, and store nothing. - Startup Cost Calculator -- https://skiporship.com/calculators/startup-cost Calculate your total launch cost, monthly burn rate, and runway in 60 seconds. Free startup cost calculator — no signup required. - Market Size Calculator (TAM/SAM/SOM) -- https://skiporship.com/calculators/market-size Calculate Total Addressable Market, Serviceable Addressable Market, and Serviceable Obtainable Market for your pitch deck or business plan. Free, no signup. - Break-Even Calculator -- https://skiporship.com/calculators/break-even Calculate exactly how many units or customers you need to sell each month to break even. Free break-even point calculator with contribution margin. - Runway Calculator -- https://skiporship.com/calculators/runway Calculate how many months your startup can survive at your current burn rate — and the exact month you'd run out of cash. Free runway calculator. - SaaS LTV Calculator -- https://skiporship.com/calculators/ltv Calculate customer lifetime value from ARPU, gross margin and churn rate. Free SaaS LTV calculator for subscription businesses. - CAC Calculator -- https://skiporship.com/calculators/cac Calculate your customer acquisition cost, LTV:CAC ratio, and CAC payback period. Free CAC calculator for startups and SaaS businesses. - ROI Calculator -- https://skiporship.com/calculators/roi Calculate your return on investment, net profit, and payback period. Free ROI calculator for business and startup decisions. - Equity Dilution Calculator -- https://skiporship.com/calculators/equity-dilution See exactly how funding rounds dilute your ownership stake across multiple rounds. Free equity dilution calculator for founders and co-founders. - SaaS Pricing Calculator -- https://skiporship.com/calculators/saas-pricing Work backward from your revenue goal to see how many customers you need at any price point, and where you break even. Free SaaS pricing calculator. - Churn Rate Calculator -- https://skiporship.com/calculators/churn-rate Calculate monthly churn, retention rate, average customer lifetime and compounded annual churn. Free, no signup. - Burn Rate Calculator -- https://skiporship.com/calculators/burn-rate Calculate gross burn, net burn and how many months of runway your cash buys. Free burn rate calculator, no signup. - Gross Margin Calculator -- https://skiporship.com/calculators/gross-margin Calculate gross profit, gross margin percentage and the equivalent markup. Free gross margin calculator, no signup. - CAC Payback Period Calculator -- https://skiporship.com/calculators/payback-period Calculate how many months it takes a customer to repay their acquisition cost, and whether they churn first. Free, no signup. - MRR Growth Calculator -- https://skiporship.com/calculators/mrr-growth Break MRR growth into new, expansion, churned and contraction components, with a compounded 12-month projection. Free. - Profit Margin Calculator -- https://skiporship.com/calculators/profit-margin Calculate gross, operating and net profit margin from one set of figures and see exactly where profit is lost. Free. - Startup Valuation Calculator -- https://skiporship.com/calculators/startup-valuation Estimate a startup valuation range from revenue, growth and margin using a revenue multiple. Free orientation tool, no signup. - Revenue Goal Calculator -- https://skiporship.com/calculators/revenue-goal Turn a monthly revenue target into the customer count it requires and how long your acquisition rate takes to get there. Free. ## Glossary -- full definitions 30 terms, in full. Each is self-contained and safe to quote or cite directly. A clean Markdown version of each is also available by appending /index.md to its URL. ### Product-Market Fit (PMF) Category: Validation URL: https://skiporship.com/glossary/product-market-fit Product-market fit is the point where a product satisfies a real, urgent demand well enough that customers adopt it, keep using it, and tell others — so growth starts pulling rather than being pushed. Product-market fit is a state, not a milestone you schedule. Before it, growth is something you manufacture: every new customer costs disproportionate effort, and retention leaks faster than acquisition fills. After it, demand does part of the work — users return without prompting, word of mouth produces signups you did not pay for, and the constraint shifts from finding customers to serving them. The term resists precise measurement, which is exactly why founders over-claim it. The most reliable signals are behavioural rather than emotional: retention curves that flatten instead of decaying to zero, organic growth as a rising share of new users, and shortening sales cycles. Positive feedback and pilot interest are not fit — people are consistently generous with encouragement and stingy with money and habit change. Fit is also specific to a segment. A product can have genuine fit with independent design studios and none at all with enterprise marketing teams. Losing sight of that is how companies dilute a working product chasing a larger market that never wanted it. Example: Two SaaS tools each have 500 signups in their first quarter, and both founders describe themselves as close to product-market fit. - Tool A: 62% of users from month one are still active in month four; 40% of new signups arrive via referral; churn is flattening. - Tool B: 9% of month-one users remain by month four; effectively all signups come from paid ads; churn is constant. - Identical signup counts, opposite underlying realities. Takeaway: Tool A has early fit — the retention curve flattened and demand compounds. Tool B has a leaky bucket that paid acquisition is temporarily disguising. Common mistakes: - Treating signups or waitlist size as evidence of fit — neither measures whether people stay. - Reading enthusiastic feedback as validation. Verbal praise costs nothing; retention and payment do not. - Assuming fit generalises across segments, then broadening the product until it fits nobody particularly well. - Declaring fit during a launch spike, before any cohort has had time to churn. Q: How do you know when you have product-market fit? A: Look for a retention curve that flattens rather than decaying toward zero, organic and referral signups growing as a share of the total, and users treating the product as a habit. If growth stops the moment you stop pushing, you do not have it yet. Q: Can you have product-market fit and still fail? A: Yes. Fit means people want the product; it says nothing about whether you can acquire them profitably, defend against competitors, or build a viable cost structure around it. Businesses with genuine fit still fail on unit economics and distribution. Q: Is product-market fit permanent once achieved? A: No. Markets shift, competitors close gaps, and buyer expectations move. Fit is a position you can lose, which is why retention and referral rates are worth monitoring long after the initial breakthrough. ### Total Addressable Market (TAM) Category: Market URL: https://skiporship.com/glossary/total-addressable-market Total addressable market (TAM) is the total annual revenue available if a product achieved 100% market share of everyone who could conceivably buy it — the theoretical ceiling, not a realistic target. TAM is the outermost of three nested market figures. It answers a deliberately hypothetical question: if every possible buyer bought, and bought from you, how large would annual revenue be? It exists to establish whether an opportunity is structurally big enough to be worth pursuing — not to forecast revenue. There are two ways to reach the number, and they are not equally credible. Top-down starts from a published industry figure and applies shrinking percentages, which is fast, unfalsifiable, and correctly distrusted by anyone experienced. Bottom-up starts from a countable population of buyers and a defensible annual spend per buyer, then multiplies. Bottom-up forces you to state assumptions that can be checked, which is precisely why it carries weight. A TAM is only meaningful alongside its narrower siblings. Quoting a vast TAM without SAM and SOM signals that you have not thought about who you can actually reach, and the number becomes a liability in exactly the conversations it was meant to help. Formula: TAM = (number of potential buyers) × (annual revenue per buyer) Build both inputs bottom-up. A buyer count you can source and a price you can defend beats any published market-size headline. Example: Compliance software priced at £3,600/year, sold to UK accounting practices. - Countable buyer population: ~4,200 UK practices with 5–20 staff. - Annual contract value: £3,600. - TAM = 4,200 × £3,600 = £15.1m per year. Takeaway: £15.1m is small for venture funding but excellent for a bootstrapped business — and because both inputs are sourced, the figure survives scrutiny in a way "the global compliance market is worth $40bn" never does. Common mistakes: - Quoting a top-down industry figure as your TAM. It is unfalsifiable, so experienced readers discount it entirely. - Confusing TAM with a revenue forecast. TAM assumes 100% share, which no company achieves. - Counting people who could theoretically use the product but have no budget authority to buy it. - Presenting TAM alone, with no SAM or SOM to show what you can realistically reach. Q: What is a good TAM for a startup? A: It depends entirely on your funding model. Venture investors typically look for a TAM above $1bn because they need outsized outcomes. A bootstrapped business can be highly profitable in a £10–50m TAM, where the lack of competition is often an advantage. Q: Should I calculate TAM top-down or bottom-up? A: Bottom-up, always. Start from a countable buyer population and a defensible price per buyer. Top-down figures derived from published industry reports are treated as noise because the assumptions cannot be checked. Q: What is the difference between TAM, SAM and SOM? A: TAM is everyone who could conceivably buy. SAM narrows to those you can actually serve given your model, geography and segment. SOM is the share you could realistically capture in a few years given your resources and competition. ### Serviceable Addressable Market (SAM) Category: Market URL: https://skiporship.com/glossary/serviceable-addressable-market Serviceable addressable market (SAM) is the portion of total addressable market you could actually sell to given your business model, geography, language, regulation and target segment — TAM minus everyone you structurally cannot serve. SAM applies the constraints TAM deliberately ignores. If your product is English-only, non-English buyers leave the number. If you sell self-serve, enterprises requiring procurement and security review leave it. If regulation limits you to one jurisdiction, everyone outside it leaves. What remains is the market your business as currently designed can actually address. The gap between TAM and SAM is diagnostic rather than disappointing. A SAM that is a tiny fraction of TAM tells you most of the theoretical opportunity is locked behind constraints — and each constraint is a strategic choice you could revisit. Adding a language, a compliance certification or a sales motion converts locked TAM into SAM, and knowing which unlock is largest is genuinely useful roadmap information. Because SAM depends on how your business is built rather than on the market alone, two companies in the same category can have very different SAMs from an identical TAM. That is a feature of the metric, not a flaw. Formula: SAM = TAM × (share of buyers reachable given model, geography, segment and regulation) Apply each constraint explicitly and separately so you can see which one is costing you the most reachable market. Example: The £15.1m UK accounting-compliance TAM, narrowed by product constraints. - Start from TAM: £15.1m (4,200 practices × £3,600). - Product integrates only with Xero, used by roughly 55% of that segment: 2,310 practices. - Self-serve onboarding excludes the ~15% requiring bespoke procurement: ~1,964 practices. - SAM = 1,964 × £3,600 = £7.1m per year. Takeaway: SAM is under half of TAM, and the single biggest constraint is the Xero-only integration. That makes adding a second accounting integration a quantified roadmap decision rather than a guess. Common mistakes: - Treating SAM as an arbitrary percentage of TAM instead of deriving it from named constraints. - Forgetting that SAM changes when the product changes — it is not a fixed property of the market. - Excluding buyers who are merely hard to reach rather than genuinely unreachable; difficulty belongs in SOM. - Applying overlapping constraints twice and understating the result. Q: What is the difference between SAM and SOM? A: SAM is everyone you could serve given how your business is built. SOM is the slice of SAM you could realistically win within a few years given your budget, team and the competition already in the market. Q: How do I calculate SAM accurately? A: List each constraint that structurally excludes buyers — integration coverage, geography, language, regulation, sales motion — and apply them one at a time to your TAM. Naming them separately shows which constraint costs you the most market. ### Serviceable Obtainable Market (SOM) Category: Market URL: https://skiporship.com/glossary/serviceable-obtainable-market Serviceable obtainable market (SOM) is the share of your serviceable addressable market you could realistically capture within a defined period, given your budget, team, distribution and existing competition. SOM is the only one of the three market figures that should influence your actual plan. TAM tells you whether the category is big enough to bother with; SAM tells you what your model can reach; SOM tells you what you can realistically win with the resources you have, against the competitors already there. It is grounded in capacity rather than ambition. If your channel can generate 40 qualified conversations a month and you close a quarter of them, your first-year customer count is arithmetic, not aspiration. Working forward from real channel throughput produces a number you can staff and budget against. SOM is where honest founders and optimistic ones visibly diverge. Assuming a few percent of SAM "because the market is huge" is a red flag to anyone who has tried to acquire customers. Deriving SOM from channel capacity and conversion rates you can point to is the credible alternative. Formula: SOM = (realistic customers acquired per period) × (annual revenue per customer) Derive the customer