Every question and definition on the site, on one page.

Agencies usually run campaigns or channels. Growth Partnership works on the growth system itself: focus, strategy, the revenue funnel, experiments and ownership. In execution we work alongside your team and, where needed, the agencies you already use.

Source: Growth Partnership

A consultant often presents a strategy and leaves; a fractional CMO mostly runs the marketing function. Growth Partnership is not limited to marketing: it treats product, pricing, sales and organization as one growth system, and aims to hand that system over to your team.

Source: Growth Partnership

Three at most. I deliberately keep capacity limited so I can be genuinely involved in strategy, execution and decision-making in every partnership.

Source: Growth Partnership

With the Partner Form. I read your message, and if I think we can do good work together, I get back to you. The first conversation is exploratory: both sides assess the fit. If it fits, we start with diagnosis.

Source: Growth Partnership

I look at the situation more than the sector: companies whose growth is stuck without a clear reason and who are ready to build a lasting system. The stage a company is in determines how the focus and strategy are chosen.

Source: Growth Partnership

We set the working arrangement together, around your team's rhythm. What matters is not the location but that regular, clearly owned rituals such as the weekly growth review keep running.

Source: Growth Partnership

A leader who can make decisions, an internal owner for growth and access to data. And openness to dropping what isn't working. Since the system stays with your team in the end, the team needs to be involved from the start.

Source: Growth Partnership

Diagnosis is completed within the first 4–8 weeks and the 90-day focus becomes clear. Lasting results come as the system settles in. This is not a quick fix; it is foundation work.

Source: Growth Partnership

An approach that uses fast, low-cost experiments to find the lever that triggers growth. It is about the speed of testing and learning, and it adds most value early on, when you don't yet know what will work.

Source: Growth Approaches

A marketing practice that keeps improving channels, messaging and budget through measurement. It is a sustained rhythm rather than a one-off experiment, and it mainly looks at acquisition, conversion and retention.

Source: Growth Approaches

No, though they overlap. Growth hacking is closer to discovering; growth marketing is closer to running what you found efficiently and sustainably. Many teams do both, at different stages.

Source: Growth Approaches

A consultant usually delivers a strategy or an audit and execution stays with you. Growth Partnership joins strategy, execution and decision processes, builds the growth system with your team and hands it over. The goal is for the system to stay in your team.

Source: Growth Approaches

It depends on the stage. Without product-market fit, fast experiments; with a working channel, channel efficiency; when the blockage is at system level, a partnership. Size alone doesn't decide it; where the problem sits does.

Source: Growth Approaches

Nominal growth is the change in the revenue figure. Real growth is what remains after removing the effect of price rises, and shows how much the company actually grew in purchasing power.

Source: The Nominal Growth Illusion

(1 + nominal growth) ÷ (1 + inflation) − 1. If revenue rose 40% while prices rose 45%, real growth is about −3.4%: revenue grew, the company shrank.

Source: The Nominal Growth Illusion

Divide the nominal growth multiple by the cumulative inflation multiple for the same period. If revenue grew 5.2× over four years while prices rose about 5.67×, real growth is 5.2 ÷ 5.67 − 1 ≈ −8%. A company that grew 420% in lira terms actually shrank in purchasing-power terms.

Source: Real Growth Calculator

When comparing annual revenue with annual revenue, the annual average change in CPI is the best fit. If your cost base differs markedly from general inflation, also calculate with your own cost index and state which one you used.

Source: The Nominal Growth Illusion

TMS 29 restates financial statements to purchasing power at the end of the reporting period, an important step for reporting. But growth decisions are mostly made on monthly dashboards, sales targets and management decks that use nominal figures. That is where the illusion lives.

Source: The Nominal Growth Illusion

Dollar growth matters for imported inputs, foreign-currency debt or comparison with overseas competitors. But the exchange rate need not move at the same pace as domestic prices. Read it together with real growth in lira.

Source: The Nominal Growth Illusion

The gap that builds up, as you grow, between the value you promise users and the value you actually deliver. Its interest is paid quietly, in churn.

Source: Value Debt

Both are taken to move fast and both charge interest. Engineers see and discuss technical debt. Value debt disappears into the growth chart, so most of the time nobody tracks it.

Source: Value Debt

No. Taking a shortcut to grab a market or make a funding round can be smart. The problem is not knowing you borrowed, not recording it and never paying it back.

Source: Value Debt

There is no single number. Read new-cohort retention, time to first value, the type of support tickets and the discount needed at renewal together. The check above turns that view into a rough reading.

Source: Value Debt

A term from a16z: a user who signs up for an AI product, tries it for a couple of months and then leaves. a16z writes that, because of them, early retention curves are a less decisive indicator of long-term retention, and it suggests measuring retention and CAC from M3 instead of M0.

