> For the complete documentation index, see [llms.txt](https://handbook.opencoreventures.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://handbook.opencoreventures.com/startup-manual/gtm/growth/growth-metrics.md). # Growth metrics Weekly active users (WAU) and revenue will always be your north star metrics. In order to understand what's actually driving them and whether they're healthy, you need to break them into three layers: 1. **Unit economics:** whether each customer is worth what it costs to acquire and serve them. 2. **Revenue:** how much you're actually making (MRR, ARR, gross margin). 3. **Retention:** whether your existing customers are growing or shrinking your revenue over time (NDR/NRR). ## Unit economics Unit economics measures whether a single customer generates more value than it costs to acquire and serve. WAU and revenue can climb every week while you lose money on every customer you add, and unit economics is what surfaces that before it becomes a runway problem. Unit economics are commonly measured via four main metrics: 1. **Acquisition costs:** what it actually costs to win a paying customer, by channel. 2. **Margin:** how much of their revenue is actually yours to keep. 3. **Payback:** how fast you recover what you spent, in real dollars. 4. **Lifetime value:** what a customer is worth over time, and for how long you can trust that number. ### Customer Acquisition Cost (CAC) Customer acquisition cost (CAC) is how much it costs you to acquire a new users. It’s calculated as total paid acquisition spend divided by the number of new paid customers acquired in the same period. It's the starting point for every paid channel decision. {% hint style="info" %} CAC = Total spend ÷ New paid customers acquired {% endhint %} If a company spends $10,000 on marketing and sales efforts in a given period and acquires 100 new customers during that time, the CAC would be: $10,000 / 100 = $100 It's important to track and analyze CAC to ensure that it aligns with the lifetime value of the customers. If the cost of acquiring customers exceeds their lifetime value, it may indicate an unsustainable business model. #### Common CAC calculation mistakes to avoid 1. **Counting trial starts, not paid conversions.** A trial that never converts is a cost, not an acquisition. For open core products, this extends to free-tier and self-hosted signups. Track paid conversion as its own funnel stage. 2. **Ignoring payment failures.** A meaningful percentage of "converted" trials will fail on card decline, expiry, and users who are never going to pay. If your billing system marks conversion before payment clears, your conversion rate is overstated and your real CAC is higher than you think. Audit this before treating trial-to-paid conversion as a reliable number. 3. **Blending CAC across channels.** Blended CAC hides the fact that some channels may be profitable while others are deeply negative. Track attribution and calculate CAC per channel before scaling any of them. ### Payback period The payback period is how long it takes to recover CAC from the gross profit a customer generates. It is the most important unit economic for evaluating whether paid acquisition is viable and how aggressively to scale it. {% hint style="info" %} Payback Period = CAC ÷ (Monthly Revenue per Customer × Gross Margin %) {% endhint %} The payback period determines how much runway paid acquisition consumes before it returns value. If payback is 8 months and you have 12 months of runway, you have limited room to scale. If payback is 12 months and runway is 12 months, scaling paid puts the company at risk even if the unit economics are otherwise sound. **The most common mistake is calculating payback on revenue instead of gross profit.** At low margins the difference is significant. A payback period that looks like 4 months on a revenue basis can be 2+ years once gross margin is applied. ### Lifetime Value (LTV) Lifetime value (LTV) is the total gross profit you expect to generate from a customer over their lifetime. It helps businesses understand the long-term value of acquiring and retaining customers, and it tells you the ceiling on what you can rationally spend to acquire a customer. {% hint style="info" %} LTV = (Monthly Revenue per Customer × Gross Margin %) ÷ Monthly Churn Rate {% endhint %} The average revenue per customer is the average amount of revenue a customer generates for the business in a given period, such as a year. The customer lifespan is the average duration a customer remains engaged with the business. For example, let's say a subscription-based SaaS company has an average revenue per customer of $100 per month, and the average customer remains subscribed for 24 months. The Customer Lifetime Value would be $2,400. #### Calculating LTV from Churn Rate The revenue per customer is the average amount of revenue a customer generates for the business in a given period, such as a month or a year. The churn rate represents the percentage of customers who stop using the product or service during a specific time period. {% hint style="info" %} LTV = Revenue per Customer ÷ Churn Rate {% endhint %} For example, if the revenue per customer is $100 per month and the churn rate is 10%, the LTV would be $1,000. #### Common LTV calculation mistakes to avoid 1. **Using NRR instead of cohort retention.