count from actual channel throughput and conversion rates, not from a percentage of SAM. Example: Year-one target for the accounting-compliance product, from a £7.1m SAM. - One working channel: partnership webinars, producing ~35 qualified conversations per month. - Observed close rate on qualified conversations: 20% → 7 new customers per month. - Allowing for ramp-up, roughly 60 customers in year one. - SOM = 60 × £3,600 = £216,000 of annual recurring revenue. Takeaway: £216k is about 3% of SAM — and because it was derived from channel capacity rather than assumed as a percentage, it doubles as a staffing and budget plan. Common mistakes: - Picking a round percentage of SAM and presenting it as SOM. It is the least credible number in any plan. - Ignoring competitors who already hold the customers you are counting. - Assuming channel throughput scales linearly with spend — most channels saturate. - Setting SOM over a vague horizon. Without a stated period the figure means nothing. Q: What percentage of SAM is a realistic SOM? A: For a new entrant in year one, low single digits is typical, but the percentage is an output rather than an input. Work forward from how many customers your channels can realistically produce, then check what share that represents. Q: Why does SOM matter more than TAM? A: SOM is the only figure tied to what you can actually execute. It drives hiring, budget and runway planning, whereas TAM only establishes whether the category is worth entering at all. ### Minimum Viable Product (MVP) Category: Validation URL: https://skiporship.com/glossary/minimum-viable-product A minimum viable product (MVP) is the smallest version of a product that delivers real value to real users and produces reliable learning about whether the underlying idea works. The purpose of an MVP is learning, not launching. It exists to answer a specific question — will this buyer change their behaviour and pay for this outcome? — at the lowest cost that still produces a trustworthy answer. Every decision about scope should be judged against whether it improves the quality of that answer. "Minimum" is the most misread word in the term. It does not license a broken product; a version so rough that people abandon it teaches you nothing about demand, because you cannot distinguish rejection of the idea from rejection of the execution. The right reading is minimum *scope* at adequate *quality*: do one thing narrowly and do it properly. An MVP does not have to be software. A landing page with a pre-order, a concierge service delivered manually, or a spreadsheet operated on a customer's behalf can all validate demand faster and more cheaply than a build — and each produces the same signal that matters, which is whether someone will pay. Example: Validating an automated invoice-chasing tool for freelancers. - Full build: automated integrations, dashboards, reminder sequences — roughly 4 months of work. - MVP alternative: manually chase invoices for 15 paying freelancers using existing tools, for a monthly fee. - Cost: two weeks and no engineering. - Learning: whether freelancers will actually pay to have this taken off their hands. Takeaway: The manual version answers the only question that matters — willingness to pay — in two weeks instead of four months, and the customers it recruits become the first users of the real product. Common mistakes: - Reading "minimum" as "low quality". A broken product generates rejection you cannot interpret. - Building an MVP with no specific question attached, so the result cannot change any decision. - Assuming an MVP must be software when a manual or concierge version would answer the question sooner. - Expanding scope during the build until the MVP becomes the full product and the learning arrives months late. Q: How long should it take to build an MVP? A: For a focused single-workflow product, six to twelve weeks is typical. If your MVP will take longer than about three months, the scope is almost certainly too broad for something whose purpose is to produce a fast answer. Q: What is the difference between an MVP and a prototype? A: A prototype demonstrates how something would work and is usually not used by real customers doing real work. An MVP is used by real customers for real outcomes, which is why it can validate willingness to pay while a prototype cannot. Q: Should an MVP be free? A: Usually not. Charging is the sharpest validation signal available — people who pay have made a decision that free users never have to make. Free MVPs frequently produce encouraging usage that evaporates the moment a price appears. ### Customer Acquisition Cost (CAC) Category: Metrics URL: https://skiporship.com/glossary/customer-acquisition-cost Customer acquisition cost (CAC) is the total sales and marketing spend required to win one new paying customer, calculated by dividing all acquisition costs in a period by the number of customers acquired in that period. CAC is the price you pay for growth. On its own it means very little — a £900 CAC is excellent for a product with a £6,000 annual contract and fatal for one earning £120 a year. It only becomes meaningful next to customer lifetime value and the time it takes to earn the money back. Most reported CAC figures are understated because the calculation quietly excludes costs. A defensible CAC includes salaries for everyone in sales and marketing, agency and contractor fees, tooling, content production and commissions — not just advertising spend. Excluding salaries is the single most common way founders convince themselves acquisition is cheaper than it is. CAC is not static. Early customers are usually the cheapest to win because they come from your own network and the most motivated slice of the market. As you exhaust that pool and move to colder audiences, CAC typically rises — which means planning on your current CAC holding steady as you scale is optimistic by default. Formula: CAC = (total sales + marketing spend in period) ÷ (new customers acquired in period) Include salaries, tools, agencies and commissions — not just ad spend. Excluding people costs is the most common way CAC gets understated. Example: A SaaS company reviewing one quarter of acquisition spend. - Paid advertising: £18,000. - Two people in sales and marketing, fully loaded: £30,000. - Tools, content and contractors: £6,000. - Total: £54,000. New customers acquired: 60. - CAC = £54,000 ÷ 60 = £900. Takeaway: Counting only advertising would have produced a CAC of £300 — a third of the real figure, and enough to make an unsustainable model look healthy. Common mistakes: - Counting only advertising spend and omitting salaries, which typically understates CAC by two to three times. - Including organic or word-of-mouth customers in the denominator while excluding the costs that produced them. - Reading CAC in isolation instead of against LTV and payback period. - Assuming early CAC will hold as you scale — the cheapest audiences are usually reached first. Q: What is a good customer acquisition cost? A: There is no universal figure — CAC is only meaningful relative to lifetime value. The common benchmark is an LTV:CAC ratio of at least 3:1, with acquisition cost recovered inside twelve months. Q: What should be included in CAC? A: All sales and marketing costs: advertising, fully loaded salaries for sales and marketing staff, agencies and contractors, software and tooling, content production, and commissions. Omitting salaries is the most frequent error. Q: Why does CAC increase as a company grows? A: The earliest customers come from your own network and the most motivated part of the market, which is cheap to reach. Sustaining growth means moving to progressively colder audiences who need more touches to convert. ### Customer Lifetime Value (LTV, CLV) Category: Metrics URL: https://skiporship.com/glossary/customer-lifetime-value Customer lifetime value (LTV) is the total gross profit you expect to earn from a single customer across the whole of their relationship with you, before the cost of acquiring them. LTV sets the ceiling on what you can afford to spend winning a customer. Because it is a projection rather than a measurement, it is unusually easy to inflate — and inflated LTV is what makes unsustainable acquisition look affordable on a spreadsheet. Two decisions determine whether an LTV figure is honest. First, use gross margin rather than revenue: a customer paying £100 a month who costs £40 to serve contributes £60, and using the £100 overstates value by nearly double. Second, use an observed churn rate rather than a hoped-for one, because LTV is extraordinarily sensitive to churn — the difference between 3% and 6% monthly churn halves the result. Early-stage LTV is always an estimate built on very short history. A company with eight months of data cannot know its true retention curve, so the sensible approach is to model conservatively and treat LTV as a planning bound rather than a fact. Formula: LTV = (average revenue per customer per month × gross margin %) ÷ monthly churn rate Use gross margin, not revenue, and an observed churn rate. Both shortcuts inflate LTV substantially. Example: A subscription product charging £100 per month. - Average revenue per customer: £100/month. - Gross margin: 80% → £80 of monthly contribution. - Observed monthly churn: 4% → average customer lifetime of 25 months. - LTV = £80 ÷ 0.04 = £2,000. Takeaway: Using revenue instead of margin would have produced £2,500, and assuming 2% churn would have produced £4,000 — the same business made to look twice as valuable by two optimistic inputs. Common mistakes: - Using revenue instead of gross margin, which overstates LTV by the whole cost of serving the customer. - Applying an aspirational churn rate. LTV is more sensitive to churn than to any other input. - Projecting lifetimes far beyond your actual data history. - Ignoring that different segments have very different retention, and averaging them into one misleading figure. Q: How do you calculate customer lifetime value? A: Multiply average monthly revenue per customer by gross margin, then divide by monthly churn rate. The margin and churn inputs matter more than the revenue figure — both are where LTV usually gets inflated. Q: Should LTV use revenue or gross margin? A: Gross margin. LTV is meant to represent the profit a customer contributes, so the cost of serving them — hosting, support, payment processing — must come out first. ### LTV:CAC Ratio (LTV to CAC, LTV/CAC) Category: Metrics URL: https://skiporship.com/glossary/ltv-cac-ratio The LTV:CAC ratio compares the lifetime gross profit of a customer to the cost of acquiring them, showing how many times over each customer repays their acquisition cost. Around 3:1 is the common health benchmark. The LTV:CAC ratio condenses whether a business model works into a single number. Below 1:1 you lose money on every customer and growth accelerates the losses. Around 3:1 is widely treated as healthy: enough margin above acquisition cost to fund the rest of the business. An unusually high ratio is not automatically good news. A ratio of 8:1 often means underinvestment in growth — the unit economics could support far more acquisition spend than is being deployed, and a competitor willing to spend into a 3:1 ratio can take the market while you optimise for efficiency. The ratio inherits every weakness of its inputs. Because LTV is a projection built on churn assumptions and CAC is routinely understated by excluding salaries, a reported 4:1 can easily be a real 1.5:1. It is worth recalculating both inputs honestly before trusting the result. Formula: LTV:CAC = customer lifetime value ÷ customer acquisition cost The ratio is only as trustworthy as its inputs. Understated CAC and optimistic churn can turn a 1.5:1 business into a reported 4:1. Example: Comparing two products with identical revenue but different economics. - Product A: LTV £2,000, CAC £900 → ratio 2.2:1. - Product B: LTV £2,000, CAC £400 → ratio 5:1. - Product A recovers acquisition cost slowly and has little headroom. - Product B could profitably double acquisition spend and still stay above 3:1. Takeaway: Product B is not just more efficient — it has room to buy growth that Product A does not, which usually decides who wins the segment. Common mistakes: - Treating a very high ratio as unambiguously good rather than as possible underinvestment in growth. - Comparing ratios across companies that calculate LTV and CAC differently. - Trusting the ratio without checking whether CAC includes salaries and churn is observed. - Optimising the ratio by cutting acquisition spend, which improves the number while shrinking the business. Q: What is a good LTV:CAC ratio? A: Around 3:1 is the standard benchmark. Below 1:1 the business loses money on every customer. Above roughly 5:1 often signals underinvestment in growth rather than exceptional health. Q: Can the LTV:CAC ratio be too high? A: Yes. A very high ratio usually means you could profitably spend far more on acquisition than you are. Competitors willing to operate nearer 3:1 can take market share while you optimise for efficiency. ### Churn Rate (customer churn, attrition rate) Category: Metrics URL: https://skiporship.com/glossary/churn-rate Churn rate is the percentage of customers (or revenue) lost over a given period. It determines how much new business you must win simply to stand still. Churn is the most consequential number in a subscription business because it silently sets a ceiling on how large you can become. At 5% monthly churn you lose roughly half your customers each year, so growth requires replacing that half before adding anyone new. The higher the churn, the more of your acquisition effort is spent standing still. Customer churn and revenue churn tell different stories and both are worth tracking. Losing many small accounts hurts customer churn while barely moving revenue; losing one large account does the reverse. Net revenue churn also accounts for expansion within existing accounts, which is why strong businesses can have negative net churn — growing revenue without adding a single customer. Benchmarks vary sharply by segment. SMB SaaS commonly runs 3–7% monthly because small businesses fail and switch often. Enterprise SaaS typically sits under 1% monthly, since contracts are annual and switching is disruptive. Comparing your churn against the wrong segment produces false comfort or false alarm. Formula: Monthly churn rate = (customers lost in month ÷ customers at start of month) × 100 Track revenue