Source: Growth in the AI Era

a16z says the cost of an LLM of equivalent performance falls about 10x a year, while adding that its methodology is "far from perfect" and the rate may slow. Ethan Ding argues that demand moves to the newest model, so subscription margins don't recover.

Source: Growth in the AI Era

It hides the problem in the number; it doesn't fix it. Poyar notes that NRR on annual plans runs 10-20 points above monthly; a16z says high retention on annual contracts can give false confidence and suggests looking at usage and adoption.

Source: Growth in the AI Era

In Poyar's data, products in the low price bands show markedly weaker retention, and he himself suggests separating experimental spend from serious spend. The method section of this guide proposes adapting that split to your own price structure, as a hypothesis.

Source: Growth in the AI Era

A cohort groups users by a shared starting point (usually signup period) and follows them over time. A segment groups users by an attribute (channel, plan, device). The two combine: building a separate cohort matrix for each channel is the only way to see low retention in one segment.

Source: Cohort Analysis

There is no magic number. You need at least a few cohorts to see differences between them, but the number of users per cohort matters more: Amplitude warns against drawing conclusions from small cohorts. If cohorts are small, widen the period; build monthly cohorts instead of weekly ones.

Source: Cohort Analysis

Look at your product's usage rhythm. Weekly cohorts are natural for a product used daily, monthly cohorts for a monthly subscription. As the period shortens, each cohort has fewer users; you have to balance the two.

Source: Cohort Analysis

Start with a definition that counts the core action in which the user gets value; logging in alone is usually too weak. Also know your tool's choice between counting “on that day” (On) and “on that day or after” (On or After): Amplitude and Mixpanel name the two counts separately and they give different results.

Source: Cohort Analysis

Not by itself. As Amplitude points out, cohort analysis reveals associations, not causes. To see the effect of an improvement, randomly split users in two and compare the two groups' cohort curves.

Source: Cohort Analysis

An analysis that compares the cost of winning and keeping a customer with the gross profit they bring over their lifetime. Its core measures are ARPU, gross margin, CAC, LTV, LTV:CAC and CAC payback.

Source: Unit Economics Guide

A common rule of thumb is about 3 or higher. It is not a law: a company with high margin, low churn and plenty of cash can be comfortable with less, while a cash-tight one may need more than 3.

Source: Unit Economics Guide

A frequently quoted rule of thumb is under 12 months, but that too depends on your cash position. The longer the payback, the more capital growth needs.

Source: Unit Economics Guide

In its simple form: ARPU × gross margin ÷ churn rate (for the same period). Use monthly ARPU with monthly churn. For new products churn hasn't settled, so read the result as an estimate.

Source: Unit Economics Guide

Revenue and costs rise at different speeds. If you measure LTV at today's prices and CAC at past prices, the ratio looks better or worse than it is. Both sides should be brought to the same price level.

Source: Unit Economics Guide

Because that is what it is. The annualized revenue of a private company is not an audited number; it is a founder's or an investor's statement. The archive does not hide this, it writes it next to the figure. The claim itself is data too: when it was said, under which definition and in which context all teach something.

Source: Growth Cases

Because nothing shows that a wave brings revenue but not a company better than a wave that has broken. The same loop shape appears in rising and falling cases; the difference is made by a reason to return, margin and trust. Reading only the winners is survivorship bias.

Source: Growth Cases

The mechanism applies, the scale does not. Viral output, creator programs and launch cadence work with low traffic too; but a dollar-priced model and a lira-paying customer build margin differently. Each case's 'what it teaches' section does that translation and says it is opinion.

Source: Growth Cases

The aim is not to grade but to make the mechanism readable. The verdict is about the strength of the public evidence, not about the company. 'Perception level' does not mean the company is bad; it means an outsider has no outcome data in hand.

Source: Growth Cases

KPIs are the many indicators that track the health of a team or process. The North Star is the single metric that sets the shared direction for the whole company; KPIs usually live in the input and lever layers of the metric tree.

Source: Metric Tree

A single North Star is recommended; the point is for everyone to look at the same number. Companies serving very different customer groups can build separate trees per business unit, but each tree should still have one metric at the top.

Source: Metric Tree

Input metrics are the quantities that directly make up the North Star, such as new, retained and returning users. Levers are the more concrete, weekly-trackable measures teams work on to change those inputs.

Source: Metric Tree

The templates are a starting point. Adjust the names, definitions and links to your business model, and don't start measuring until you've defined what the 'core value action' means in your product.

Source: Metric Tree

Tracking levers weekly and input metrics monthly is a common rhythm. Revisiting the tree's structure during quarterly planning, or when the business model changes significantly, is usually enough.

