When it comes to success or failure as a startup, it’s ultimately about the people and the numbers. Or people and numbers. I’ve written about people challenges before and I will again – a lot of it is intuitive if infuriating – but the numbers?
Too many founders and entrepreneurs seem to want to hide from the numbers. Even if you think you are not a numbers person, never ever say that out loud. You have to be. As with everything else, it’s OK to fake it until you make it. Then who knows? Like me, you may discover you had an inner accountant in you all along! Here’s how to sweat your metrics, data and standard numbers harder in order to directly increase your chances of success.
Business model basics matter
You can have a few great products, customers, awards, lots of PR – you can feel like a proper company – and still not have a business. If the unit economics of your startup do not stack up, you do not have a business. If the reason you hate working on your financial model is because it makes you sick to realise the numbers are impossible to achieve, you do not have a business. If you have based your pricing model solely on what IBM commands for an inferior product to yours, you do not have a business. If you assume your costs will stay low because you will keep bootstrapping forever, you do not have a business. Until your customer acquisition costs, churn/renewal rate and operating costs are aligned to a place where you have proved that it is possible to both satisfy customers and make money, you do not have a business.
Do not imagine that because your end goal is an acquisition by Facebook, Salesforce or whoever that having basic business model does not matter. In Europe at least, it is almost unheard of to successfully scale first and figure out the revenue model second. If you do not have a strong business model, accompanied by unit metrics that make sense, you will not survive long enough to be acquired, and on the vague off-chance you are, it is likely to be as an early stage acqui-hire (as in buying the team) where you’ll get to stick around as an employee for the next few years to really learn the importance of unit metrics and KPIs.
One of the reasons I care so much about this is that I am a data geek and yet I know from personal experience how easy it is to overestimate your monthly revenue potential and under-estimate the cost and time of acquiring a customer, then the cost and effort that goes into to satisfy those customers. I have written about product market fit issues, but it’s more fundamental than that – this is a basic business model failure and that can be tackled and resolved really early on (as in before building a product or raising money).
Over the last few months, I have met with an average of 5 entrepreneurs each week. Yet I have seen so few startups with really good revenue models and accompanying financial models/unit metrics, that I am starting to conclude there is an educational black-hole around this – at least in the UK. I get it is not a sexy as pitching, but this is not something you can outsource – nor can you afford or need a Financial Director. A friendly accountant or advisor might help you pull together an investor-worthy financial model and P&L, but defining the financial bones of your business are entirely down to you.
So if I am scaring you or guilting you into worrying that you’ve been giving insufficient thought to your business model, A) Good!! My work here is done. B) Here’s a reading list:
Blindly copying the “normal” revenue model for your space is a risk. It is possible everyone else was copying too and it makes no sense to anyone. It is also possible that it worked for the ‘original’ innovator, but you have very different businesses and it isn’t optimal for you. It may also be that by settling on the first and obvious revenue stream, you miss multiple other opportunities to become a cash-generating entity.
There a couple of key things to think about that can make the difference between success and failure. The biggest, in my view, is cash conversion cycle – at its simplest, how quickly does money come into your business compared to how quickly it leaves again. Upfront payments, annual payment over monthly payments, bulk credit bundles are fantastic because they generate cash that can be reinvested into growth (people, marketing, raw materials) so that you can build and sell more. Slow sales cycles + slow cash-in cycles leave you with little choice but to raise money from other sources and hampers your ability to rapidly iterate/pivot to get product-market fit.
I’m all about reading lists this week. But trust me – you might learn something!
Startups tend to start off pretty cost efficient, with the best highly talented at getting things for free. But bootstrapping, blagging freebies and hustling something for nothing is rarely a sustainable long-term strategy. It can constrain your ability to buy more of the goods, people or marketing that would let you sell more and therefore grow. Look at any possible means to get clever on your payment terms, think leasing over buying, drop-shipping over buying stock, short production cycles over long ones, gin not whisky (that one’s for the Scottish readers!)
Worse still, bring on a few directors and advisors, raise a bit of money, and suddenly founders can find themselves under pressure to hire expensive CTOs, FDs, and Sales Directors. (More about optimal team sizes below). This can knock the whole financial model of the business off – if the cost of acquisition consistently exceeds lifetime value – there is no business at all. Beware of having an old or non-startup playbook imposed on you and really, really understand the financial and structural shape of optimal businesses in your space. Run smaller, cheaper and more efficiently than most believe possible for as long as it takes to get product market fit – only then does adding multiples of more of the same generate growth that you can afford. And stay cost-efficient – stay positively tight and frugal on spending around the boring essentials. As long as being frugal is not making you inefficient, you are buying a tiny bit of extra cash runway and not pointlessly eating into profits.