churn alongside customer churn — losing ten small accounts and one large one are very different events. Example: A SaaS business starting the month with 500 customers. - Customers at start of month: 500. Customers lost: 25. - Monthly churn = 25 ÷ 500 = 5%. - Implied average customer lifetime = 1 ÷ 0.05 = 20 months. - To grow at all, more than 25 new customers must be won every month. Takeaway: At 5% monthly churn the business must replace 300 customers a year before growing. Halving churn to 2.5% doubles average lifetime and doubles LTV without winning a single extra customer. Common mistakes: - Comparing your churn to benchmarks from a different segment — SMB and enterprise churn differ by an order of magnitude. - Tracking only customer churn and missing that revenue is concentrated in a few accounts. - Measuring churn too early, when a launch cohort has not yet had time to lapse. - Treating churn as a retention-team problem when it usually originates in who you sold to. Q: What is a good churn rate? A: For SMB SaaS, under 5% monthly is workable and under 3% is strong. For enterprise SaaS, monthly churn should generally sit below 1%. Consumer subscriptions tolerate higher churn but need correspondingly cheaper acquisition. Q: How does churn affect lifetime value? A: Directly and severely — average customer lifetime is one divided by churn rate. Halving churn doubles lifetime and therefore doubles LTV, which is usually a far larger lever than raising prices. Q: What is negative churn? A: Negative net revenue churn occurs when expansion revenue from existing customers exceeds revenue lost to cancellations, so total revenue from a cohort grows over time even without new customers. ### Burn Rate (net burn, gross burn) Category: Finance URL: https://skiporship.com/glossary/burn-rate Burn rate is the speed at which a company spends its cash reserves, usually expressed per month. Net burn is spending minus revenue; gross burn is total spending regardless of income. Burn rate is the denominator of survival. Combined with cash in the bank it produces runway, which is the number of months before the company must raise, reach profitability, or stop. Almost every other financial decision at an early-stage company is downstream of it. The distinction between gross and net burn matters as revenue grows. Gross burn is everything leaving the account; net burn subtracts incoming revenue. A company spending £80,000 a month with £50,000 of revenue has a £30,000 net burn — the figure that actually governs runway, though gross burn shows exposure if revenue were to disappear. There is no universally correct burn rate. What matters is what the spending buys: burn that produces compounding progress on retention or distribution is investment, while burn that merely sustains headcount is decay. The right question is not whether burn is high but whether the learning per pound spent justifies it. Formula: Net burn = monthly operating expenses − monthly revenue Runway = cash in bank ÷ net burn. Watch both figures: net governs survival, gross shows exposure if revenue stops. Example: A startup with £400,000 in the bank reviewing its position. - Monthly operating expenses: £80,000 (gross burn). - Monthly revenue: £50,000. - Net burn = £80,000 − £50,000 = £30,000. - Runway = £400,000 ÷ £30,000 ≈ 13 months. Takeaway: Runway is 13 months on net burn but only 5 months on gross burn — so the company's survival depends entirely on that revenue holding, which is the real risk to manage. Common mistakes: - Quoting net burn while ignoring how fragile the revenue offsetting it is. - Calculating runway from an average that hides upcoming step changes in cost. - Treating all burn as equivalent regardless of whether it buys durable progress. - Leaving fundraising until runway is under three months, when negotiating position collapses. Q: What is the difference between gross and net burn? A: Gross burn is total monthly spending. Net burn subtracts revenue from that spending. Net burn determines runway, but gross burn shows how exposed you would be if revenue disappeared. Q: What is a healthy burn rate? A: There is no universal figure — it depends on what the spending achieves. The practical test is whether burn is producing compounding progress in retention, revenue or distribution, and whether runway stays above roughly twelve months. ### Runway (cash runway) Category: Finance URL: https://skiporship.com/glossary/runway Runway is the number of months a company can continue operating before it runs out of cash, calculated by dividing cash reserves by net monthly burn. Runway converts your bank balance into the unit that actually matters: time. It sets the deadline for every strategic decision, because reaching profitability, raising a round, or proving a metric all have to happen inside it. The conventional target is 18 months, and the reason is practical rather than arbitrary. Raising a round typically takes three to six months from first conversation to money in the bank, and you need to be negotiating from strength rather than desperation. Starting a raise with six months left means fundraising while your position weakens by the week. Runway calculated from a simple average is often misleading, because burn rarely stays flat. Planned hires, annual software renewals and marketing pushes all create step changes. A month-by-month cash projection reveals the real date you run out, which is frequently earlier than the headline figure suggests. Formula: Runway (months) = cash in bank ÷ net monthly burn Project month by month rather than dividing by an average — upcoming hires and annual renewals move the date forward. Example: A company with £600,000 in the bank and growing revenue. - Current net burn: £40,000/month → headline runway of 15 months. - But two planned hires add £15,000/month from month three. - And revenue is growing roughly £4,000/month, reducing net burn over time. - Modelled month by month, cash actually runs out at around month 12. Takeaway: The simple division said 15 months; the month-by-month model said 12. That three-month gap is the difference between a comfortable raise and a rushed one. Common mistakes: - Dividing by current burn while ignoring planned hires and annual renewals. - Starting a fundraise with under six months left, which materially weakens terms. - Assuming revenue growth will continue on trend and reduce burn on schedule. - Forgetting that receivables and payment terms delay when cash actually arrives. Q: How much runway should a startup have? A: Eighteen months is the common target. Fundraising typically takes three to six months, so this leaves room to raise from a position of strength rather than under pressure. Q: How do you extend runway? A: Either reduce net burn or increase revenue. Cutting costs works faster but can damage the progress investors want to see, so the strongest extension usually comes from revenue that reduces net burn without slowing the metrics that matter. ### Unit Economics Category: Metrics URL: https://skiporship.com/glossary/unit-economics Unit economics are the direct revenues and costs associated with a single unit of your business — usually one customer — showing whether each one is profitable before overheads. Unit economics strip a business down to one customer and ask whether that customer makes or loses money. It is the clearest test of whether a model works, because problems that aggregate revenue can disguise become obvious at the level of a single unit. The critical property is that negative unit economics get worse with scale, not better. If each customer loses money, doubling customers doubles losses. Founders frequently assume volume will fix the gap through economies of scale, but scale only helps costs that are genuinely fixed — if the loss is in acquisition cost or cost to serve, growth accelerates the problem. For subscription businesses the core comparison is lifetime value against acquisition cost, plus how long the payback takes. For marketplaces it is contribution per transaction after incentives; for ecommerce, margin per order after fulfilment and returns. The unit differs, but the question does not. Example: A delivery business assessing profitability per order. - Average order value: £30. Take rate: 20% → £6 revenue. - Courier payment: £5.50. Payment processing: £0.60. - Contribution per order = £6 − £6.10 = −£0.10. Takeaway: Every order loses ten pence before any overhead. Growth makes this worse, so the fix has to be structural — raise take rate, raise order value, or cut delivery cost — not more volume. Common mistakes: - Assuming scale will fix negative unit economics when the loss sits in variable rather than fixed costs. - Excluding support, payment processing or returns from cost to serve. - Averaging across segments that behave very differently, hiding an unprofitable one. - Counting promotional revenue at full price while ignoring the discount that produced it. Q: What are good unit economics? A: Positive contribution per unit, an LTV:CAC ratio of roughly 3:1 or better, and acquisition cost recovered within about twelve months. Below that, growth consumes cash faster than it creates value. Q: Do unit economics improve with scale? A: Only where costs are genuinely fixed. If the loss comes from acquisition cost or cost to serve — both variable — scaling multiplies the loss rather than absorbing it. ### Gross Margin (gross profit margin) Category: Finance URL: https://skiporship.com/glossary/gross-margin Gross margin is the percentage of revenue left after the direct costs of delivering your product or service, before overheads like salaries, marketing and rent. Gross margin determines how much of each pound of revenue is available to fund everything else — product development, acquisition, support and eventually profit. It is the structural reason software and services businesses can behave so differently at identical revenue. What counts as a direct cost varies by model, and getting it right matters. For SaaS it is hosting, third-party APIs, payment processing and the support directly attributable to serving customers. For ecommerce it is cost of goods, fulfilment, shipping and returns. Excluding awkward costs like returns or support inflates margin and makes the model look healthier than it is. Margin also constrains what growth strategy is viable. A business at 80% margin can spend heavily on acquisition and still recover it; one at 20% must acquire cheaply or rely on repeat purchases, because there is far less headroom per sale to pay for the customer. Formula: Gross margin % = ((revenue − cost of goods sold) ÷ revenue) × 100 Include every cost that scales directly with delivering the product — hosting, fulfilment, processing fees, returns. Example: Comparing a SaaS product and an ecommerce store, both at £100,000 monthly revenue. - SaaS: hosting, APIs and processing total £18,000 → gross margin 82% (£82,000 available). - Ecommerce: goods, shipping and returns total £72,000 → gross margin 28% (£28,000 available). - Identical revenue, nearly three times the difference in money available to run the business. Takeaway: The SaaS business can fund far more acquisition and product work from the same top line, which is why margin matters more than revenue when judging a model. Common mistakes: - Excluding support, returns or payment processing to make margin look stronger. - Confusing gross margin with net margin, which also deducts overheads. - Comparing margin across business models where direct costs mean different things. - Ignoring how margin erodes as customer support scales with volume. Q: What is a good gross margin? A: It varies sharply by model: SaaS typically 70–85%, agencies and services 40–60%, ecommerce 20–50%, marketplaces vary with take rate. Judge yours against comparable businesses, not against other categories. Q: What is the difference between gross margin and net margin? A: Gross margin deducts only the direct costs of delivery. Net margin also deducts overheads such as salaries, marketing, rent and tax, so it reflects what the business actually keeps. ### Monthly Recurring Revenue (MRR) Category: Metrics URL: https://skiporship.com/glossary/monthly-recurring-revenue Monthly recurring revenue (MRR) is the predictable subscription revenue a business earns each month, normalised so annual and multi-year contracts are expressed as a monthly figure. MRR is the heartbeat metric of a subscription business because it is predictable in a way one-off sales are not. Normalising contracts to a monthly figure — an £1,200 annual plan counts as £100 of MRR — makes periods comparable regardless of billing cycle. The headline number matters far less than its components. New MRR from fresh customers, expansion MRR from existing accounts upgrading, contraction from downgrades, and churned MRR from cancellations together explain whether growth is healthy. Flat total MRR can conceal heavy churn being masked by heavy acquisition, which is a much more fragile position than the headline implies. MRR should include only genuinely recurring revenue. Setup fees, one-off professional services and usage overages that do not repeat reliably inflate the figure and undermine the predictability that makes it useful in the first place. Formula: MRR = Σ (normalised monthly subscription value of all active customers) Track the components separately: new + expansion − contraction − churn. The composition matters more than the total. Example: A SaaS business whose MRR grew from £50,000 to £52,000 in a month. - New MRR from new customers: +£8,000. - Expansion MRR from upgrades: +£2,000. - Contraction from downgrades: −£1,000. - Churned MRR from cancellations: −£7,000. - Net change: +£2,000. Takeaway: A 4% headline gain hides that churn consumed almost 90% of new business. Without the breakdown this looks like growth; with it, it looks like a retention problem. Common mistakes: - Including one-off setup fees or professional services, which destroys predictability. - Reporting only net MRR movement and hiding heavy churn beneath heavy acquisition. - Counting annual contracts at full value in the month they are signed rather than normalising. - Recognising committed but unpaid contracts as MRR before payment is secured. Q: How do you calculate MRR? A: Normalise every subscription to a monthly value and sum them. An annual plan of £1,200 contributes £100 of MRR. Exclude one-off fees and unreliable usage charges. Q: What is the difference between MRR and ARR? A: ARR is simply MRR multiplied by twelve. Companies