** Net revenue retention (NRR) above 100% looks healthy but can be driven entirely by a small number of high-expansion accounts mathematically offsetting high churn everywhere else. If a narrow cohort of power users is expanding aggressively, NRR will look strong while the majority of customers are churning. Segment your LTV calculation by acquisition channel and user profile. If LTV varies significantly by segment, a blended number is not meaningful and may be actively misleading. 2. **Extrapolating from young cohorts.** If your oldest paying cohort is 3 months old, you have 3-month LTV data, not 12-month. Don't project forward without evidence. Early cohorts consistently overstate long-run retention because your most engaged users are disproportionately represented at the start. 3. **Not capping the estimate at your data horizon.** The further out your LTV projection, the less reliable it is. Cap your LTV estimate at the time period you have actual retention data for, and label it clearly. ### LTV:CAC ratio The LTV/CAC ratio is a crucial metric for SaaS businesses. It measures the relationship between the customer lifetime value and the customer acquisition cost. This ratio helps determine the long-term profitability of acquiring customers. To calculate the LTV/CAC ratio, divide LTV by CAC. {% hint style="info" %} LTV/CAC Ratio = LTV ÷ CAC {% endhint %} **The standard benchmark is LTV:CAC ≥ 3:1,** indicating a strong return on investment in customer acquisition. A ratio below 1:1 means every customer you acquire is destroying value on a unit basis. A high LTV/CAC ratio indicates that the lifetime value of a customer exceeds the cost of acquiring that customer. This is a positive sign as it suggests that the business is generating more revenue from customers over their lifetime than it spends to acquire them. On the other hand, a low LTV/CAC ratio indicates that the cost of acquiring customers is higher than the value they generate over their lifetime. This can be a warning sign as it may lead to unsustainable business growth. The ratio is only as reliable as its inputs. A model showing 3:1 built on assumed conversion rates, assumed retention, and not-yet-realized margins is a hypothesis, not a validated number. Treat it as one until real cohort data confirms it. ### Scaling spend Once unit economics are validated, the constraint on scaling is payback period relative to runway. Before increasing spend materially: 1. **Confirm CAC is stable as spend increases.** CAC typically rises as you exhaust your best-performing audiences. A CAC that looked good at one spend level may look very different at 5x that level. 2. **Confirm LTV holds in newer cohorts.** Early cohorts are often not representative of the broader market you reach through paid at scale. 3. **Track new paid users vs. churned paid users each month.** If churn is absorbing most of your new acquisition, you're running to stand still. More spend won't fix this — it will accelerate it. ## Revenue metrics Revenue metrics measure how much you're actually making but the standard definitions get corrupted easily, and can overstate the business. ### Monthly recurring revenue (MRR) Monthly recurring revenue (MRR) should reflect payments that have actually cleared; exclude all trials, pending charges, and unpaid invoices. {% hint style="info" %} MRR Definition = Sum of recurring revenue from active, successfully-paid subscriptions {% endhint %} Stripe's default MRR report can include trialing or unconfirmed subscriptions depending on configuration; override it to count successful payments only, and decide once whether you're reporting gross or net of discounts. Handle these consistently: 1. **Trials:** not MRR until conversion and successful payment. 2. **Failed charges:** excluded until payment clears, not counted at the point of attempted charge. 3. **Refunds:** backed out of the period they were refunded in, not restated into the original sale period. ### Annual Recurring Revenue (ARR) Annual recurring revenue (ARR) is only meaningful when it reflects contracted, durable revenue: annual contracts, or monthly revenue you have real reason to expect will persist. {% hint style="info" %} ARR = MRR x 12 {% endhint %} Early on, MRR × 12 is often just an annualized snapshot of a small and volatile base, not a forecast. Report ARR once you have enough contract-length or retention data to back it; before that, MRR is the more honest number. ### Gross margin Gross margin is the percentage of revenue left after the direct costs of delivering your product (COGS). For software businesses, this is primarily hosting and infrastructure. For AI products, inference costs are often the dominant variable. It's calculated as revenue minus COGS, divided by revenue. {% hint style="info" %} Gross Margin % = (Revenue − COGS) ÷ Revenue {% endhint %} Gross margin determines how much of each dollar of revenue is actually available to recover CAC and build a viable business. A customer paying $100/month at 10% gross margin generates $10 in gross profit. The same customer at 50% gross margin generates $50. #### Common gross margin calculation mistakes to avoid 1. **Using a target margin.