Source: Metric Tree

No. An investor's decision depends on the team, market, timing and relationships, among many other things. This check is only a self-assessment of your readiness on the growth and metrics side.

Source: Investment Readiness

The calculation runs in your browser and no separate request is made to send your answers. However, your choices are written into the link in the address bar; whoever you share it with sees the same result. Be careful who you share the link with.

Source: Investment Readiness

No. They are rules of thumb widely used in the industry. Enterprise sales can justify longer periods and low-priced products shorter ones. What matters is knowing a threshold that makes sense for you and measuring it consistently.

Source: Investment Readiness

In a high-inflation environment, nominal growth can be overshadowed by price increases. Investors expect you to separate the two, and not doing so can erode trust. See the Nominal Growth Illusion page for detail.

Source: Investment Readiness

Start with the three weakest areas on the result page. Closing one or two gaps often changes the overall picture noticeably. Retake the check when you are ready.

Source: Investment Readiness

Because inference cost and the failed attempt stay with the seller. Bessemer lists three conditions: confidence in performance, the ability to absorb cost variance, and a clear, measurable outcome. Poyar notes that many enterprises still crave predictability. That is why the tool recommends outcome-based pricing only when all three conditions hold together.

Source: Pricing Model Picker

In Poyar's 2026 survey (230+ software companies, April–May 2026, self-reported) hybrid was the most common model (hybrid = a combination of two or more models): 37%, up from 25% twelve months earlier. In ICONIQ's July 2026 report (Q4 2025 and Q2 2026 surveys of ~300 software executives, self-reported), consumption-based pricing rose from 35% to 42% in six months and outcome-based from 18% to 23%; companies blend 1.7 models on average. These are survey results; they do not show what is right for you.

Source: Pricing Model Picker

In Poyar's words, seats are not necessarily dying but are less effective than they used to be. Where value scales with the number of users, a seat can still make sense. As automation grows, customers need fewer seats, and revenue can fall as the product succeeds.

Source: Pricing Model Picker

In Poyar's 2026 survey, 29% of companies let customers choose between several models (230+ companies, self-reported). The option gives customers flexibility but complicates the price page and billing. Starting with one model and adding a second once usage data arrives is the healthier order (rule of thumb).

Source: Pricing Model Picker

In Bessemer's words: Tokens work for technical buyers but confuse everyone else. A token relates to your cost, not to the customer's work. For a non-technical buyer, a unit closer to value (a resolved ticket, a prepared file) or included usage inside a plan is easier to understand.

Source: Pricing Model Picker

No. It doesn't estimate, correct or benchmark the number. It only shows which questions the claim answered on its way in; the corrected number comes from your own measurement.

Source: Growth Claim Check

The other four questions adjust a measurement. If the measurement is a survey answer, there is no time or outcome to adjust. Perception is valuable, but it doesn't replace an outcome metric.

Source: Growth Claim Check

Compare with older cohorts at the same age, or roll the tool out in stages; the team or segment whose turn hasn't come yet becomes a temporary comparison. If neither is possible, write that next to the number.

Source: Growth Claim Check

There is no sign-up; the reading runs in your browser and no separate request is made to send your answers. So the reading can be shared, the answers are written to the link as a short code; if you share the link, whoever opens it sees them too. The claim sentence is not written to the link.

Source: Growth Claim Check

Because the sample size does not depend on who wrote the variant. There is no AI in the formula: only traffic, base rate and the effect you want to see. Building became free; knowing did not. Adding variants splits traffic and lowers power per experiment.

Source: Experiment Capacity

In a layered setup several experiments can share the same traffic, but each still waits for its own sample from that same traffic. The bottleneck is not 'how many at once' but 'how many weeks each, and at what effect size'. Overlapping experiments on the same page or flow also carry interaction risk.

Source: Experiment Capacity

Three paths: make a bigger change and look for a bigger effect; measure a step higher in the funnel that sees more users; or move from A/B to coarser but honest methods such as before/after comparisons, cohort tracking and holdouts. Deciding small improvements by principle, without measuring, is also a method; an A/B test run as a ritual is not.

Source: Experiment Capacity

It works, but the required sample grows a lot; low-rate metrics need disproportionate traffic to show an effect. Often the right answer is to measure a higher intermediate metric, such as reaching the checkout page. That is the same direction as Kohavi's advice on sensitive surrogate metrics.

Source: Experiment Capacity

Because the probability that a significant result is real depends on how many of your experiments truly work. The large-company rates Kohavi reports range from 8 to 33 percent. If you do not know yours, 10 percent is a reasonable start; an optimistic guess makes the tool optimistic too.

Source: Experiment Capacity

This version assumes a binary metric such as conversion and builds variance as p(1−p). For continuous metrics you need to measure variance from your own data and put it into the same formula. Variance reduction techniques such as CUPED also lower the sample; they are not included here.