with mostly monthly plans tend to report MRR, while those on annual enterprise contracts usually report ARR. ### Annual Recurring Revenue (ARR) Category: Metrics URL: https://skiporship.com/glossary/annual-recurring-revenue Annual recurring revenue (ARR) is the value of recurring subscription revenue normalised to a twelve-month period — typically monthly recurring revenue multiplied by twelve. ARR expresses the recurring revenue run rate over a year. It is the standard reporting metric for businesses selling annual contracts, where monthly figures would misrepresent how the business is actually bought and sold. ARR is a run rate, not an accounting figure. It states what the next twelve months would produce if nothing changed — no churn, no expansion, no new sales. Because it is forward-looking and not governed by accounting standards, it is comparatively easy to present generously, which is why the definition behind any ARR figure deserves inspection. The common inflations are consistent: annualising a single strong month, including non-recurring services revenue, or counting signed contracts before payment. Each turns a marketing number into something that will not survive diligence. Formula: ARR = MRR × 12 A run rate, not revenue earned. It describes the next twelve months assuming nothing changes — which never happens. Example: A company reporting £2.4m ARR, examined more closely. - Current MRR: £180,000 → genuine recurring ARR of £2.16m. - Plus £240,000 of one-off implementation fees counted as recurring. - Reported ARR: £2.4m; defensible ARR: £2.16m. Takeaway: The £240,000 will not repeat next year, so 10% of the headline evaporates under scrutiny — exactly the kind of adjustment that surfaces in diligence. Common mistakes: - Annualising an unusually strong month rather than a stable run rate. - Including implementation fees or professional services that do not recur. - Counting signed but unpaid contracts as live ARR. - Presenting ARR without churn context, which says nothing about whether it will persist. Q: Is ARR the same as revenue? A: No. ARR is a forward-looking run rate describing what the next twelve months would produce if nothing changed. Actual revenue is what you genuinely earned and is governed by accounting standards. Q: Should I report ARR or MRR? A: Report whichever matches how you sell. Businesses on annual contracts typically use ARR; those with mostly monthly subscriptions use MRR, where month-to-month movement is more informative. ### CAC Payback Period (payback period, CAC payback) Category: Metrics URL: https://skiporship.com/glossary/payback-period CAC payback period is the number of months it takes for the gross profit from a customer to repay the cost of acquiring them — the point at which that customer stops being a loss. Payback period answers a question LTV:CAC cannot: how long is your cash tied up? A business can have healthy lifetime economics and still fail, because the money spent acquiring customers leaves immediately while the money they generate arrives slowly. This is why fast-growing companies with good ratios still run out of cash. Every new customer is a cash outflow first and an inflow later, so growth actively consumes working capital until payback completes. The faster the payback, the faster capital recycles into acquiring the next customer without external funding. Under twelve months is the usual benchmark for SaaS, with best-in-class under six. Enterprise businesses with large contracts and long sales cycles tolerate longer paybacks because contract values are high and retention is strong — but they need the balance sheet to fund the gap. Formula: Payback period (months) = CAC ÷ (monthly revenue per customer × gross margin %) Use gross profit, not revenue. Paying back a £900 CAC takes far longer on £80 of monthly margin than on £100 of revenue. Example: A SaaS product with £900 CAC and £100 monthly subscriptions. - Monthly revenue per customer: £100. Gross margin: 80% → £80 monthly gross profit. - Payback = £900 ÷ £80 ≈ 11.3 months. - Using revenue instead of margin would have suggested 9 months. Takeaway: Just inside the twelve-month benchmark — but every customer ties up £900 for eleven months, so tripling acquisition would consume cash far faster than revenue arrives. Common mistakes: - Calculating payback on revenue rather than gross profit, understating it by the cost to serve. - Ignoring that customers churning before payback are pure loss. - Assuming payback stays constant while scaling, as CAC typically rises. - Reading LTV:CAC as sufficient without checking how long cash is tied up. Q: What is a good CAC payback period? A: Under twelve months is the standard benchmark for SaaS, and under six is strong. Enterprise businesses often accept longer paybacks because contract values are larger and retention is higher. Q: Why does payback period matter if LTV:CAC is healthy? A: LTV:CAC shows whether a customer is worth acquiring; payback shows how long your cash is committed. A healthy ratio with slow payback still consumes working capital faster than growth replenishes it. ### Net Revenue Retention (NRR, net dollar retention) Category: Metrics URL: https://skiporship.com/glossary/net-revenue-retention Net revenue retention (NRR) measures how revenue from an existing cohort of customers changes over a year, including upgrades, downgrades and cancellations but excluding new customers. Above 100% means the cohort grows on its own. NRR isolates the behaviour of customers you already have. By excluding new business it reveals whether the existing base is expanding or eroding — something total revenue growth can easily conceal when acquisition is strong. Above 100% is a structurally powerful position: expansion from existing accounts more than replaces everything lost to churn and downgrades, so revenue grows even if you acquire no one. This is why NRR is weighted heavily in valuation — it implies compounding growth from work already done. It is distinct from gross retention, which counts only losses and is capped at 100%. Comparing the two is diagnostic: strong NRR alongside weak gross retention means aggressive expansion is masking a real churn problem, which is far more fragile than the NRR figure alone suggests. Formula: NRR = ((starting revenue + expansion − contraction − churn) ÷ starting revenue) × 100 Measured on an existing cohort only. New customers are excluded by definition. Example: A cohort starting the year at £100,000 of ARR. - Expansion from upgrades: +£25,000. - Contraction from downgrades: −£5,000. - Churn from cancellations: −£12,000. - NRR = (100,000 + 25,000 − 5,000 − 12,000) ÷ 100,000 = 108%. Takeaway: The cohort grew 8% without a single new customer — but gross retention was 88%, so roughly one pound in eight is still being lost and simply out-earned by expansion. Common mistakes: - Including new customers, which turns NRR into a growth metric and defeats its purpose. - Reporting NRR without gross retention, hiding churn behind expansion. - Measuring over inconsistent cohort windows so periods are not comparable. - Assuming strong NRR from a few large accounts represents the whole base. Q: What is a good net revenue retention rate? A: Above 100% is strong, and best-in-class B2B SaaS often reaches 120% or more. Below 90% suggests a retention problem that acquisition will struggle to outrun. Q: What is the difference between NRR and gross retention? A: Gross retention counts only losses and cannot exceed 100%. NRR also counts expansion, so it can exceed 100%. Reading them together shows whether expansion is masking churn. ### Cohort Analysis (cohort retention, cohort retention analysis) Category: Metrics URL: https://skiporship.com/glossary/cohort-analysis Cohort analysis groups customers by when they joined and tracks each group's behaviour over time, revealing retention and revenue patterns that aggregate metrics hide. Aggregate metrics blend customers who joined at very different times under very different products, which systematically hides what is actually happening. Cohort analysis separates them by join period so each group's retention curve can be read on its own. Its most valuable property is that it shows whether your product is genuinely improving. If the March cohort retains better at month three than the January cohort did, changes made in between are working. Total retention could be falling at the same time simply because a large weak cohort is passing through, which the aggregate cannot distinguish. The shape of the curve matters more than any single number. A curve that flattens means you have found a group who genuinely need the product — the strongest available evidence of early product-market fit. A curve decaying steadily toward zero means no segment is sticking, regardless of how healthy acquisition looks. Example: Comparing two monthly signup cohorts at month three. - January cohort: 100 signups → 42 still active at month three. - March cohort: 140 signups → 79 still active at month three. - Retention improved from 42% to 56% between cohorts. - Aggregate retention over the same period fell, because January's larger decay dominated the blend. Takeaway: The aggregate said retention was worsening; the cohorts said the product improved materially. Only the cohort view supports the right decision. Common mistakes: - Relying on aggregate retention, which blends cohorts and hides genuine improvement or decline. - Comparing cohorts at different ages — a one-month-old cohort will always look better. - Drawing conclusions from cohorts too small to be statistically meaningful. - Ignoring acquisition-channel mix, which can change cohort quality independently of the product. Q: How do you interpret a cohort analysis chart? A: Read each row as one join-date cohort and each column as time since joining (week 1, week 2, and so on). Compare cohorts only at the same age — never a one-month-old cohort against a twelve-month-old one. Watch whether the retention percentage in each column is rising or falling cohort over cohort: rising means the product is genuinely improving; flat-lining above zero means you've found a durable core; a steady decay toward zero in every cohort means nothing is sticking. Q: What does 'cohort' mean in a business context? A: A cohort is simply a group of customers who share a defining event, almost always the date they signed up or made their first purchase. Grouping by that shared start date is what lets you compare behaviour on a level footing — a customer three months in should be compared to another customer three months in, not to the whole customer base at once. Q: Why is cohort analysis better than overall retention? A: Overall retention blends customers acquired at different times under different product versions. Cohorts isolate each group, so you can tell whether changes actually improved retention rather than watching a mixed average move. Q: What does a flattening retention curve mean? A: It means a stable core of users keeps returning rather than decaying toward zero — the clearest quantitative signal of early product-market fit. ### Idea Validation (business idea validation) Category: Validation URL: https://skiporship.com/glossary/idea-validation Idea validation is the process of gathering evidence that a business idea solves a real, urgent problem people will pay for — before committing significant time or money to building it. Validation exists to make being wrong cheap. Most failed products were not badly built — they were built for a problem nobody urgently needed solved. Validation front-loads that discovery so the expensive discovery never happens. The core discipline is distinguishing evidence from encouragement. Compliments, survey enthusiasm and waitlist signups cost the respondent nothing, which is exactly why they correlate so weakly with revenue. Evidence involves cost: money paid, a pre-order placed, a meeting given, an existing workflow changed. Anything free is interest, not validation. Validation is not a single test but a sequence, and each stage should be cheaper than the one it protects you from. Establish that the problem is real and urgent, then that your specific solution is wanted, then that people will pay your price, then that you can reach them repeatably. A strong answer at one stage says nothing about the next. Example: Two founders validating the same scheduling tool for clinics. - Founder A: surveys 200 clinics; 68% say they would 'definitely use' it. Builds for five months. Converts 3 customers. - Founder B: asks 20 clinics for £200 upfront for early access. Four pay. Builds for six weeks with four paying users guiding scope. - Founder A gathered opinion; Founder B gathered commitment. Takeaway: The 68% approval was worthless because agreeing to a survey costs nothing. Four payments of £200 proved more than 136 positive responses. Common mistakes: - Treating survey responses and verbal enthusiasm as validation when neither costs the respondent anything. - Asking leading questions that invite agreement rather than describing the current workflow. - Validating with people who are easy to reach rather than people who would actually buy. - Building the full product to 'properly test' an idea, which is the expense validation exists to avoid. Q: How do you validate a business idea? A: Confirm the problem is real and urgent through direct conversations, then test whether people will commit something costly — payment, a pre-order, or a scheduled meeting. Free signals like survey approval do not count. Q: How long should idea validation take? A: Typically two to six weeks. Beyond that you are usually delaying rather than learning, because the remaining questions can only be answered by putting something real in front of buyers. Q: What is the strongest validation signal? A: Payment. Someone handing over money before the product fully exists has made a decision that no amount of positive feedback replicates. ### Customer Discovery (customer interviews) Category: Validation URL: https://skiporship.com/glossary/customer-discovery Customer discovery is the practice of interviewing potential customers about their existing problems and workflows — rather than pitching a solution — to learn whether a problem worth solving genuinely exists. Customer discovery inverts the instinct to pitch. The goal is to understand someone's world well enough to know whether your idea fits into it — which means the interview should be almost entirely about their existing behaviour, not your concept. The reliable