Understanding Unit Economics: The Key to Startup Success and Funding

May 5

In today’s startup landscape, unit economics has become a watchword for survival and success. At its core, unit economics means understanding your business at the most granular level – how much profit (or loss) you make per “unit” of product or per customer. In simple terms, if you sell a product for $100 and it costs $70 to produce and deliver that product, you earn $30 in gross profit per unit. But if you had to spend another $40 on marketing to acquire that customer, then in total you lost $10 on that sale – a sign of problematic unit economics. Founders who grasp these fundamentals avoid being the butt of the classic startup joke: “we lose a little money on every customer, but we make it up on volume”. Instead, they focus on making more money per customer than it costs to acquire and serve that customer, ensuring each sale contributes to the company’s long-term viability. In this article, we’ll explore what unit economics means, why it’s critical for startup success, how top venture firms evaluate these metrics at different stages, and how considerations vary between SaaS and hard tech companies.

What Are Unit Economics and Why Do They Matter?

Unit economics refers to the revenue and costs associated with a single unit of product or one customer. For a SaaS startup, a “unit” might be one subscriber or user; for an e-commerce company, it could be one order; for a hardware company, one device sold. By breaking your business down to the per-unit level, you can tell if you’re fundamentally profitable (i.e. if each incremental customer adds value or drains resources). Positive unit economics means you earn more from a customer over time than it costs to acquire and serve that customer. Negative unit economics means you’re losing money on each unit sold, which is unsustainable in the long run (you can’t rely on “making it up in volume” if volume just multiplies losses!).

VC investors care deeply about these metrics because they signal whether scaling up will create value or just accelerate losses. As Sequoia Capital has noted, “positive unit economics require careful attention to the fundamental financial building blocks of the business”. In other words, figuring out your per-unit profit is as important as finding product-market fit. It’s one of the core pillars of a sustainable company. Andreessen Horowitz (a16z) emphasizes that solid unit economics have a “cascading effect”: when each customer is profitable, you generate more cash to reinvest in growth, leading to a healthier business and a higher valuation. Investors ultimately value companies based on future cash flows, so startups with higher margins and efficient customer acquisition can justify higher valuations. For example, many early stage investors, including a16z, often use a 3X LTV:CAC ratio (lifetime value to customer acquisition cost) as a “rough benchmark” of health - if each customer’s lifetime value is at least 3 times the cost to acquire them, the company is likely on solid footing. We have shown an analysis of these metrics on Ventures Edge here.

Beyond valuations, good unit economics are critical to a startup’s survival and eventual enterprise profitability. They indicate you have a viable business model, not just a flashy product. As Y Combinator’s Sam Altman quipped, Silicon Valley is willing to fund money-losing companies in the short run if they “make more than [they] spend on each user” and things “get better not worse as you get bigger”. But even the most growth-friendly investors have little appetite for a model that will “probably always lose money”. In the late 2010s and early 2020s, a lot of startups chased growth while glossing over dismal unit economics, often explaining it away with the hope that growth would fix all. Many of those narratives didn’t pan out. Most great companies, even if unprofitable overall in early years, showed good unit economics soon after they began monetizing.

In short, unit economics are a reality check: if you can’t outline a path to profitability per customer or per product, you may be in a “bad business” that growth alone won’t fix.

Investor Perspectives: What Top VCs Say About Unit Economics

Leading North American VC firms have been increasingly vocal about the importance of unit economics. Here are a few perspectives and quotes from prominent investors and funds:

Andreessen Horowitz (a16z) – In recent market commentary, a16z has stressed a shift from “growth at all costs” to sustainable growth. In a 2023 guide for founders raising capital, their team noted that during the ZERP era investors rewarded rapid user growth “even at the cost of poor unit economics and profitability.” But today “the ‘growth at all costs’ mantra has come to an end”, and investors are putting more weight on profitability. If your “unit economics are in the red” (i.e. negative profit), a16z advises “prioritizing efforts to improve [them]… even if it means achieving lower growth in the present”. The message is clear: in the long run, growth is only good if it’s not fundamentally undermining the business. Conversely, efficient growth can be a major advantage. A16z highlights metrics like CAC (Customer Acquisition Cost) payback and distinguishes between “blended CAC” (including organic customers) and “paid CAC” (from marketing spend). They note that paid CAC is critical for evaluating viability because it shows whether you can “scale up user acquisition profitably” – if you can pay for ads and still make money per user, you have a scalable model.
Sequoia Capital – Sequoia has long advocated for strong unit economics as a foundation of enduring companies. One of Sequoia’s startup guides states that for a product to succeed long-term you need product-market fit and positive unit economics as well as scalability. In mid-2022, amid economic uncertainty, Sequoia released a memo titled “Adapting to Endure” urging startups to pursue “sustainable, profitable growth” rather than reckless expansion. They encouraged founders to “improve unit economics” by “boosting revenue per customer while trimming acquisition costs”, proclaiming that “efficiency is the new black”. This reflects a broader industry pivot: investors want to see startups doing more with less and focusing on high-ROI activities at the earliest stages. Sequoia emphasizes understanding the fundamental economics - CAC, LTV, and overall profitability - behind a startup’s business model. It’s not enough to have a great product; you must show that serving each customer can be profitable in a reasonable time frame.
Bessemer Venture Partners (BVP) – Bessemer, known for its Cloud Index and investment in SaaS companies, has published benchmarks illustrating what “good” unit economics look like, especially for SaaS startups. In their 2023 State of the Cloud report, Bessemer notes that “unit economics are finally more in vogue” again as the market has shifted to prioritizing efficiency. They urge founders to ask tough questions like, “Is your sales and marketing spend filling a leaky bucket?” - in other words, are you retaining customers and recouping acquisition costs, or are you losing customers as fast as you acquire them? Bessemer provides specific “good, better, best” benchmarks for SaaS companies to aim for. For example: CAC payback (the time to earn back what you spent to get a customer) should be 12-18 months (good), 6-12 months (better), or under 6 months (best). They also look for high gross margins and net revenue retention (customers expanding usage over time). A healthy net revenue retention above 100% - meaning customers on average spend more each year than the last – is a strong positive signal (120%+ is “best” in their book). Bessemer even devised an “Efficiency Score” (Net New ARR / Net Burn) to measure how much new revenue a company generates per dollar it burns. The takeaway is that top VCs like Bessemer now expect startups, even relatively early, to demonstrate efficiency and the ability to turn investment into revenue effectively. As BVP puts it, the industry has moved from the age of growth-at-all-costs to the “age of efficiency”, and companies that want to raise money on good terms need to show strong unit economics and fiscal discipline.

In summary, leading investors across the board are doubling down on unit economics. Good unit economics instill confidence that a startup isn’t just buying growth with borrowed time. They indicate that the business model works and additional funding will be poured into a financial engine that can eventually produce profits. On the flip side, if your unit economics are poor (e.g. low margins, high customer acquisition costs, weak customer lifetime value), savvy VCs will dig in deep during due diligence - and possibly pass on the investment. As one founder-focused publication noted, “the strength of your unit economics will be one of the key competitive advantages in a venture market that many predict will toughen”. For founders, the message is: know your numbers. Be prepared to discuss and defend how much it costs to get a customer, how much that customer will spend, how long they’ll stay, and how those figures will improve as you scale. If you can’t answer these, it’s a red flag to investors.

Unit Economics at Different Stages: From Pre-Seed to Growth

Unit economics matter at every stage of a startup’s journey, but the way investors evaluate them evolves as your company grows. A pre-seed startup won’t have the same depth of data as a Series B company, yet in each phase VCs will look for appropriate signs that your unit economics either are positive or are trending in the right direction. Let’s break down the expectations and focus at pre-seed, seed, Series A, and growth stages.

