Growth
Growth is single most important factor in determining whether, how quickly, and on what terms companies can fundraise.
OCV companies have ~9-12 months to show meaningful traction. If a company struggles to gain traction, we may wind it down. Growth is shown through usage and revenue metrics. Investors want to see an obvious demand for a commercial product. For an enterprise company, meaningful growth could be a handful of logos at a few hundred thousand in annual recurring revenue (ARR).
Early-stage startups operate on a weekly growth cadence: week-over-week (WoW) growth goals and product deliverables. That’s why OCV meets with Pre-Seed companies weekly.
The most successful founders drive growth efforts in the early stages. Investors will want to know that you've figured out growth and have a deep understanding of your growth channels. Understanding your growth channels means you know where to spend to grow more.
Growth goals
Pre-seed company KPIs should be either usage-based or revenue-based growth, reported weekly. Most companies start by tracking weekly active users (WAU), and revenue becomes the primary metric once you have a first paying user. 10% WoW growth from a reasonable baseline is the bare minimum growth rate. Growth below 10% is an immediate signal to make changes and place new bets to get growth above 10% the following week.
Goals are always binary, measurable, and ambitious. Production-based goals (“Release this feature” or “Write this blog post”) are important inputs that help you achieve your goals, but are not goals themselves.
Growth rate
Growth is measured by growth rate, which is typically the ratio of new users/customers to existing ones.
Growth Rate = [(Present Value - Initial Value) / Initial Value] x 100
Early growth numbers can be misleading. In your first few weeks, percentage growth should look astronomical because you're starting from nearly nothing.
Growing from 1 user to 11 users is 1,000% growth.
Growing from 1,000 users to 1,100 users is 10% growth.
The second scenario has a much lower growth rate but adds a lot more users.
Target extremely high WoW growth in the first few weeks until you've established a baseline of 1,000 users. Then you can start tracking toward 10% WoW growth.
Growth rate examples: Low-baseline growth versus rapid early growth
Scenario 1: ~10% WoW growth from a low baseline Starting from 5 users and growing at a steady 10–12% each week looks healthy on paper, but the compounding effect is slow to show up when your base is small. By week 10 you have 15 users. The growth rate is right; the baseline is the problem. This is why getting to your first real users fast matters.
Scenario 2: Rapid early growth Starting from the same 5 users, aggressive early acquisition (500%+ WoW in the first weeks) builds the base quickly. By week 10 you have 858 users.
The takeaway Early-stage growth rate is less meaningful than the baseline it's applied to. Your goal in the first month is to acquire users as aggressively as possible and then aim for 10% WoW growth.
Weekly active users (WAU)
Weekly active users (WAU) is your top-level metric that tracks the number of people who interacted with your product each week. How you define an "interaction" should be as simple as possible—someone who logged in or took an action in the product. The definition of this metric should never change. Tracking WoW growth is only meaningful when the definition is consistent.
Weekly active users is a helpful, high-level growth metric that you will report on at every office hour. However, founders should be looking under-the-hood metrics to understand the health of this metric and what's driving it. Engagement and retention metrics add color and insight into what's driving aggregate WAU growth. Engagement metrics tell you how users are behaving in the product and retention metrics tell you if they are getting real value.
You should quickly familiarize yourself with some concepts that will help you get deeper visibility into what's driving growth: user activation, cohort retention analysis, and user segmentation. The video from YC partner David Lee is the clearest explanation we've found of how retention works under the hood, and why it's the primary driver of sustainable WAU growth.
User activation
User activation is a helpful concept for understanding your product onboarding funnel. Founders need to make a judgement call on how to define onboarding and what completion looks like. You want to define onboarding completion as a step or action that user completes whereby there's a high likelihood that user will stick around. That action is your activation milestone.
An activation milestone is the behavior that most reliably predicts retention. Finding it requires looking at your retained users and asking: what did they do that churned users didn't?
A peer-to-peer payment app might consider activation when someone links a debit card or sends their first dollar. Or they define activation as sending two transactions because there's a large drop-off after the first. So their milestone is two transactions, and the entire onboarding funnel is built around getting users there. Mint's internal concept of "time to pie" found that once a user saw a pie chart of their spending by category, they were very likely to be retained. Everything before that moment (signing up, connecting financial accounts, etc.) counted as an interaction, but didn't predict retention the way that single moment did. So they defined activation around it and treated reducing time to pie as a core product initiative.