Source: Experiment Capacity

They are complements. Retention is the share that stays, churn the share that leaves. 90% retention means 10% churn, but both must be measured on the same cohort and definition.

Source: What is a good retention rate?

By the natural usage rhythm of the product. Lenny's benchmark uses month 6, SaaS Capital a one-year cohort. What matters is keeping the definition fixed and tracking your own curve over time.

Source: What is a good retention rate?

First make sure you are looking at the right segment. Then isolate which cohorts and channels the losses concentrate in. A benchmark is not a diagnosis; it tells you where to look.

Source: What is a good retention rate?

Not always. Below 100% is common for products selling to very small businesses; in Lenny's table the good threshold for that segment is roughly 80%. What matters is your position within your own segment, and its direction.

Source: What is a good NRR?

GRR counts only losses and downgrades and cannot exceed 100%. NRR adds upsell, cross-sell and price increases. Together they show both leakage and growth.

Source: What is a good NRR?

Divide today's monthly revenue from people who were customers a year ago by their total monthly revenue back then. New customers enter neither number. The calculator does these steps for you.

Source: What is a good NRR?

3 is a guideline threshold; Skok describes these as guidelines only. Healthy businesses may fall below it at first. Use it as a starting point for discussion, not a target.

Source: What is a good LTV:CAC ratio?

The source does not answer this directly; it says the best businesses reach 7-8. A high ratio signals strong economics, but read it together with CAC payback when deciding how fast to push growth.

Source: What is a good LTV:CAC ratio?

When you have enough customers and a real retention history. An LTV computed from a few months of data is unreliable; in the early days cohort retention is a sturdier thing to watch.

Source: What is a good LTV:CAC ratio?

According to Skok, beyond 12 months profitability weakens; in Aleph's data the median is 16. So 12 months is a good reference, but with a high ACV it may not be realistic.

Source: What is a good CAC payback period?

On gross margin where possible. Sources may define the period differently; compare your definition with theirs before benchmarking.

Source: What is a good CAC payback period?

In Aleph's data companies growing above 50% have a median of 10 months. The report reads this as fast growth not being bought through inefficient acquisition; it is not a causal claim.

Source: What is a good CAC payback period?

Arithmetically, 1% monthly is about 11.4% annual loss, close to SaaS Capital's 90% gross retention threshold. It still depends on your segment and on whether you count revenue or customers.

Source: What is a good churn rate?

In practice, no. Even for high-ACV companies the median gross retention is around 95%; aim to reduce loss meaningfully, not to eliminate it.

Source: What is a good churn rate?

Both. Gross retention shows the loss, NRR shows it net of expansion. Looking only at NRR can hide weak retention.

Source: What is a good churn rate?

On Sacks's suggested scale for venture-stage startups, under 1x is amazing and over 3x is bad. The scale is an investor's rule of thumb; the multiple is expected to fall as the company matures.

Source: What is a good burn multiple?

Per Sacks, churn nets against the denominator and raises the multiple. Using gross bookings would hide that loss and make the multiple look better than it is.

Source: What is a good burn multiple?

Sacks finds it acceptable in the early years, when sales have just started. If it does not fall as the company matures, he treats it as a warning sign.

Source: What is a good burn multiple?

On the rule as Feld reports it, growth rate plus profit should add up to 40%; better is ‘awesome’. It is a rule of thumb with no measured industry average behind it.

Source: Rule of 40: what is a good score?

Feld writes that he heard it from a late stage investor at a board meeting, whose firm called it the 40% rule. He does not present it as his own.

Source: Rule of 40: what is a good score?

Feld takes EBITDA as the baseline and backtests with the others. If you run your own infrastructure the results diverge; state the number you use.

Source: Rule of 40: what is a good score?

In Bessemer's cloud portfolio the average is 65–70%, with the middle 50% of companies at roughly 60–80%. Top performers sit at 75–85%+ depending on ARR band. The portfolio is not a random sample.

Source: What is a good gross margin?

There is no single ‘AI margin’; the sources are separate samples. In BVP's 2025 sample Shooting Stars sit at 60%, slightly below SaaS peers (BVP gives no SaaS figure), and Supernovas at ~25%. ICONIQ's survey gives 45% for 2025, but the text does not define which segment it measures. Do not compare these directly with Bessemer's cloud portfolio through 1H21.

Source: What is a good gross margin?

In Bessemer's portfolio Twilio was strong at ~50% for much of its life; BVP ties Supernovas' low margin to trading profit for distribution. If you cannot write down why yours is low, it is a signal (our inference).

Source: What is a good gross margin?

If you are comparing annual revenues, the annual average CPI change is more consistent, because revenue accrues across the year. If you are comparing year-end balances such as cash or debt, December-on-December fits better. The calculator lets you switch between both and see the difference.