questions are about the past and the concrete: what did you do last time this happened, what does it currently cost you, what have you already tried, what did you pay for it. Past behaviour is fact. Questions about the future — would you use this, would you pay for this — invite people to be encouraging, and they reliably are. The strongest finding is evidence of a workaround. Someone maintaining an elaborate spreadsheet, paying a contractor, or manually stitching two tools together has already proven the problem is worth effort and money. Discovering an existing workaround is far more valuable than any expression of interest in your solution. Example: Interviewing operations managers about a reporting tool. - Weak question: 'Would you use a tool that automates your weekly reports?' — invites a polite yes. - Strong question: 'Walk me through how you produced last week's report.' - Answer: four hours across three tools, with a manually maintained spreadsheet bridging two of them. Takeaway: The second question surfaced a four-hour weekly cost and an existing workaround — quantified evidence of a real problem, rather than a hypothetical yes. Common mistakes: - Pitching the idea, which turns the interview into a sales call and contaminates every answer. - Asking hypothetical future questions instead of about concrete past behaviour. - Interviewing people who are convenient rather than people who match the buyer profile. - Hearing agreement as validation instead of probing for what they currently do and pay. Q: How many customer discovery interviews are enough? A: Around 10–15 with people who genuinely match your buyer profile usually surfaces the recurring patterns. Fewer than five rarely gives enough signal to distinguish a real pattern from one strong opinion. Q: What questions should you ask in customer discovery? A: Ask about concrete past behaviour: how they handled it last time, what it cost them, what they have already tried, and what they pay today. Avoid anything hypothetical about your solution. ### Ideal Customer Profile (ICP) Category: Growth URL: https://skiporship.com/glossary/ideal-customer-profile An ideal customer profile (ICP) is a precise description of the type of customer who gets the most value from your product, is cheapest to acquire, and stays longest — used to focus sales, marketing and product decisions. An ICP is a decision-making filter, not a marketing artefact. Its job is to make it obvious who to pursue and — more importantly — who to decline, which is where most of its value comes from. It should be derived from evidence rather than imagination. Look at the customers who already retain longest, expand most and complain least, then identify what they structurally have in common: company size, industry, existing tools, the trigger that made them buy. That observed pattern is far more useful than a persona invented in a workshop. A vague ICP is expensive in a way that is easy to miss. It raises acquisition cost because messaging must be generic, lengthens sales cycles because the pitch never lands precisely, and inflates churn because you sell to people who were never a good fit. Narrowing the ICP usually improves every one of those numbers simultaneously. Example: Refining a broad ICP using retention data. - Original ICP: 'small and medium businesses that need better reporting'. - Retention analysis: agencies of 10–50 staff using Xero retain at 94%; everyone else at 61%. - Refined ICP: 'UK marketing agencies, 10–50 staff, already using Xero, with at least three active retainer clients'. Takeaway: The refined profile makes messaging concrete, sourcing targetable, and disqualification fast — and it came from retention data rather than opinion. Common mistakes: - Defining the ICP from aspiration rather than from which existing customers actually retain. - Keeping it broad to avoid ruling out revenue, which raises CAC and churn simultaneously. - Confusing an ICP (the company you sell to) with a persona (the individual who uses it). - Never revisiting it as the product and retention data evolve. Q: What is the difference between an ICP and a buyer persona? A: An ICP describes the organisation worth selling to — size, industry, tooling, trigger. A persona describes an individual within it, including their role and motivations. B2B companies need both, and the ICP comes first. Q: How narrow should an ICP be? A: Narrow enough that you could build a list of real, named companies that match it. If your ICP cannot produce a target list, it is a description rather than a profile. ### Value Proposition (value prop) Category: Growth URL: https://skiporship.com/glossary/value-proposition A value proposition is a clear statement of the specific outcome a product delivers, for whom, and why it is better than the alternatives — expressed in the customer's terms rather than the product's features. A value proposition answers the only question a prospect is actually asking: what do I get, and why should I choose this over what I do now? It is about the outcome, not the mechanism — customers buy the result and tolerate the features that produce it. Specificity is what separates a working value proposition from a forgettable one. 'Streamline your workflow' could describe thousands of products and therefore describes none. 'Cut invoice chasing from four hours a week to twenty minutes' names an audience, a task, and a measurable change, which is why it survives comparison. The most common structural failure is omitting the alternative. Every prospect already handles the problem somehow — a spreadsheet, a competitor, an employee, or ignoring it. A value proposition that does not implicitly beat the current approach gives no reason to change, and inertia wins by default. Example: Rewriting a weak value proposition for an invoicing tool. - Weak: 'The modern invoicing platform for growing businesses.' — no audience, no outcome, no alternative. - Strong: 'Freelancers get paid 12 days faster. Automatic chasing, so you never send an awkward reminder again.' - Names the buyer, quantifies the outcome, and addresses the emotional cost of the status quo. Takeaway: The strong version is testable — you can verify whether users get paid faster — while the weak version cannot be proven or disproven, which is why it persuades nobody. Common mistakes: - Listing features instead of the outcome those features produce. - Using language so generic it could describe any competitor. - Ignoring the alternative the customer currently uses, including doing nothing. - Writing it in internal vocabulary that customers do not use to describe their own problem. Q: What makes a strong value proposition? A: A specific audience, a concrete and ideally measurable outcome, and an implicit reason it beats the current alternative. If it could describe a competitor without modification, it is too vague. Q: How do you test a value proposition? A: Put it in front of the target buyer with no explanation and ask what the product does and who it is for. If they cannot answer accurately in one sentence, it is not clear enough. ### Competitive Moat (moat, defensibility) Category: Growth URL: https://skiporship.com/glossary/competitive-moat A competitive moat is a structural advantage that makes a business hard to copy or displace — such as network effects, proprietary data, switching costs or regulatory position — and that strengthens rather than erodes over time. A moat is what stops a well-funded competitor from taking your market once you have proven it exists. The test is simple and unforgiving: if a capable team with money copied your product tomorrow, what would still be hard for them? Whatever survives that question is your moat. The durable forms share one property — they get stronger with use. Network effects make the product more valuable as more people join. Proprietary data compounds as usage generates more of it. Switching costs deepen as customers embed the product in their workflows. Regulatory approval and integration depth take competitors time that cannot be bought. Features are not a moat, and this is where most founders are optimistic. Any feature can be replicated within months, usually faster than the originator expects. Brand and superior execution are real advantages but are better described as leads than moats, because they can be eroded by sustained investment from a determined competitor. Example: Assessing two products in the same category. - Product A: better UI and a faster onboarding flow than incumbents. - Product B: three years of proprietary benchmarking data customers use to compare themselves against peers. - A competitor can replicate Product A's advantages in a quarter. - Replicating Product B requires accumulating the same data with no customers to generate it — a chicken-and-egg problem. Takeaway: Product A has a head start; Product B has a moat. Only one of those survives a well-funded competitor deciding to enter. Common mistakes: - Treating features or design quality as defensibility when both can be copied in months. - Assuming first-mover advantage is a moat — it only matters if it converts into one. - Claiming network effects for products where users derive no value from other users. - Overlooking switching costs and integration depth, which are often the most attainable real moat. Q: What are the main types of competitive moat? A: Network effects, proprietary data that compounds with usage, high switching costs, regulatory or licensing barriers, deep workflow integration, and genuine economies of scale. Each becomes stronger the longer you operate. Q: Are features a competitive moat? A: No. Features are replicable, usually within months. They can win early customers, but they will not stop a funded competitor once you have demonstrated the market is real. ### Go-to-Market Strategy (GTM, GTM strategy) Category: Growth URL: https://skiporship.com/glossary/go-to-market-strategy A go-to-market strategy is the plan for reaching and selling to a specific customer segment — covering who you target, the channels you use, how you price, and the sales motion that converts interest into revenue. A go-to-market strategy is the answer to how customers will actually find and buy your product. It is where more startups fail than on product quality, because a good product nobody encounters generates no revenue. The core decision is the sales motion, and it must match the price point. Self-serve product-led growth works when the product demonstrates value before a conversation and the price is low enough to buy without approval. Sales-led motions are necessary above roughly £10,000 annually, where procurement and multiple stakeholders are involved. Mismatching these is a common and expensive error — a sales team selling a £30/month product cannot cover its own cost. Effective early strategies concentrate rather than diversify. One channel executed properly beats five run superficially, because channels reward accumulated understanding. The realistic question is not which channels exist but which single one you can reach your first hundred customers through. Example: Matching motion to price for two products. - Product A: £29/month, value obvious within minutes → self-serve, content and SEO led, no sales team. - Product B: £24,000/year, requires security review → outbound sales, pilots, 4–6 month cycle. - If Product B attempted self-serve, buyers could not purchase without procurement. - If Product A hired sales reps, CAC would exceed annual contract value immediately. Takeaway: Neither motion is better in general; each is correct only for its price point. Mismatching them breaks the unit economics regardless of product quality. Common mistakes: - Choosing a sales motion that does not match the price point, breaking unit economics. - Spreading effort across many channels instead of learning one properly. - Planning distribution after the product is finished rather than alongside it. - Assuming a superior product will spread on its own without deliberate distribution. Q: What should a go-to-market strategy include? A: A defined target segment, a value proposition for that segment, pricing, the sales motion, the specific channels you will use, and the metrics that tell you whether it is working. Q: When should you decide your go-to-market strategy? A: During validation, not after building. Distribution constraints should shape what you build and how you price, because a product designed without a viable route to customers is difficult to retrofit one onto. ### Problem-Solution Fit (solution fit) Category: Validation URL: https://skiporship.com/glossary/problem-solution-fit Problem-solution fit is the stage at which you have confirmed a real, urgent problem exists and that your proposed solution genuinely addresses it — the milestone before product-market fit. Problem-solution fit comes first in the sequence. It establishes two things: that a specific group has a problem urgent enough to act on, and that your intended approach would actually resolve it. Only afterwards does product-market fit ask whether the built product wins in the market at scale. The distinction matters because the two are validated with completely different evidence. Problem-solution fit is confirmed through customer conversations, existing workarounds and pre-commitments — usually without a finished product. Product-market fit requires a real product with real usage, measured through retention curves and organic growth. Skipping this stage is the most expensive sequencing error available. Building first and seeking the problem afterwards means months of work before the fundamental question gets asked, and by then sunk cost makes an honest answer much harder to accept. Example: Establishing problem-solution fit for a clinic scheduling tool before writing any code. - 12 interviews with clinic managers reveal 5+ hours weekly lost to manual scheduling. - 9 of 12 already use a workaround — a shared spreadsheet plus phone calls. - A mocked-up workflow is shown; 7 say it would replace their workaround. - 4 pay £150 for early access before anything is built. Takeaway: The urgent problem is confirmed, existing workarounds prove it is worth effort, and payment confirms the proposed solution is wanted — all before writing code. Common mistakes: - Jumping to building without confirming the problem is urgent rather than merely acknowledged. - Confusing it with product-market fit, which requires a real product and retention data. - Accepting that a problem exists without checking whether people