Pre-Seed Stage: Story and Potential

At the pre-seed (or angel) stage, startups are often pre-revenue or have minimal revenue. You may not have statistically significant unit economics quite yet - perhaps you’re still building the product or have only a handful of beta users. Investors at this stage (angels, pre-seed funds) know they are betting primarily on the team, vision, and market. However, even without hard numbers, founders should demonstrate a clear understanding of their future economic model. This means articulating: What will you charge? What do you estimate it costs to deliver your service or product? Who is your customer and how will you reach them cost-effectively? A pre-seed investor will look for plausible positive unit economics in the future. For example, if you’re a SaaS company, can you explain how you might acquire users (perhaps through viral growth, low-cost marketing, or product-led growth) and eventually monetizethem at a profit? If you’re building a hardware device, have you thought about manufacturing costs and pricing at scale? At this stage, the unit economics conversation is mostly about potential and assumptions, not proven metrics. Smart founders will bolster this with any early evidence available (maybe a small pilot where it cost $500 to acquire a customer who’s willing to pay $50/month - an indicator that if that customer stays ~1 year, LTV > CAC). The goal is to convince pre-seed investors that “unit economics can work out for this business, and we won’t be stuck in a fundamentally margin-negative model.” If your model inherently requires, say, spending $100 to deliver $50 of value, that’s a problem to address now, not later.

Seed Stage: Early Validation

By the seed stage (typically the first institutional round, often $1-3M raised), investors will expect some tangible signs of unit economics from real market data. You don’t need perfectly tuned metrics - far from it - but you should have initial indicators that each customer can be profitable in time. For many SaaS seed startups, this is when they start tracking things like customer acquisition cost and churn rate on a small scale. For instance, perhaps you’ve acquired 50 paying customers: how did you get them? If mostly through organic means or inexpensive experiments, that’s a good sign. If you had to spend $100k on Google ads to get those 50 customers (i.e. $2,000 CAC each) and each customer pays only $500 a year, that’s a red flag unless you can argue those customers will stay for many years or spend much more over time. Seed investors will ask about gross margins (are you building a high-margin business?). A common expectation for software startups is gross margins in the range of ~60-80% at this stage - it’s understood you might not be fully optimized yet, but if your cost of serving customers is already very high, it requires some explanation. Investors like Sequoia often focus on unit economics drivers even at seed: CAC, LTV, usage frequency, etc., as a way to gauge if there’s a real business behind a product customers love.

Importantly, unit economics at seed are often evaluated qualitatively as much as quantitatively. For example, a seed VC might note: “This company’s early users absolutely love the product (high engagement, low churn so far) and they’re paying for it, which suggests the company is delivering real value. The founder also has a plan to acquire customers via partnerships which could keep CAC low. Gross margins are 70% now with potential to hit 85% as they streamline onboarding and automate more functions. We believe the unit economics will be very strong with more volume.” In contrast, if a seed startup has to give its product away for free or heavily subsidize usage to attract customers (e.g. a marketplace that spends $100 in coupons to get a $50 transaction), investors will worry that the model isn’t economically viable. By the end of seed stage, you ideally want to show at least a path to “positive unit economics” - meaning that with some scale or tweaks, you’ll make money on each customer. Startups that reach “positive unit economics” (making more per customer than they spend to acquire/serve that customer) are essentially proving their business model works, and will be in a much stronger position to raise a Series A.

Series A: Proven Model and Repeatability

Series A is where unit economics really take center stage in investor due diligence as by this stage, your startup likely has notable revenue and customer data . The expectation is that you’ve achieved product-market fit and have a repeatable sales or user acquisition process - now VCs want to see if that process can scale economically. A Series A investor (like a16z, Sequoia, etc.) will dive deep into metrics such as:

Customer Acquisition Cost (CAC) – How much are you spending on sales and marketing per customer acquired? Is this cost stable, growing, or shrinking? For context, many VCs consider a CAC payback period of around 12 months or less to be healthy by Series A (meaning within a year, the revenue from a customer has paid back the cost to acquire them). If your payback is, say, 24+ months, it might be a concern unless your customers stick around for a very long time.
Lifetime Value (LTV) – How much gross profit will an average customer bring in over their lifetime with you? By Series A, you might have some data on annual retention or recurring revenue that lets you project LTV. A partner at a16z wrote that 3X LTV:CAC is a rough benchmark for financial health - it shows efficient returns on marketing spend. At Series A, investors love to see signs that for every $1 you spend, you get $3+ in value back; it implies that pouring in more money (from the VC) can lead to profitable growth.
Gross Margins and Contribution Margin – Investors will scrutinize your gross margin (revenue minus direct costs). High gross margins (70-90% for software) indicate each sale leaves plenty to cover other expenses. If you have a hardware or hybrid business with lower margins, be prepared to explain how you will improve margins (e.g. through scale or additional high-margin services). Some VCs also look at contribution margin per customer (revenue minus all variable costs associated with serving that customer, including customer support, etc.) as a true measure of per-customer profit. By Series A, gross margins should ideally be improving or stable at a solid level - if your margins are eroding as you grow, that’s a red flag.
Retention and Engagement – Keeping customers is as important as acquiring them. Investors will ask: what is your churn rate (the percentage of customers or revenue that you lose each month or year)? What is your net revenue retention (existing customers’ spend this year vs last year)? Strong retention basically increases LTV, making unit economics more favorable.

At Series A, you should be able to present a cohesive story: “It costs us $X to acquire a customer, and in their first year we earn $Y from them at an 80% gross margin. Our churn is low, so over 3 years a customer’s LTV is 5X whatwe spent. Therefore, scaling up marketing will create value. With $10M of new funding, we can acquire 1,000 more customers and expect to generate Z in gross profit from them over time.” This kind of narrative, backed by data, gives Series A investors confidence. In fact, some late seed/Series A investors have hard metrics guidelines: for example, one venture fund noted they like to see annual run-rate revenue around $2–3M, gross margins ~75%, and a plan to reach profitability within 12–24 months of the A round. These aren’t universal numbers, but they illustrate the heightened bar at Series A. Essentially, Series A is about proving unit economics on a small scale and convincing investors that injecting capital will be like fuel on a well-tuned fire – not gasoline poured into a leaking bucket.

Growth Stage (Series B and Beyond): Scaling Efficiently

In growth rounds (Series B, C, and onwards), companies are expected to their unit economics fully honed in and be focusing on efficiency and scale. Growth-stage investors (including late-stage VCs, growth equity, etc.) will compare your metrics against industry benchmarks and public companies. They look for scalability: as you grow revenue, are you maintaining or even improving unit economics? Or are costs rising faster than revenue? Key considerations at this stage include:

Efficiency Metrics and the Rule of 40 – Investors often use composite metrics like the Rule of 40, which says that a company’s growth rate + profit margin (or EBITDA, or FCF) should exceed 40%. This balances growth and profitability. By Series C or later, pursuing growth at the expense of unit economics is heavily discouraged. A16z listed “Don’t pursue growth at the expense of profitability” as a commandment, noting that in recent markets investors have re-centered on profitability and “efficiency is the new black”. Growth investors want to see that you can continue to expand while trending toward profitability, not away from it.
Best-in-Class Unit Economics – As a company matures, the bar rises. Where Series A might have been happy with 3X LTV/CAC, a Series B or C might aim for 5X LTV/CAC or higher. Bessemer’s benchmarks for a “typical Series B/C enterprise SaaS” include CAC payback well under 12 months, net retention 120%+, and other top-tier metrics. By growth stage, investors will compare you to public comps: e.g., if your gross margin is 50% but all the publicly traded companies in your sector have 80% margins, that discrepancy will be probed. You might get away with some inefficiencies in earlier stages, but by Series C-D, your metrics should approach the profile of an eventual IPO-worthy company.
Cohort Economics and Saturation – Growth investors will also consider cohort analyses. Are newer customer cohorts as good or better than earlier ones? Or are you picking the low-hanging fruit and now acquisition is getting tougher (rising CAC, lower LTV)? They will segment your unit economics by customer type, geography, or product to see if scaling is hitting limits. For example, maybe your unit economics are great in one segment but terrible in another - a growth round diligence process will uncover that and ask how you’ll focus on the best cohorts. Bessemer’s advice of asking “Which customer segments will you deprioritize because their unit economics will not work even at scale?” becomes very relevant here. At scale, you must choose your battles and double down where the economics make sense.
Path to Profitability – By late-stage, even if you’re still burning cash overall, investors want to see a clear path to profitability. Often this means showing that if you stopped investing so much in growth (R&D, S&M), the existing customer base and their unit economics would produce a profitable company. Some companies by Series C or D start generating positive operating cash flow or at least demonstrate that new revenue is coming at a very low incremental cost (high contribution margin). If unit economics are strong, then achieving profitability is usually just a matter of scale (covering fixed costs). Growth investors may ask for models showing at what future revenue figure you “break-even” given current unit economics. If that number seems unachievable or far too high, it indicates unit economics might still be too weak.