Source: Real Growth Calculator

Yes. With "My own rate" you can enter a single annual rate applied to every year. If your cost structure differs from headline CPI, for example mostly imported inputs or rent, this can give a more meaningful real growth figure for your company.

Source: Real Growth Calculator

Yes. In years when the exchange rate rises faster than inflation, lira revenue can grow while its dollar value falls. The reverse also happens. Which one matters depends on the currency of your costs and goals.

Source: Real Growth Calculator

CPI values are TurkStat's official figures as tabulated by the Central Bank of the Republic of Türkiye (CBRT); the exchange rate is the annual average of the CBRT's daily indicative USD buying rates. Only complete years are used, and the last-updated date is shown in the data note under the results.

Source: Real Growth Calculator

Not with a single number. You need to look at how fast revenue grows, whether customers stay, what growth costs and how long your cash lasts, together. This tool puts those four dimensions on one screen.

Source: Growth Check-up

On Craft Ventures' scale, under 1 is amazing, 1–1.5 great, 1.5–2 good, 2–3 suspect and above 3 bad. Burn multiple shows how much cash you burn for every unit of net new ARR.

Source: Growth Check-up

Craft Ventures gives these rules of thumb for venture-stage startups: under 1× is amazing, 1–1.5× great, 1.5–2× good, 2–3× suspect, over 3× bad. Sacks notes that the bar rises at each stage.

Source: Burn Multiple Calculator

It says your growth rate plus profit margin should be 40% or higher, a reference point often cited by investors such as Bessemer. A fast-growing company can run at a loss; a slow-growing one is expected to be profitable.

Source: Growth Check-up

It's a rule that says annual revenue growth plus profit margin should be 40% or more. In Bessemer's words, businesses above 40% are deemed increasingly valuable. It shows the balance between growth and profitability in a single number.

Source: Rule of 40 Calculator

There is no universal number. We treat under 6 months as critical and 6–12 months as a caution zone; that is our working threshold, not market data. The reasoning: a fundraise or a serious cost reset takes months, and you need time to do it.

Source: Growth Check-up

There's no universal number. The test that matters is whether your break-even month comes before the month cash runs out. If profitability isn't in sight, remember that raising money takes time too, and act well before runway gets short.

Source: Runway & Default Alive Calculator

No. Fields left at 0 are not counted. If a dimension lacks enough data, its row shows "Not enough data" and it is excluded when picking the weakest dimension.

Source: Growth Check-up

One row per cohort: a label, the cohort size (M0), then the number of users still active in each period. Tabs, semicolons, commas or spaces all work; copying from Excel is enough. Rows can have different lengths: a newer cohort shows fewer periods. If you only have retention percentages, switch the value type to percent; M0 stays a head count.

Source: Cohort Matrix Calculator

A lot. Loosen the definition and the matrix looks better while nothing has really changed. Before you run the tool, ask: does your active definition count the action where users get value, or only that they opened the app?

Source: Cohort Matrix Calculator

Conditional retention stayed at or above the threshold (default 95%) for two periods in a row: within that window, loss slowed down. Nothing more. With few cohorts, or last periods resting on few people, a plateau can be chance; the tool flags periods with a denominator under 30 as "small sample".

Source: Cohort Matrix Calculator

The projection carries the loss rate of your last observed periods forward. When you observe few periods relative to the horizon, part of the number rests on periods that have not happened yet; how much depends on the shape of the curve. When this share is high, read the LTV as an assumption rather than a measurement.

Source: Cohort Matrix Calculator

No. It is a sensitivity calculation: if the first-period rate were 5 points higher and later periods carried that through at the same ratio, what would LTV be? Only an experiment shows whether such an improvement will happen. The calculation helps you weigh whether it is worth the engineering time to try.

Source: Cohort Matrix Calculator

The calculation runs in your browser and makes no separate request to send your numbers. However, the matrix you paste (and the second segment's matrix, if any) is written into the link in the address bar. If you reload or share that link, the numbers travel with the address, and the address also reaches the server that serves the page. If the matrix is long, it is not written to the link at all. If the data is sensitive, anonymise the labels.

Source: Cohort Matrix Calculator

The commonly cited rule of thumb is 3:1. It is an industry reference point, not a law or a study result. Below 1 means you lose money on each customer. The more fundamental check is whether payback is shorter than average customer lifetime.

Source: Unit Economics Calculator

Because revenue is not all yours. LTV calculated before direct costs such as hosting, payment fees and support overstates what a customer is worth and misleads you on how much you can spend to acquire one.

Source: Unit Economics Calculator

Divide total sales and marketing spend for a period (ads, salaries, tools, agency fees) by the number of new customers won in that period. Using ad spend alone understates CAC.