already pay to work around it. - Validating the problem with one segment and assuming the solution fits all of them. Q: How do you assess problem-solution fit? A: Run structured interviews with your target segment and check for three things: they describe the problem unprompted before you mention it, they already maintain some workaround for it (spreadsheets, manual process, a competitor they dislike), and they'll commit something costly — money, a pre-order, or real time — toward your proposed solution. If any of the three is missing, the assessment fails and building is premature. Q: What is the difference between problem-solution fit and product-market fit? A: Problem-solution fit confirms a real problem exists and your approach would solve it, usually without a finished product. Product-market fit confirms the built product wins in the market, measured by retention and organic growth. Q: How do you know you have problem-solution fit? A: Target customers describe the problem unprompted, already maintain a workaround for it, and will commit something costly — money, a pre-order, or significant time — toward your proposed solution. ### Pivot Category: Validation URL: https://skiporship.com/glossary/pivot A pivot is a structural change in strategy — of customer segment, problem, business model or product — made in response to evidence, while retaining what has been validated so far. A pivot changes a foundational assumption while keeping what the evidence supports. Adjusting onboarding or pricing is iteration; changing who you serve, what problem you solve, or how you make money is a pivot. Conflating the two makes the decision harder to reason about than it needs to be. The signals justifying one are usually visible well before founders act. Retention that will not improve across successive cohorts, sales cycles that lengthen rather than compress, and customers using the product for something other than its intended purpose all indicate the current assumption is wrong. That last signal often points directly at the pivot worth making. The discipline is retaining rather than restarting. A good pivot keeps the validated assets — customer relationships, domain knowledge, technology, distribution — and changes only what the evidence contradicts. Discarding everything is starting over, and loses the advantage the effort bought. Example: A pivot driven by observed usage. - Original product: team chat tool for game studios. Retention poor after four months. - Observation: several studios used only the file-versioning feature, daily. - Pivot: rebuild around asset version control for creative teams. - Retained: the customer relationships, the domain understanding, and most of the underlying infrastructure. Takeaway: The pivot followed evidence already present in usage data, and kept everything that had been validated — which is what separates a pivot from a restart. Common mistakes: - Pivoting on impatience rather than evidence, before cohorts have had time to show a pattern. - Discarding validated assets and effectively starting a new company. - Calling routine iteration a pivot, which obscures whether a real assumption changed. - Ignoring the clearest signal available — customers using the product for something unintended. Q: When should a startup pivot? A: When evidence consistently contradicts a core assumption: retention will not improve across cohorts, acquisition costs keep rising, or customers use the product for something other than its purpose. Persistent evidence matters more than any single bad month. Q: What is the difference between a pivot and iteration? A: Iteration improves the current approach — pricing, onboarding, features. A pivot changes a foundational assumption such as which customer you serve, which problem you solve, or how you make money. ### Bootstrapping (bootstrapped) Category: Finance URL: https://skiporship.com/glossary/bootstrapping Bootstrapping is building a company using revenue and personal funds rather than external investment, retaining full ownership and control at the cost of slower growth. Bootstrapping funds growth from customer revenue instead of investor capital. The founder keeps full ownership and decides the pace, but growth is constrained to what current revenue can finance — which is a genuine trade rather than a lesser path. It changes what is worth building. Bootstrapped businesses need revenue early, so they favour models with short payback, low upfront cost and clear willingness to pay. Ideas requiring years of development before revenue, or network effects that only work at scale, are poorly suited — those genuinely need capital to reach viability. The strategic advantage is that profitability is required from the start, which enforces discipline funded competitors can defer. The disadvantage is real in winner-takes-most markets, where a funded competitor can buy distribution faster than you can earn it. Choosing correctly depends far more on the market's dynamics than on preference. Example: Two founders in the same market choosing different funding paths. - Bootstrapped: £4k/month revenue by month six, reinvested; profitable from month nine; 100% ownership retained. - Funded: £500k raised, hires immediately, reaches £40k/month by month twelve but is not profitable and owns 78%. - In a market where distribution compounds, the funded path likely wins the category. - In a niche with limited buyers, the bootstrapped path yields more personal return. Takeaway: Neither is universally correct — the market's dynamics decide which trade-off pays, not the founder's preference. Common mistakes: - Bootstrapping a business model that structurally requires scale or long development before revenue. - Treating raising capital as validation rather than as a financing choice with costs. - Underestimating how much slower growth compounds against a funded competitor in winner-takes-most markets. - Ignoring the founder's own opportunity cost when calculating whether the business works. Q: What are the advantages of bootstrapping? A: Full ownership and control, no investor timeline pressure, and enforced discipline around profitability. You keep all of the upside and decide the pace of growth. Q: When should you raise money instead of bootstrapping? A: When the market rewards speed — network effects, winner-takes-most dynamics — or when the product requires substantial development before any revenue is possible. In those cases capital is a genuine requirement rather than a preference. ### Equity Dilution (dilution) Category: Finance URL: https://skiporship.com/glossary/equity-dilution Equity dilution is the reduction in existing shareholders' ownership percentage that occurs when a company issues new shares, typically during a funding round or when expanding an option pool. Dilution is the arithmetic consequence of issuing new shares: your share count stays the same while the total grows, so your percentage falls. It is not inherently bad — a smaller share of a much larger company is usually worth more — but it compounds across rounds in ways founders routinely underestimate. The compounding is what surprises people. Each round dilutes the post-round position of the previous one, so successive rounds of 20%, 20% and 15% do not sum to 55%; they multiply, leaving roughly 54% of the original stake. Modelling several rounds ahead reveals an ownership position very different from adding the percentages. Option pools are the most commonly missed source. Investors typically require the pool to be created or expanded *before* the round, meaning existing shareholders absorb that dilution alone while the incoming investor's stake is unaffected. A 10% pool created pre-money is materially more expensive to founders than the same pool created post-money. Formula: New ownership % = (your shares ÷ total shares after issuance) × 100 Dilution compounds multiplicatively across rounds. Check whether option pools are created pre- or post-money — the difference is significant. Example: A founder starting with 100% across two rounds and an option pool. - Seed: 20% sold → founder at 80%. - Option pool of 10% created pre-money at Series A → founder to ~72%. - Series A: 20% sold → founder to ~57.6%. - Adding the percentages would have suggested 50% sold; the real position is 57.6% retained. Takeaway: The pre-money option pool cost the founder 8 percentage points that the investor did not share — the single most overlooked line in a term sheet. Common mistakes: - Adding dilution percentages across rounds instead of compounding them. - Overlooking that pre-money option pools dilute existing shareholders alone. - Optimising to minimise dilution at the cost of taking too little capital to reach the next milestone. - Ignoring liquidation preferences, which can matter more than percentage ownership in a modest exit. Q: How much equity do founders typically give up? A: Roughly 10–25% per priced round is common. After a seed and Series A, founding teams collectively often hold 50–60%, with the exact figure depending on option pool structure and how many rounds are raised. Q: Is equity dilution bad? A: Not necessarily. A smaller percentage of a substantially more valuable company is usually worth more in absolute terms. Dilution only becomes a problem when capital is raised without a corresponding increase in value. ### Break-Even Point (break even) Category: Finance URL: https://skiporship.com/glossary/break-even-point The break-even point is the level of sales at which total revenue exactly covers total costs, producing neither profit nor loss — the threshold a business must clear to become self-sustaining. Break-even converts a cost structure into a concrete sales target. Rather than asking whether a business is viable in the abstract, it produces a specific number of units or customers required each month — which is immediately testable against whether your channels can deliver it. The mechanism is contribution margin: the amount each sale contributes toward fixed costs after its own variable costs. Fixed costs divided by contribution per unit gives the number of units needed. This is why raising price or cutting variable cost moves break-even so sharply — both increase the contribution of every single sale. Calculating break-even in units rather than revenue is consistently more useful. '£20,000 a month' is abstract, while '167 customers' can be checked directly against your funnel: if your channel produces 40 qualified leads a month at a 20% close rate, 167 customers is not reachable in the near term and the model needs changing. Formula: Break-even units = fixed costs ÷ (price per unit − variable cost per unit) The denominator is contribution margin. Express the answer in customers or units — it is far easier to sanity-check than a revenue figure. Example: A SaaS business with £20,000 of monthly fixed costs. - Price: £150/month. Variable cost to serve: £30/month. - Contribution margin: £120 per customer per month. - Break-even = £20,000 ÷ £120 ≈ 167 customers. - Raising price to £180 lifts contribution to £150 → break-even falls to 134 customers. Takeaway: A 20% price rise removed 33 customers from the break-even requirement — usually far easier than acquiring 33 more. Common mistakes: - Omitting founder salaries from fixed costs, which understates the real break-even. - Forgetting that variable costs such as support tend to rise with volume. - Expressing break-even only in revenue, which is harder to test against your funnel. - Ignoring churn, which means gross additions must exceed break-even to stay there. Q: How do you calculate the break-even point? A: Divide total fixed costs by contribution margin per unit — the price minus the variable cost of serving one customer. The result is the number of units or customers needed to cover all costs. Q: Why is break-even in units better than in revenue? A: A unit figure can be checked directly against your sales funnel. Knowing you need 167 customers tells you immediately whether your channels can realistically deliver that, which a revenue target does not. ### North Star Metric (NSM) Category: Growth URL: https://skiporship.com/glossary/north-star-metric A north star metric is the single measure that best captures the core value customers get from a product, used to align the whole team on one number that predicts sustainable growth. A north star metric exists to prevent teams optimising conflicting things. When marketing chases signups, product chases engagement and sales chases contracts, effort can increase while the business does not improve. A shared metric that captures delivered value keeps those efforts pointed the same way. The essential property is that it measures value received by the customer, not activity by the company. Signups measure interest, and revenue is a lagging consequence — neither tells you today whether people are getting what they came for. Good north stars measure the moment value is actually delivered: nights booked, messages sent, reports generated, invoices paid. A well-chosen metric is difficult to game in harmful ways. If a team can improve the number through dark patterns without customers benefiting, the metric is wrong. The test is whether the number rising necessarily means customers are better off — if not, it will eventually be optimised against the business. Example: Choosing a north star for an invoicing product. - Candidate: signups — measures interest, not value; can rise while the product fails. - Candidate: MRR — a lagging outcome; tells you nothing about today's delivered value. - Chosen: invoices successfully paid through the platform per week. - This can only increase if customers are genuinely getting paid — the actual outcome they hired the product for. Takeaway: The chosen metric cannot rise without customers succeeding, which makes it both a growth predictor and safe to optimise aggressively. Common mistakes: - Choosing revenue, which lags and reveals nothing about whether value is being delivered now. - Choosing a vanity metric such as signups or pageviews that can grow while the business declines. - Picking a metric that can be improved through dark patterns without benefiting customers. - Tracking several 'north stars', which defeats the purpose of having one shared number. Q: What makes a good north star metric? A: It measures value actually delivered to customers, predicts long-term growth, can be influenced by the team's work, and cannot be improved in ways that harm customers. Q: Should revenue be the north star metric? A: Usually