In summary, as you move through funding stages, the tolerance for unclear or poor unit economics drops sharply. Early on, investors give you leeway to refine the model; by Series A, they expect proof that the model works on a micro level; by Series B and beyond, they expect you to be squeezing maximum efficiency from the model. Founders should anticipate these shifting expectations. A great exercise is to know the typical metrics for companies at the stage you’re targeting - many VC firms publish guides or benchmarks - and honestly assess where you stand. Are you below average on some key metric? If so, be ready to explain why (for instance, maybe you deliberately kept prices low to drive adoption but plan to improve monetization, thus improving LTV). Also, emphasize trends: if your CAC was $100 six months ago and $50 now, that trend can trump the absolute number in investors’ eyes because it shows you’re actively improving unit economics.

As you can see, by the growth stage a startup is held to a high standard on metrics. But the underlying principle is consistent: at every stage, investors want assurance that you’re building an economically sound business. If early on the metrics are imperfect, the trend and fundamentals should indicate that with more time or money, you can hit the targets. Founders should actively manage and track their unit economics over time - not just for investors, but as a feedback loop for the business. For example, if your CAC is creeping up quarter by quarter, you need to investigate why (are you saturating an easy channel? Is competition driving up ad costs?). If your gross margins are lower than expected, can you re-negotiate supplier contracts or improve operational efficiency? By treating these numbers as core business health indicators, you’ll make better decisions and also inspire confidence in potential investors with your command of the business.

SaaS vs. Hard Tech: How Unit Economics Differ by Business Model

“Unit economics” is a universal concept, but the specific metrics and considerations can vary greatly between different types of businesses. Perhaps the most stark contrast is between Software-as-a-Service (SaaS) companies and “Hard Tech” companies (which for our purposes includes hardware startups, electronics, robotics, and other businesses with significant manufacturing or R&D costs). Investors will evaluate unit economics in the context of the business model - what’s considered good for a SaaS might be mediocre for a consumer product, and vice versa.

Revenue Model and Margins: SaaS companies typically sell software on a subscription or usage-based model, which means recurring revenue and high gross margins. Once the software is built, the cost of delivering it to one more customer (hosting, support, etc.) is relatively low - so gross margins of 75-90% are common for pure software. Hard tech companies, on the other hand, often sell physical products (devices, hardware units) which have significant cost of goods sold. This yields lower gross margins - a hardware startup might have 30%, 40%, maybe 50% gross margin on each unit sold, because each product has material costs, assembly, shipping, etc. It’s not unusual for hardware or deep tech gross margins to be less than half that of a comparable SaaS business. As VC Jason Lemkin pointed out, many classic SaaS metrics “break if you aren’t really an 80%+ gross margin business”, citing the example that Shopify’s blended gross margin (with its payments hardware/services) is under 50%, whereas pure software tends to be ~80%. Investors adjust expectations accordingly: a hardware startup with 40% gross margin isn’t necessarily bad (it might be normal for that industry), but they will want to see that margin improving over time or supplemented by other revenue streams. Moreover, lower margins mean there’s less room for error in other costs - if you only keep $0.40 of each $1, your customer acquisition and overhead need to be extremely efficient to make a profit.