Source: Unit Economics Calculator

There is no single number; it depends on your sales model. The logical limit is that it must be shorter than average customer lifetime. Bessemer points to under 12 months for SMB, under 18 for mid-market and under 24 for enterprise.

Source: Unit Economics Calculator

The formula says so, but no customer base stays forever. If your churn is too low to measure yet or you are very early, enter a conservative estimate. The calculator does not show LTV at zero churn.

Source: Unit Economics Calculator

On your provider's API pricing page. Providers price per million tokens, with input and output separate and cached input and batch processing as separate lines. The defaults in this tool are examples, not current prices; take real prices from the page and token averages from your own logs.

Source: AI Product Unit Economics Calculator

The cache share is the portion of input tokens read from cache; cached reads are priced below normal input. But providers can charge separately for writing to the cache, and if the hit rate is low the saving shrinks. Output tokens are not affected by caching either. In this tool you enter only the cached share and the read ratio; cache write fees are not a separate line, so you can approximate their effect by entering a lower cache share. The example value is zero.

Source: AI Product Unit Economics Calculator

There is no fixed rule. Rule of thumb: keep Q below the loss threshold that the flat price covers, and check that the overage price covers cost per request. A second rule of thumb: you want a Q that keeps the typical user out of overage and moves heavy users into paying it. Change Q and watch the loss threshold, the blended margin and the chart.

Source: AI Product Unit Economics Calculator

Not necessarily. This is an inference: the bill is price times tokens. If prices fall while users make longer or more requests, cost does not fall. The sensitivity table tests only a change in cost (what happens to margin if cost falls); to test growing usage, raise the typical user's requests or the token averages and compare the results.

Source: AI Product Unit Economics Calculator

From your logs: rank users by monthly requests, and look at how many times typical usage the top slice makes and what share of users it is. Where you cut the slice is a judgment call; run the tool with a few different cuts and see how far the result moves.

Source: AI Product Unit Economics Calculator

Two things: the success rate and the cost of a failed attempt. In the tool every request is an attempt; revenue is success rate times price per outcome, and the inference cost of a failed attempt stays with you. According to Bessemer, a difficult customer issue can consume far more compute than anticipated, so track the success rate split by case difficulty rather than as one average (rule of thumb). The success-rate sensitivity shows where margin goes if the rate falls by 10 and 20 points. Enter the rate from your own logs; the default value is an example.

Source: AI Product Unit Economics Calculator

Separate the goal first, because there are two different answers. To keep your lira profit, price rise = cost share × rate rise; if cost is a third of net revenue, a 30 percent rate rise needs only about a 10 percent price rise (an example for illustration). To keep your margin percentage, since all cost is in dollars, the price must rise by the same percentage as the rate. If you are profitable, the second is always the higher price, and not every market will bear it. Choosing between them is a decision: profit amount or margin? The tool shows both and makes no rate forecast; you enter the rate and the scenario. If part of your cost is paid in lira, both results come out slightly overstated.

Source: AI Product Unit Economics Calculator

In its simplest form: cash ÷ monthly net burn. Net burn is monthly expenses minus monthly revenue. 12 million in cash and 800 thousand of monthly net burn means 15 months of runway. If revenue is growing, real runway is longer; if expenses are rising, it's shorter. This tool accounts for both.

Source: Runway & Default Alive Calculator

It's from Paul Graham's 2015 essay. If your expenses stay constant and your revenue keeps growing at the rate it has over the last several months, and you reach profitability on the money you have left, you're default alive. If not, you're default dead. In other words: would you survive without raising more?

Source: Runway & Default Alive Calculator

Gross burn is the total you spend each month; net burn subtracts revenue from that. Runway uses net burn, because that's what actually leaves the bank account.

Source: Runway & Default Alive Calculator

Graham's definition holds expenses flat, which is a conservative starting point. In reality, hiring and new tools push expenses up. Enter your planned expense growth and the result reflects your own budget. Leave it at zero and the calculation matches Graham's definition exactly.

Source: Runway & Default Alive Calculator

Divide net burn for a period by net new ARR for the same period. $9M of net burn and $4M of net new ARR in a quarter is 2.25×. Net burn is expenses minus the revenue you actually collect.

Source: Burn Multiple Calculator

The ratio stops making sense: the cash you burned brought no growth, and ARR actually shrank. Understand churn and contraction first; trying to optimise the multiple is the wrong question at that point.

Source: Burn Multiple Calculator

If net burn is zero or negative, the company is generating cash and the multiple doesn't compute. A measure like the Rule of 40 is better for weighing growth against profitability.

Source: Burn Multiple Calculator

The formula works for any period, since both numbers cover the same one. But a monthly figure can jump on a single large deal. For decisions, quarterly or trailing twelve months is more reliable.