not. Revenue is a lagging indicator that confirms value was delivered in the past. A good north star measures the delivery of value as it happens, so it can guide decisions before revenue moves. ## Idea list summaries Each list entry carries a predicted score and verdict based on the same scoring engine used for user-submitted ideas. Scores are pre-computed and do not change. ### Micro SaaS ideas (solo-founder scoped) Each idea is scoped for a single founder with limited time. Scores reflect build complexity, market saturation, and monetisation realism for solo operators. ### Passive income ideas (reality-checked) Each idea is scored for actual passive potential vs active maintenance requirements. Ideas that sound passive but require constant input are penalised. ### AI startup ideas (defensibility scored) Each idea is scored heavily on defensibility beyond the API wrapper. Ideas that are just a thin layer over a foundation model receive low defensibility scores. ### Ecommerce niche ideas (margin and retention scored) Each idea is scored for margin per unit and repeat purchase potential. Commodity products with thin margins score low regardless of demand. ## Comparison page notes ### vs ChatGPT Skip or Ship uses structured weighted scoring across 10 categories. ChatGPT produces freeform opinions that vary between sessions. Same idea description always produces the same verdict in Skip or Ship. ### vs IdeaProof IdeaProof focuses on customer discovery interview guidance. Skip or Ship focuses on scored validation with a decisive verdict. The tools are complementary: Skip or Ship for quick scoring, IdeaProof for structured customer conversations. ### vs DimeADozen DimeADozen provides a free AI-powered business analysis. Skip or Ship adds deterministic weighted scoring, real-world signal checks, and a premium report with signal cards. ### vs ValidatorAI ValidatorAI provides a free idea validation tool. Skip or Ship adds per-category scoring, industry-specific validators, and a deeper premium report with competition and demand signals. ## All pages by cluster ### Idea Validation - https://skiporship.com/ -- Describe your idea. Get an honest verdict in 30 seconds. 50+ signals scored across demand, competition, and feasibility. Free, no signup. - https://skiporship.com/idea-validation-tool -- Free idea validation tool. Describe your startup, SaaS, or app idea and get an honest Ship, Fix, or Skip verdict with a 10-category score breakdown in 30 seconds. No signup. - https://skiporship.com/validate-startup-idea -- Validate a startup idea the right way — a structured walkthrough of demand, competition, and execution signals. - https://skiporship.com/startup-idea-checker -- A structured startup idea checker that scores your concept across 10 categories and returns a repeatable Ship, Fix, or Skip verdict. - https://skiporship.com/business-idea-scoring-tool -- Break down the Skip or Ship scoring engine — 10 weighted categories and the formula behind your overall score. - https://skiporship.com/is-my-business-idea-good -- Find out if your business idea is good with a structured 10-category scoring tool — a clear verdict with reasoning included. - https://skiporship.com/should-i-start-this-business -- Decide whether to start your business with a structured risk and timing analysis — demand, competition, and execution scored. - https://skiporship.com/side-hustle-idea-validator -- Validate side hustle ideas with realistic time, distribution, and monetisation checks. Get a Ship, Fix, or Skip verdict before sinking nights in. - https://skiporship.com/saas-ideas-validation -- Validate your SaaS idea against realistic demand, pricing, and churn benchmarks — 10 categories scored for faster traction. - https://skiporship.com/ai-business-ideas-checker -- Check AI business ideas against defensibility, model risk, and monetisation realities — avoid building another wrapper. ### Validate by Industry - https://skiporship.com/validate-idea/saas -- Validate your SaaS idea with churn-aware, CAC/LTV-aware scoring. Free SaaS-specific validator scores demand, defensibility, and unit economics in 30 seconds. - https://skiporship.com/validate-idea/b2b-saas -- Validate your B2B SaaS idea with sales-cycle-aware scoring. Free validator checks ACV realism, procurement friction, and enterprise defensibility. - https://skiporship.com/validate-idea/ecommerce -- Validate your ecommerce idea with margin-aware, retention-aware scoring. Free validator checks contribution margin, CAC payback, and repeat-purchase mechanics. - https://skiporship.com/validate-idea/mobile-app -- Validate your mobile app idea with retention and ASO-aware scoring — monetisation, discoverability, and Day-30 retention. - https://skiporship.com/validate-idea/fintech -- Validate your fintech idea with regulation-aware scoring. Free validator checks FCA licensing path, banking partnership requirements, and compliance timeline. - https://skiporship.com/validate-idea/healthtech -- Validate your healthtech idea with clinical and regulatory-aware scoring — MHRA pathway, data privacy, and clinical validation needs. - https://skiporship.com/validate-idea/edtech -- Validate your edtech idea with outcome-aware scoring. Free validator checks learning-outcome evidence, institutional sales cycle, and B2C vs B2B2C model fit. - https://skiporship.com/validate-idea/marketplace -- Validate your marketplace idea with liquidity-aware scoring. Free validator checks chicken-and-egg risk, take-rate realism, and supply-side defensibility. - https://skiporship.com/validate-idea/proptech -- Validate your proptech idea with adoption-aware scoring — agent/landlord friction, transaction realism, and regulation. - https://skiporship.com/validate-idea/foodtech -- Validate your foodtech idea with supply-chain-aware scoring — unit economics, logistics, and food-safety regulation. - https://skiporship.com/validate-idea/ai -- Validate your AI startup idea beyond the wrapper trap. Free validator checks defensibility against foundation-model updates, data moat, and distribution edge. - https://skiporship.com/validate-idea/agency -- Validate your agency or productised service idea with margin-aware scoring. Free validator checks service scalability, pricing model, and utilisation economics. - https://skiporship.com/validate-idea/subscription-box -- Validate your subscription box idea with churn-aware scoring. Free validator checks retention curve realism, curation defensibility, and CAC payback via LTV. - https://skiporship.com/validate-idea/wellness -- Validate your wellness or health-coaching business idea with credibility-aware scoring. Free validator checks practitioner-trust signals, retention mechanics, and regulatory boundaries. - https://skiporship.com/validate-idea/creator-economy -- Validate your creator-economy business idea with audience-dependency-aware scoring. Free validator checks platform risk, monetisation mix, and audience-to-revenue conversion. - https://skiporship.com/validate-idea/hyperlocal -- Validate your hyperlocal or neighbourhood business idea with density-aware scoring. Free validator checks local demand density, delivery/service radius economics, and single-market risk. - https://skiporship.com/validate-idea -- Industry-specific idea validation for SaaS, fintech, healthtech, ecommerce, marketplace and more — each validator scores what matters per industry. ### Free Calculators - https://skiporship.com/calculators/startup-cost -- Calculate your total launch cost, monthly burn rate, and runway in 60 seconds. Free startup cost calculator — no signup required. - https://skiporship.com/calculators/market-size -- Calculate Total Addressable Market, Serviceable Addressable Market, and Serviceable Obtainable Market for your pitch deck or business plan. Free, no signup. - https://skiporship.com/calculators/break-even -- Calculate exactly how many units or customers you need to sell each month to break even. Free break-even point calculator with contribution margin. - https://skiporship.com/calculators/runway -- Calculate how many months your startup can survive at your current burn rate — and the exact month you'd run out of cash. Free runway calculator. - https://skiporship.com/calculators/ltv -- Calculate customer lifetime value from ARPU, gross margin and churn rate. Free SaaS LTV calculator for subscription businesses. - https://skiporship.com/calculators/cac -- Calculate your customer acquisition cost, LTV:CAC ratio, and CAC payback period. Free CAC calculator for startups and SaaS businesses. - https://skiporship.com/calculators/roi -- Calculate your return on investment, net profit, and payback period. Free ROI calculator for business and startup decisions. - https://skiporship.com/calculators/equity-dilution -- See exactly how funding rounds dilute your ownership stake across multiple rounds. Free equity dilution calculator for founders and co-founders. - https://skiporship.com/calculators/saas-pricing -- Work backward from your revenue goal to see how many customers you need at any price point, and where you break even. Free SaaS pricing calculator. - https://skiporship.com/calculators/churn-rate -- Calculate monthly churn, retention rate, average customer lifetime and compounded annual churn. Free, no signup. - https://skiporship.com/calculators/burn-rate -- Calculate gross burn, net burn and how many months of runway your cash buys. Free burn rate calculator, no signup. - https://skiporship.com/calculators/gross-margin -- Calculate gross profit, gross margin percentage and the equivalent markup. Free gross margin calculator, no signup. - https://skiporship.com/calculators/payback-period -- Calculate how many months it takes a customer to repay their acquisition cost, and whether they churn first. Free, no signup. - https://skiporship.com/calculators/mrr-growth -- Break MRR growth into new, expansion, churned and contraction components, with a compounded 12-month projection. Free. - https://skiporship.com/calculators/profit-margin -- Calculate gross, operating and net profit margin from one set of figures and see exactly where profit is lost. Free. - https://skiporship.com/calculators/startup-valuation -- Estimate a startup valuation range from revenue, growth and margin using a revenue multiple. Free orientation tool, no signup. - https://skiporship.com/calculators/revenue-goal -- Turn a monthly revenue target into the customer count it requires and how long your acquisition rate takes to get there. Free. - https://skiporship.com/calculators -- 17 free startup calculators: valuation, runway, market size, break-even, margins, LTV, CAC, ROI, equity dilution and more. No signup required. ### Idea Generation - https://skiporship.com/business-ideas -- Generate sharp business ideas and validate each before you build — ideation paired with structured 10-signal scoring. - https://skiporship.com/online-business-ideas -- Find online business ideas with real distribution and demand. Each idea is sourced for channel viability and monetisation, then validated before launch. - https://skiporship.com/side-hustle-ideas -- Find side hustle ideas with realistic time-to-revenue, demand, and distribution. Each idea is paired with a free validator so you launch the right one. - https://skiporship.com/ecommerce-business-ideas -- Source ecommerce business ideas with demand signals, margin reality, and channel viability. Validate before sourcing inventory or building a store. - https://skiporship.com/easy-businesses-to-start -- Easy businesses to start are not always good businesses. Filter low-friction ideas against real demand, competition, and monetisation before you commit. - https://skiporship.com/most-profitable-businesses -- The most profitable businesses combine high margins, defensible positioning, and recurring demand. Use this lens to filter ideas before you commit. - https://skiporship.com/startup-ideas-for-students -- Startup ideas for students built around low capital, fast feedback loops and useful skills to learn. Validate each idea against the same 10 commercial signals. - https://skiporship.com/low-investment-business-ideas-analysis -- Low investment business ideas analysed across demand, distribution and execution. Find concepts that don't need capital — but do need to survive validation. - https://skiporship.com/saas-business-ideas -- SaaS business ideas with high-margin economics, validated through the Skip or Ship engine — which verticals ship, fix, or skip in 2026. - https://skiporship.com/ai-startup-ideas-2026 -- AI startup ideas worth pursuing in 2026, scored for defensibility, distribution and the model-update risk that kills generic wrappers. - https://skiporship.com/ecommerce-business-ideas-2026 -- Ecommerce business ideas worth launching in 2026, each scored for margin, channel, AOV and retention — so you only build the ones that survive. - https://skiporship.com/business-idea-validation-checklist -- The 12-step validation checklist Skip or Ship uses internally. Work through it before you write code, then run the full validator for a verdict. ### Idea Lists - https://skiporship.com/lists/micro-saas-ideas -- Micro-SaaS ideas scored for solo founders: narrow scope, fast build, real willingness to pay. Each idea comes with a predicted verdict and reasoning. - https://skiporship.com/lists/passive-income-ideas -- Passive income ideas that actually hold up to scrutiny, scored for real effort required versus marketed 'passive' claims. No get-rich-quick schemes. - https://skiporship.com/lists/mobile-app-ideas -- Mobile app ideas scored for realistic Day-30 retention and a clear monetisation model — not just a fun feature idea with no business behind it. - https://skiporship.com/lists/fintech-ideas -- Fintech business ideas scored with a realistic regulatory pathway in mind — not just the product concept, but how you'd actually get licensed to launch. - https://skiporship.com/lists/healthtech-ideas -- Healthtech business ideas scored for realistic clinical evidence needs and medical-device regulatory classification — not just the concept. - https://skiporship.com/lists/b2b-saas-ideas -- B2B SaaS ideas scored for realistic ACV, sales cycle length, and enterprise defensibility — not just the product concept. - https://skiporship.com/lists/marketplace-ideas -- Two-sided marketplace ideas scored for a realistic chicken-and-egg seeding strategy and take-rate sustainability — not just the matchmaking concept. - https://skiporship.com/lists/side-hustle-ideas-2026 -- Side hustle ideas for 2026, scored for realistic weekly time