** If you're optimizing infrastructure or renegotiating rates, your margin is improving but unit economics are a present-tense measure. Don't scale spend against a margin you haven't hit yet. Always use current margin figures. 2. **Running paid acquisition <30% gross margin.** This is usually structurally unviable. There isn't enough gross profit per customer to recover CAC in a reasonable window. Fix margin before you fix spend. ## Retention metrics Retention measures whether the customers and revenue you already have are growing or shrinking, independent of new acquisition. It's a different signal from unit economics: you can have great LTV:CAC on new customers while your existing base is churning over time. ### Customer Retention Rate (CRR) Customer retention rate (CRR) is the percent of customers you retain over a period of time. It's also called Gross Logo Retention. A good annual CRR target is 90%. {% hint style="info" %} CRR = (# of Customers at End of Period - # of New Customers Acquired During the Period) ÷ # of Customers at the Start of Period x 100 {% endhint %} The Customer Churn Rate is 1 - Customer Retention Rate. ### Net Dollar Retention (NDR / NRR) Net dollar retention measures what happens to a fixed cohort of existing customers' revenue over a period, with no new logos included. It's calculated as revenue plus expansions (upsells, seat growth, usage growth) net of contraction (downgrades) and churn (lost accounts entirely). It's the cleanest read on whether your product is deepening its hold on the customers who already have it. {% hint style="info" %} NDR = (Starting Revenue + Expansion − Contraction − Churn) ÷ Starting Revenue {% endhint %} NDR above 100% means the existing customer base alone, with zero new customers acquired, is generating more revenue at the end of the period than at the start. Structurally, that changes what growth depends on: 1. **Growth becomes less dependent on new-logo acquisition.** A company with 115% NDR is compounding revenue from its installed base every period, on top of whatever new customers CAC-driven acquisition brings in. The two effects stack rather than being the only source of growth. 2. **It raises the ceiling on how much CAC you can rationally spend**, since new customers are now expected to expand over time rather than simply renew flat, which feeds directly into a higher LTV. 3. **It compounds.** A cohort acquired this year that nets 110% NDR annually is worth meaningfully more by year three than the same cohort at 100% flat retention — this is part of why early-cohort extrapolation (see LTV, above) has to be checked against realized, not assumed, expansion. NDR below 100% means the opposite: the business is on a treadmill where new acquisition has to outrun the erosion of the existing base just to stay flat, which is a materially harder position to grow from and worth surfacing before it shows up as a growth-rate problem. ### Gross Revenue Retention (GRR) Gross revenue retention (GRR) is the same cohort calculation as NDR with expansion stripped out. It caps at 100% and only ever measures what you lost. {% hint style="info" %} GRR = (Starting Revenue − Contraction − Churn) ÷ Starting Revenue {% endhint %} This is the metric to check whenever NDR looks strong, because NDR can hit 110% on a base that's losing 30% of its revenue to churn every year, so long as a handful of accounts are expanding hard enough to cover it. GRR can't hide that: a business with 110% NDR and 70% GRR has a serious churn problem wearing a healthy top-line number, while 110% NDR and 95% GRR reflects a genuinely sticky base with real expansion on top. **As a rule of thumb, GRR below \~90% is worth investigating regardless of what NDR shows.** Report the two together; NDR alone is an incomplete picture, and it's the gap between NDR and GRR that tells you how much of your retention story is expansion versus not losing customers in the first place. ### Revenue Retention vs. User Retention Revenue retention and user (logo) retention measure different things and often diverge. A company can lose a substantial share of its logos (low CRR) while NDR stays strong, if the accounts that remain are expanding enough in revenue to more than cover the ones that left. The reverse also happens: high logo retention with weak or negative NDR, if customers stay but downgrade. This divergence is especially common in usage-based or seat-based pricing, where a shrinking logo count from consolidating smaller accounts can coexist with a growing dollar base from expanding enterprise ones. Track both. A strong NDR doesn't mean logo churn isn't a problem, and a strong CRR doesn't mean revenue is actually growing. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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