A special form of activation is converting to a paid user. Founders often track their paid conversion rate as well as their activation rate.
Activation rate is the percentage of new users who reach your activation milestone. Once you've defined the milestone, your onboarding funnel exists to get users there as fast as possible, and activation rate tells you how well it's working.
The milestone doesn't have to be complicated. The right milestone is whatever behavior most reliably predicts that a user will stick around.
Cohort retention analysis
Watch David Lieb's video on Cohort Retention.
User retention is the most honest signal of whether your product has value. Cohort analysis is how you measure it. A cohort is a group of users defined by when they first used your product. Cohort analysis tracks how many users from each group return in subsequent weeks. The simplest starting point is tracking new versus returning users each week, and doing the same for activated users specifically.
A cohort analysis that blends all users together can hide what's actually driving or dragging retention. Cutting users in different ways reveals which segments retain well, which don't, and why.
Segment your cohort analysis by acquisition channel to see which channels are producing durable users and which are inflating WAU without contributing to your retained base (this requires tracking attribution). A growing WAU number driven by paid acquisition can look healthy until those users are isolated and found to churn at twice the rate of organic users. If paid marketing is assumed to be profitable based on average life time value (LTV) across all users, but the LTV of paid users is significantly lower than organic, that spend may not be profitable at all.
Other useful dimensions to cut by:
Acquisition channel: paid, organic, referral, direct
Cohort timing: comparing older cohorts to newer ones tells you whether product improvements are actually moving retention
User profile: company size, industry, or role for B2B; demographic or geography for consumer
Device or platform: particularly relevant if your product experience varies by surface
Free versus paying users: paid and free users behave differently, and blending them hides both; segmenting by paid versus free shows whether paying customers are actually engaging with the product, and when they're most likely to churn
When a segment retains well while others drag the overall number down, it usually means one of two things: the product is a strong fit for that segment and a weak fit for others, or onboarding works better for one type of user. Either way, it points to where to focus, whether that's doubling down on a channel, tightening acquisition targeting, or fixing a specific onboarding gap.
Carrying capacity
Improving retention moves the growth curve, but how far your growth can actually go depends on how many new users you're adding, and whether that number is growing.
Carrying capacity tells you how many users your current growth engine can sustain at steady state.
Carrying capacity = users added during a period ÷ % of userbase that churns during the period
If you're losing a fixed percentage of your user base every period, you need a constant stream of new users just to hold steady. At some point, those two forces balance out: the number of users you're gaining equals the number you're losing. That equilibrium is your carrying capacity.
Carrying capacity example: If each week you are,
Adding 5 new users
Losing 5% of your base
Ceiling = 100 users
If you add 10 new users per week at the same churn rate, and the ceiling doubles to 200. The ceiling isn't fixed but it's predictable, given a constant acquisition rate and a constant churn rate.
However, the math only applies when new user acquisition is linear, meaning you're adding roughly the same number of new users every period. If that's the case, you will eventually hit your ceiling no matter how good your retention is. The only way to avoid a hard ceiling is to grow acquisition as a percentage, not just in absolute terms.
If you're adding 10% more users every week than the week before, your acquisition is compounding along with your base, and a fixed carrying capacity doesn't really apply. This is the mechanic behind the 10% WoW growth target: week-over-week percentage growth keeps your acquisition expanding in proportion to your base, which is what prevents you from flatlining.
There are two levers to raise your carrying capacity:
Reduce churn
Increase new user acquisition
If you're adding the same number of users every week and growth is slowing, that's not a signal to double down on the same acquisition channel. It's a signal to evaluate whether you're approaching equilibrium, and whether the right move is to find a new lever, improve retention, or both.
Later-stage growth benchmarks
As companies progress to later stages, there are a few other well-known benchmarks you may hear about.
Triple Triple Double Double (T2D3)
This is a growth benchmark for early-stage companies to go from $1-2M in ARR (typically Series A stage) to $100M+ ARR in 5-6 years. So if you start at $2M ARR, you'd go: $2M → $6M → $18M → $36M → $72M → $144M
The Rule of 40
This is an efficiency benchmark that's more relevant once you're at scale (typically $50M+ ARR, though people debate the threshold). It says your growth rate + profit margin should exceed 40%. For example: 30% growth + 15% margin = 45%, good.
Burn multiple
This is an efficiency benchmark that tells you how many dollars you're burning to generate each dollar of new ARR. Lower is better, but the expectations are different at each stage of the company. Read David Sacks' substack article if you want to know more.
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