Customer Acquisition and Sales Cycle: SaaS businesses often rely on online marketing, inside sales, or product-led growth to acquire users relatively quickly. The sales cycle can be short (days or weeks for SMB SaaS, or a few months for enterprise deals), and CAC is closely monitored via digital ad spend, conversion rates, etc. Hard tech companies frequently face longer sales cycles and more complex go-to-market motions. For example, a robotics startup might need to do heavy enterprise sales or pilots before closing a deal, or a consumer hardware robot depending on retail distribution, which has its own costs and margins (retailers taking a cut). This means CAC for hard tech is often tricky: you might spend many months of effort to land a customer, or rely on partnerships and distributors. Additionally, hardware startups sometimes employ strategies like pre-orders or crowdfunding to validate demand. From a unit economics perspective, SaaS CAC is usually expressed per customer acquired, whereas hard tech CAC might be per device sold or per deal and can include costs like channel discounts, trade shows, etc. Investors evaluating a hard tech startup will consider these differences - they might focus on metrics like sales pipeline conversion rates or payback period per customer rather than the purely digital marketing CAC ratios common in SaaS.

Lifetime Value and Recurring Revenue: In SaaS, by definition the goal is to have customers paying continuously (monthly or annually). This means that if you keep churn low, the Lifetime Value (LTV) of a customer can be quite high - a customer might subscribe for 5-10 years, and even increase their subscription over time. This recurring nature is why SaaS businesses are valued highly and why investors love metrics like LTV/CAC and net retention. In contrast, many hard tech or hardware companies are based on one-time sales of a product. If you sell a machine or a device, the customer might not purchase again for several years (if at all). That makes LTV effectively equal to the one-time sale gross profit, unless the company has other revenue streams. To improve economics, many modern hard tech startups try to introduce recurring revenue components: for example, a hardware device might come with a subscription for software updates, maintenance plans, or consumables (think of razor-and-blade models or a drone sold with a monthly data service). This hybrid approach can increase LTV and smooth out revenue, making the business more SaaS-like. Investors will pay attention to what happens after the initial sale: Is there an opportunity to upsell the customer additional services or replacements? What’s the upgrade cycle? If a company sells an electric vehicle battery system, do they get ongoing revenue from maintenance or from battery recycling after 5 years? Hard tech founders need to convince investors that the economics extend beyond a single transaction, or if it truly is mostly one-off sales, that the margins on that one sale are high enough to sustain the business.

Upfront Costs and Capital Intensity: Another difference is capital intensity. Hard tech often requires significant upfront costs per unit (prototypes, manufacturing tooling, inventory) which can distort early unit economics. For example, the first 100 units of a hardware product might cost more to make than the sales price, because the company hasn’t yet optimized manufacturing or achieved volume discounts on components. This is understood by investors, but it must be managed carefully. The true unit economics might only reveal themselves at scale (say, when you produce 10,000 units and can leverage bulk production). Investors will often discuss economies of scale with hard tech founders: “If we fund you to build a factory or contract manufacture at volume, how much does your cost per unit drop?” They want to see a path to healthy unit economics through scale. For instance, maybe at low volume your gross margin is 20%, but at high volume it will be 50% - if that’s demonstrated or at least plausible, investors may accept short-term negative unit economics as a means to an end. In contrast, SaaS businesses usually don’t have this physical scaling issue - their costs per user might even increase slightly with scale (due to more support staff, bigger cloud hosting bills), but generally software benefits from economies of scale on the revenue side (one product can serve many customers). Hard tech companies also tend to use more capital (both VC and non-dilutive) to reach scale. It’s common for hardware startups to raise debt or use pre-order cash to finance inventory, whereas SaaS startups mostly spend on people (R&D, sales) and can adjust burn more flexibly.