Source: Burn Multiple Calculator

Add annual revenue growth percentage to profit margin percentage. A company growing 30% with a 10% FCF margin scores 40. One growing 28% with a −6% margin scores 22.

Source: Rule of 40 Calculator

Bessemer's definitions use free cash flow (FCF) margin. Many companies calculate it with EBITDA too. FCF reflects capital expenditure and working capital, so it's the stricter measure. Whichever you choose, be consistent.

Source: Rule of 40 Calculator

Usually not. Bessemer says efficiency scores like this are meaningful above $25M of ARR, and that early-stage companies should focus on burn multiple and the path to free cash flow.

Source: Rule of 40 Calculator

Bessemer's 2024 adaptation: growth rate is multiplied by a factor (about 2 for late-stage private companies) and added to FCF margin. The idea is that over the long run growth contributes more to value than profitability does.

Source: Rule of 40 Calculator

Take starting MRR, add expansion from existing customers, subtract contraction and churned MRR, then divide by starting MRR. 500k starting, 15k expansion, 8k contraction and 15k churn: (500 + 15 − 8 − 15) ÷ 500 = 98.4%. New customers are left out.

Source: NRR & GRR Calculator

NRR counts expansion; GRR doesn't. So GRR can never exceed 100% and measures only losses. NRR shows whether the existing base grew on a net basis, expansion included.

Source: NRR & GRR Calculator

Expansion from existing customers outweighs churn and contraction. Your recurring revenue grows even if you win no new customers, and new sales add on top.

Source: NRR & GRR Calculator

Raise the monthly rate to the twelfth power: 101% a month is about 112.7% a year. This assumes the same rate repeats every month. The most accurate annual figure comes from comparing last year's customer cohort's MRR then and now.

Source: NRR & GRR Calculator

NRR measures only the health of the existing base. Include new customers and strong sales can hide weak retention. This tool shows new MRR only in the bridge and in ending MRR.

Source: NRR & GRR Calculator

There is no single right ROAS. The minimum is your break-even ROAS: 1 ÷ contribution margin. With a 30% contribution margin, anything below 3.33× loses money. Profitable growth needs a ROAS above that, one that protects your target margin — the tool calculates that too.

Source: ROAS Calculator

First find what each sale leaves before ads: gross margin minus variable costs such as shipping and fees. Break-even ROAS is the inverse of that ratio. With a 45% gross margin and 15% variable costs, contribution is 30% and break-even ROAS is 1 ÷ 0.30 = 3.33×. If you track revenue including VAT, scale it up by the VAT rate.

Source: ROAS Calculator

ROAS measures revenue per unit of ad spend; POAS measures profit (here, contribution before ads). A POAS above 1 means ads pay for themselves in profit. When one campaign sells products with very different margins, POAS is the better guide.

Source: ROAS Calculator

Profit should be calculated on revenue excluding VAT, because the tax isn't yours. If your ad dashboard reports VAT-inclusive values, that's fine — just compare VAT-inclusive ROAS with a VAT-inclusive break-even ROAS. The tool puts both on the same basis.

Source: ROAS Calculator

Three common reasons: the break-even bar is higher than assumed (shipping, fees and returns were left out), the platform over-credits itself (counting orders that would have happened anyway), or fixed costs outside advertising consume the contribution. This tool fixes the first; attribution needs controlled tests and fixed costs need a break-even analysis.

Source: ROAS Calculator

Conversion rate is the number of people who complete the target action divided by the number who reached that step, times 100. If 1,600 of 20,000 visitors sign up, the sign-up conversion rate is 8%. For the whole funnel, divide people at the last step by people at the first.

Source: Conversion Funnel Calculator

There is no single meaningful number; it varies widely with industry, price, traffic source and what counts as a conversion. The most useful comparison is your own history: the same step, same channel, last month and last year. If you borrow an outside average, make sure its step definition matches yours.

Source: Conversion Funnel Calculator

Usually the one with the lowest rate, where most people drop off. Relative improvements have the same effect at every step, but a low-rate step is usually easier to improve. The final call depends on the cost of the fix and how confident you are in it.

Source: Conversion Funnel Calculator

Funnel analysis shows where users drop between steps; cohort analysis shows how groups who joined in the same period behave over time. A funnel answers 'where do we lose them?', a cohort answers 'do they stay?'. They're most useful together.

Source: Conversion Funnel Calculator

They're different things. Going from 8% to 10% is a 2-point gain but a 25% relative increase. State which one you mean when reporting experiment results; this tool lets you try both.

Source: Conversion Funnel Calculator

CAGR (compound annual growth rate) is the constant yearly rate at which a value would have grown from start to end. Formula: (End ÷ Start)^(1 ÷ years) − 1. Revenue that went from 4 million to 9 million in 3 years has a CAGR of about 31%.