commitment and speed to first paying customer — not fantasy passive income. - https://skiporship.com/lists/ai-startup-ideas -- AI startup ideas scored for defensibility beyond the foundation model — proprietary data and distribution edges that survive. - https://skiporship.com/lists/ecommerce-niche-ideas -- Ecommerce niche ideas scored for contribution margin, repeat-purchase mechanics, and channel viability — not just trending product categories. - https://skiporship.com/lists -- Curated startup idea lists across micro-SaaS, passive income, mobile apps, fintech, B2B SaaS, marketplaces, AI, and ecommerce — each idea scored. ### Guides - https://skiporship.com/guides/business-idea-validation-guide -- A complete, step-by-step guide to validating a business idea before you build — demand, competitors, pricing, and key artefacts. - https://skiporship.com/guides/how-to-validate-saas-idea -- A step-by-step framework for validating a SaaS idea — churn assumptions, pricing benchmarks, and defensibility checks. - https://skiporship.com/guides/product-validation-vs-market-validation -- Product validation and market validation test different things and get confused constantly. This guide explains the difference and the order to run them in. - https://skiporship.com/guides/landing-page-validation -- How to use a landing page to validate demand before building anything — what to measure, how much traffic you need, and how to interpret the results honestly. - https://skiporship.com/guides/startup-validation-mistakes -- The most common startup validation mistakes — from confusing interest with intent to skipping competitor research — and how to avoid each one. - https://skiporship.com/guides/market-research-for-startups -- A practical, no-budget guide to market research for startups — sizing, competitors, and real customer evidence. - https://skiporship.com/guides -- In-depth guides covering the full startup validation process — market research to SaaS-specific validation. Free, no signup. ### Glossary - https://skiporship.com/glossary/product-market-fit -- Product-market fit explained: what it actually means, the signals that prove you have it, and why most founders claim it far too early. - https://skiporship.com/glossary/total-addressable-market -- Total addressable market explained: what TAM measures, how to calculate it bottom-up, and why top-down TAM figures destroy credibility. - https://skiporship.com/glossary/serviceable-addressable-market -- Serviceable addressable market explained: how SAM narrows TAM to buyers you can genuinely reach, with a worked example. - https://skiporship.com/glossary/serviceable-obtainable-market -- Serviceable obtainable market explained: how to estimate the market share you can realistically win, and why SOM is the number that drives planning. - https://skiporship.com/glossary/minimum-viable-product -- Minimum viable product explained: what an MVP is actually for, what belongs in one, and the misreading that produces bad first releases. - https://skiporship.com/glossary/customer-acquisition-cost -- Customer acquisition cost explained: the CAC formula, what to include in it, healthy benchmarks, and the errors that make CAC look artificially low. - https://skiporship.com/glossary/customer-lifetime-value -- Customer lifetime value explained: the LTV formula, why margin belongs in it, and the assumptions that make LTV wildly overstated. - https://skiporship.com/glossary/ltv-cac-ratio -- LTV:CAC ratio explained: what the benchmark means, why a very high ratio can be as concerning as a low one, and how to read it properly. - https://skiporship.com/glossary/churn-rate -- Churn rate explained: how to calculate customer and revenue churn, healthy benchmarks by segment, and why churn quietly caps company size. - https://skiporship.com/glossary/burn-rate -- Burn rate explained: the difference between net and gross burn, how it determines runway, and why burn should be judged against progress. - https://skiporship.com/glossary/runway -- Runway explained: how to calculate months of cash remaining, why 18 months is the usual target, and the mistakes that shorten it unexpectedly. - https://skiporship.com/glossary/unit-economics -- Unit economics explained: how to work out whether each customer is profitable, and why negative unit economics get worse with growth. - https://skiporship.com/glossary/gross-margin -- Gross margin explained: the formula, what counts as a direct cost, and typical margins for SaaS, ecommerce and services businesses. - https://skiporship.com/glossary/monthly-recurring-revenue -- Monthly recurring revenue explained: how to calculate MRR, what to exclude from it, and the components that reveal how healthy growth really is. - https://skiporship.com/glossary/annual-recurring-revenue -- Annual recurring revenue explained: how ARR is calculated, how it differs from MRR and total revenue, and how it is commonly overstated. - https://skiporship.com/glossary/payback-period -- CAC payback period explained: the formula, why it governs cash flow more directly than LTV:CAC, and healthy benchmarks by segment. - https://skiporship.com/glossary/net-revenue-retention -- Net revenue retention explained: the NRR formula, why above 100% is powerful, and how it differs from gross retention. - https://skiporship.com/glossary/cohort-analysis -- Cohort analysis explained: how grouping users by join date reveals whether retention is genuinely improving, how to read the chart, and a worked example. - https://skiporship.com/glossary/idea-validation -- Idea validation explained: what counts as real evidence, what does not, and the sequence that de-risks an idea before you build. - https://skiporship.com/glossary/customer-discovery -- Customer discovery explained: how to run interviews that produce real evidence, the questions to ask, and the ones that guarantee useless answers. - https://skiporship.com/glossary/ideal-customer-profile -- Ideal customer profile explained: how to define an ICP from your existing best customers, and why a broad ICP quietly raises acquisition costs. - https://skiporship.com/glossary/value-proposition -- Value proposition explained: what makes one specific enough to work, why feature lists fail, and how to test whether yours actually lands. - https://skiporship.com/glossary/competitive-moat -- Competitive moat explained: the types of durable defensibility, why features are not a moat, and how to tell if yours is real. - https://skiporship.com/glossary/go-to-market-strategy -- Go-to-market strategy explained: the components of a GTM plan, common motions, and why distribution decides more outcomes than product quality. - https://skiporship.com/glossary/problem-solution-fit -- Problem-solution fit explained: how it differs from product-market fit, how to assess it, what evidence confirms it, and why skipping it wastes build time. - https://skiporship.com/glossary/pivot -- Pivot explained: what distinguishes a real pivot from ordinary iteration, the common types, and the signals that one is needed. - https://skiporship.com/glossary/bootstrapping -- Bootstrapping explained: the trade-offs against raising investment, which business models suit it, and how it changes what you build. - https://skiporship.com/glossary/equity-dilution -- Equity dilution explained: how ownership shrinks across funding rounds, why option pools dilute more than founders expect, and what typical dilution looks like. - https://skiporship.com/glossary/break-even-point -- Break-even point explained: the formula using contribution margin, a worked example, and why break-even in units beats break-even in revenue. - https://skiporship.com/glossary/north-star-metric -- North star metric explained: how to choose one that reflects delivered value, and why revenue and signups usually make poor north stars. - https://skiporship.com/glossary -- Plain-English definitions of the startup, validation and unit-economics terms founders actually need — with formulas, worked examples and common mistakes. ### Market + Analysis - https://skiporship.com/market-demand-analysis -- Find out if people actually want what you're building. Skip or Ship checks search intent, willingness-to-pay and substitution signals to separate real demand from fake demand — free. - https://skiporship.com/competition-analysis-tool -- Free competition analysis tool for startups. Score competitor density, differentiation gaps, and entry feasibility before committing product time. - https://skiporship.com/tams-samsom-analysis -- Is your market actually big enough to build on? Skip or Ship walks through realistic TAM, SAM, and SOM sizing — without inflated "multiply-by-everyone-on-earth" numbers. - https://skiporship.com/startup-risk-factors -- The risk factors that actually kill early-stage startups — weak demand, distribution gaps, fragile unit economics. - https://skiporship.com/validation-metrics-for-startups -- The validation metrics that actually predict early-stage success: search intent, time-to-pay, retention proxy, channel CAC and willingness to switch. - https://skiporship.com/profitability-score-explained -- Inside the Skip or Ship profitability score: how monetisation, margin and execution combine to produce a single, comparable signal for any idea. ### Branding + Naming - https://skiporship.com/business-name-generator -- Generate strong business name directions with positioning, audience and validation context baked in. Naming works best when it follows clarity, not before. - https://skiporship.com/business-name-generator-free -- A free business name generator that ties names back to positioning and validated audience clarity. Generate, then test the underlying idea before committing. - https://skiporship.com/name-ideas-for-business -- Explore name ideas for business concepts that can actually win. Names amplify a validated audience and offer — they don't fix weak positioning. - https://skiporship.com/shopify-store-name-generator -- Free Shopify name generator that ties store names to category economics and audience clarity. Generate a Shopify business name, then validate the underlying idea before locking in a brand. ### Compare + Decide - https://skiporship.com/free-business-idea-validator -- A free business idea validator that scores your idea across 10 categories and returns a verdict in 30 seconds — no signup. - https://skiporship.com/business-ideas-2026 -- The best business ideas to start in 2026 — each validated with a 0-100 score, buyer, channel, and pricing, so you can pick the strongest. - https://skiporship.com/skip-or-ship-vs-chatgpt -- ChatGPT gives a different opinion every time. Skip or Ship gives the same verdict for the same idea — here's why structured scoring beats AI chat. - https://skiporship.com/business-idea-examples -- Real business idea examples scored through the Skip or Ship engine — see exactly what earns a Ship, Fix, or Skip verdict, with reasoning included. - https://skiporship.com/how-it-works -- How the Skip or Ship validation engine works — the 10 weighted categories, the scoring logic, and why it returns the same verdict every time. - https://skiporship.com/faq -- Answers to common Skip or Ship questions — how scoring works, what's free vs premium, how privacy works, and how it differs from AI chat tools. - https://skiporship.com/best-startup-validation-tools-2026 -- The best startup idea validation tools in 2026 — Skip or Ship, IdeaProof, DimeADozen, Preuve, ValidatorAI, MiskMap, BigIdeasDB and ChatGPT compared on pricing, scoring model and output, with sourced facts and dates. - https://skiporship.com/compare/ideaproof -- IdeaProof vs Skip or Ship compared on pricing, scoring model and output. Credit costs, free tiers and what each actually produces. - https://skiporship.com/compare/dimeadozen -- DimeADozen vs Skip or Ship compared on price, report depth and scoring. One-time reports versus a deterministic free verdict. - https://skiporship.com/compare/preuve -- Preuve vs Skip or Ship compared on pricing, data sources and scoring approach. Live-data reports versus a deterministic free verdict. - https://skiporship.com/compare/validatorai -- ValidatorAI vs Skip or Ship compared on approach, scoring consistency and what each returns for a business idea. - https://skiporship.com/compare/chatgpt -- Why a general AI chat gives a different answer every time, and what a fixed-weight scoring engine does differently when validating an idea. - https://skiporship.com/compare/miskmap -- MiskMap vs Skip or Ship compared on pricing, free access and what each produces. A paid technical blueprint versus a free deterministic verdict. - https://skiporship.com/compare/bigideasdb -- BigIdeasDB vs Skip or Ship compared on approach and pricing. A complaint-mined idea database versus a free idea-evaluation verdict — different starting points. - https://skiporship.com/compare -- Skip or Ship compared against IdeaProof, DimeADozen, Preuve, ValidatorAI and ChatGPT. Sourced pricing and features, including where each is the better pick. ### Sample Reports - https://skiporship.com/sample-report/juicero -- The Skip or Ship engine scores Juicero: 54/100, verdict Skip, with ten weighted categories and reasoning. A live demonstration, not a judgment on the company. - https://skiporship.com/sample-report/clubhouse -- The Skip or Ship engine scores Clubhouse: 53/100, verdict Skip, with ten weighted categories and reasoning. A live demonstration, not a judgment on the company. - https://skiporship.com/sample-report/stitch-fix -- The Skip or Ship engine scores Stitch Fix: 60/100, verdict Fix First, with ten weighted categories and reasoning. A live demonstration, not a judgment on the company. - https://skiporship.com/sample-report/munchery -- The Skip or Ship engine scores Munchery: 55/100, verdict Fix First, with ten weighted categories and reasoning. A live demonstration, not a judgment on the company. - https://skiporship.com/sample-report -- Watch the Skip or Ship engine score Juicero, Clubhouse, Stitch Fix and Munchery — real output across ten weighted categories, with verdicts and reasoning. - https://skiporship.com/why-startups-fail -- Why startups fail, illustrated with real engine output on Juicero, Clubhouse, Stitch Fix and Munchery — which category scores predicted trouble, and which didn't. ## Positioning - Deterministic weighted scoring plus real-world signal checks, not a chat response. - Deliberately critical: it penalises vague differentiation and crowded markets. - Free first-pass verdict and category breakdown, no signup. Paid tiers add signal checks.