In practice, many startups blend elements of both - for instance, a hardware company that also sells software services, or a SaaS company that delivers a physical component (IoT devices, etc.). Investors will dissect each component’s unit economics. A notable point from SaaS investor Jason Lemkin was that “loss-making hardware revenue doesn’t count” when evaluating a SaaS company’s metrics. For example, some SaaS companies (like a payments provider that sells terminals) might sell hardware at a loss to get a software customer. VCs will typically exclude or heavily discount such revenue in their analysis of unit economics, focusing on the profitable portion. This underscores that not all revenue dollars are equal - revenue with poor unit economics (low or negative margin) is not valued as highly as revenue with strong margins. In contrast, a pure hardware startup doesn’t have the luxury of excluding hardware revenue - it is the business - so it must prove that even if margins are lower, the overall model can generate venture-level returns (often through volume and market size).

To summarize, SaaS businesses are generally expected to have faster, more clear-cut unit economics, whereas hard tech startups often have to educate investors on a longer path to profitability per unit. A SaaS founder might talk about how quickly they recoup marketing spend and how expansion revenue boosts customer LTV. A hard tech founder might focus on how they will drive down unit costs by 50% at scale and how each customer will buy multiple units or come back for upgrades, eventually making the upfront CAC worth it. Both need to show a credible model where lifetime profits exceed the costs. The differences in model mean different levers to pull: SaaS can tweak pricing plans, reduce churn via product improvements, or optimize ad spend; hard tech can redesign the product for cheaper production, find cheaper components, or bundle services to increase effective revenue per customer.

From an investor’s perspective, the bar for unit economics is high in both cases, but the timeline and emphasis differ. SaaS startups might be expected to show good unit economics very early (within a year or two of launch) since the feedback cycle is quick. Hard tech startups might be given a bit more runway to prove unit economics (perhaps needing to get through an R&D phase and into initial production). However, no investor will ignore unit economics completely. The bottom line for founders is: know the key metrics in your industry, track them, and be ready to explain how you’ll hit targets that make your business attractive. If you’re a SaaS, be fluent in things like CAC, churn, LTV. If you’re building hardware, know your BOM cost, target gross margin at scale, and how you’ll reach it, as well as any recurring revenue you can generate.

Conclusion: Building an Economically Viable Startup

For startup founders, especially those without a finance background, unit economics might initially sound like an abstract finance term. In reality, it’s a hugely empowering concept. By breaking down your business into per-customer or per-unit costs and revenues, you gain a clear view of how you make money and where you bleed money. This clarity helps you make better strategic decisions - whether it’s adjusting pricing, improving your product to increase retention, or reining in an expensive marketing channel. It also prepares you to face investors with confidence: you can demonstrate that you know your business “inside-out” and have a plan to optimize the right levers.

Leading VC firms from a16z to Sequoia to Bessemer all hammer home the same point: startups live and die by their ability to eventually turn customers into profit. In frothy times, it’s easy to deprioritize this and chase growth, but markets inevitably tighten. The companies that endure (and continue to raise capital on good terms) are those that prove their unit economics early and improve them over time. If you can show that each dollar invested in growth returns more dollars back in revenue or gross profit, investors will line up to give you funding. If not, you’ll be fighting an uphill battle, or worse, scaling a model that loses money faster as it grows.

Mastering unit economics is not just about impressing venture capitalists - it’s about building a resilient, self-sustaining company. Even if your goal is aggressive growth and market dominance, you will reach a point where the question “Can this business actually make money?” must be answered convincingly. The sooner you answer it, the better off you’ll be. Strong unit economics give you options: the option to raise funding (because investors see the promise of a return), or even the option not to raise, because you can grow through internally generated cash. As one startup finance adviser put it, “Unit economics helps startups determine whether they’re making money on every sale or losing money, which helps with long-term sustainability.” A startup that makes money on each customer can survive nearly any market turbulence; one that loses money on each customer is living on borrowed time and capital.

For founders, the actionable takeaway is this: treat unit economics as a first-class metric, as important as your product roadmap or your growth numbers. By instilling a culture of metric tracking and continuous improvement around these fundamentals, you’ll not only have an easier time fundraising, but you’ll also build a business that can stand on its own legs. And ultimately, that’s what every founder and investor wants - a business that isn’t just growing, but growing profitably and durably, one unit at a time.

Colin Ryan