Source: CAGR Calculator

A simple average adds up the yearly growth rates and divides by the number of years, ignoring compounding. A value that grows 50% and then falls 50% has a simple average of 0%, yet it actually lost 25%. CAGR accounts for compounding, so it reflects the true path from start to end.

Source: CAGR Calculator

You can, but read it with care. Annualising six months of growth turns small differences into very large rates, and seasonality distorts the result. For short periods, reporting monthly growth or total growth is more honest.

Source: CAGR Calculator

Switch the calculator to "Target" mode and enter today's value, the target and the period. The result is the constant annual growth rate needed to get there. Comparing it with your historical CAGR quickly shows whether the plan is realistic.

Source: CAGR Calculator

It is right for nominal growth, but under high inflation a large part of the growth comes from price increases. To see real growth, run the same figures through the Real Growth Calculator or compare them in US dollars.

Source: CAGR Calculator

If the same CAGR continues, the time to double is ln 2 ÷ ln(1 + CAGR). For a quick mental estimate, the commonly cited rule of thumb is the "rule of 72": divide 72 by the growth rate in percent. The calculator uses the exact formula.

Source: CAGR Calculator

Divide fixed costs by unit contribution margin, which is price minus unit variable cost. With 15,000 in monthly fixed costs, a price of 50 and variable cost of 30, unit contribution is 20 and break-even is 15,000 ÷ 20 = 750 units.

Source: Break-Even Point Calculator

Fixed costs are paid every month regardless of volume: rent, salaries, software subscriptions. Variable costs rise with each sale: product cost, shipping, payment fees, sales commission. If you're unsure, ask whether the cost would halve if sales halved.

Source: Break-Even Point Calculator

Divide fixed costs by the contribution margin ratio. With a 40% ratio, 15,000 in fixed costs needs 15,000 ÷ 0.40 = 37,500 in revenue. For businesses selling many products, revenue-based break-even is usually more practical.

Source: Break-Even Point Calculator

It's how far current sales exceed break-even sales, as a percentage. If you sell 900 units and break even at 750, your margin of safety is 16.7%: a drop larger than that puts you in the red.

Source: Break-Even Point Calculator

Three ways: raise price, lower unit variable cost or cut fixed costs. The lever table in the calculator compares how much the same improvement in each would lower the bar, so you can see where to start.

Source: Break-Even Point Calculator

Subtract cost from price, divide by price and multiply by 100. If a product costs 60 and sells for 100 excluding VAT, profit is 40 and margin is 40 ÷ 100 = 40%.

Source: Profit Margin Calculator

Margin divides profit by price; markup divides it by cost. The same 40 profit is a 40% margin on a price of 100 and a 66.7% markup on a cost of 60. Margin can never reach 100%; markup has no ceiling. A 100% markup equals a 50% margin.

Source: Profit Margin Calculator

No. Adding 30% to cost is a 30% markup, which equals roughly a 23.1% margin. For a 30% margin, price at cost ÷ 0.70 — 142.86 for a product that costs 100.

Source: Profit Margin Calculator

Without. VAT belongs to the tax authority, not the seller. If you know the VAT-inclusive price, divide by (1 + VAT rate) to get the net price first; the tool does this for you.

Source: Profit Margin Calculator

With cost-based pricing: cost ÷ (1 − target margin). For a cost of 60 and a 35% target margin, the price excluding VAT is 92.31; with 20% VAT it's 110.77. Treat this as a floor and weigh the final price against perceived value and competitors.

Source: Profit Margin Calculator

They are the three parts of a revenue change. The volume effect is the revenue impact of the change in total units sold, the price effect that of changes in unit prices, and the mix effect that of a shift in the share of units across products. In this tool the three add up to the revenue change exactly.

Source: Price or Volume? Calculator

When the share of sales moves to lower-priced products. Even if total units stay flat and no price changes, revenue falls because the average unit price falls. For example, if units of the expensive product fall while units of the cheap one rise, mix is negative.

Source: Price or Volume? Calculator

The three effects still add up to the same total, but the split between them changes. For example, measure the price effect with period-1 units and the cross term between price and volume moves to another line. This tool uses the order shown above and writes the formulas on the page; use the same order when you compare periods.

Source: Price or Volume? Calculator

Put 0 in period-1 units for a new product, and 0 in period-2 units for a discontinued one. Because a new product's period-1 price was not observed, the tool uses its period-2 price, so its revenue is booked to volume and mix rather than price.

Source: Price or Volume? Calculator

This tool does not separate it; the prices you enter are nominal. If the price effect is positive, part of it may reflect general price increases. For inflation-adjusted growth, use the Real Growth Calculator.

Source: Price or Volume? Calculator