Between Excel, your online banking & accounting tool and Google Analytics, you’ll likely have everything you need to track all the business critical startup KPIs (key performance indicators). Be the owner of these tools and never trust a spreadsheet where the formulas have been hidden from you.
Your key metrics will vary by business type, I have a SaaS and data tech bias because that is what I know best. But the following are fairly universal:
Bookings are the value of a contract between the company and the customer. It reflects a contractual obligation on the part of the customer to pay the company.
Revenue or sales refers to all the money a company takes in from doing what it does — whether making goods or providing services.
Net revenue or sales equate to gross revenue minus directly related selling expenses. At a minimum, this should reflect the wholesale cost of products sold, including freight, and any sales commissions paid.
Net Income – aka the bottom line – is simply profit, and the whole income statement flows toward this number. You start with net sales or net revenue, subtract your expenses, factor in any gains or losses from other activities and set aside money for taxes, if necessary. Whatever is left is net income. If more money went out than came in, the company has a net loss.
EBITDA – Earnings Before Interest, Taxes, Depreciation and Amortisation – is essentially net income with interest, taxes, depreciation and amortisation added back to it. EBITDA is used to analyse and compare profitability between companies because it eliminates the effects of financing and accounting decisions.
Net burn rate – the total amount of money your company loses each month. This tells you how long you can operate before running out of cash and therefore dictates your funding horizon. Personally, I think you should always know the exact day the money runs out – but then I thrive on pressure!
Customer acquisition cost (CAC) is the amount of money you need to spend on salespeople, marketing, advertising, exhibitions and related expenses, on average, to acquire a new customer. It is so easy to underestimate it – especially if you only look at the paid marketing/advertising component. But if you had to employ a salesperson for a year to close a sale, and they took 10 flights and 20 nights in a hotel, that is all part of your CAC.
ARR (annual recurring revenue) is a measure of revenue components that are recurring in nature. It should exclude one-time (non-recurring) fees and professional service fees. This comes down to the never-ending tussle between product and consultancy and if consultancy really counts – no, in this metric it doesn’t.
Lifetime value (LTV) is the measurement of the net profit of the customer over the life of the relationship. Understanding this number, especially in its relation to CAC, is critical to building a scalable company. The ratio of CAC to LTV is an indicator of the sustainability of the company, as it is extremely difficult to support a negative LTV without substantial investment.
While top-line bookings growth is super important, investors want to understand how profitable that revenue stream is. Gross profit provides that measure. What’s included in gross profit may vary by company, but in general, all costs associated with the manufacturing, delivery, and support of a product/service should be included.
Gross profit margin = (revenue – cost of goods sold)/revenue. The gross profit margin should be large enough to cover your fixed (operating) expenses and leave you with a profit at the end of the day
Churn rate, when applied to a customer base, refers to the proportion of contractual customers or subscribers who leave the company during a given time period. While there are all different kinds of churn, according to Andreessen Horowitz, investors typically look at it the following ways: Monthly unit churn = lost customers/prior month total; Retention by cohort: Month 1 = 100% of installed base, Latest Month = % of original installed base that is still transacting; Gross churn: MRR (monthly recurring revenue) lost in a given month/MRR at the beginning of the month.
Are your investor and business metrics aligned?
If you have taken equity investment, you need to understand that you have committed to a path of very high growth, not a path of low scale profitability. If your growth is stable, your costs declining and you’re reaching break-even – you have in all likelihood failed to deliver on your plan. In this investment model, you are committed to spending the money you have taken and turning that into very significant – as in 20x-50x or more, multiples of growth in a large and growing market. Even niche traction, if it disproves there is a huge market, is problematic. Your investors will typically have a standard set of growth, churn and customer acquisition efficiency metrics to measure your progress – once you are on this path, your whole company needs to understand and optimise for these.
“CMRR (Committed Monthly Recurring Revenue), Cash Flow, CAC (Customer Acquisition Cost and Payback Period), CLTV (Customer Lifetime Value) and Churn. We recommend EVERY cloud business track and report on these as a starting point, plus additional metrics that are relevant to your teams and functions as appropriate.”
Smart, high growth focused investors won’t typically want you distracted by consultancy and professional services if you are a SaaS or cloud-based business because those metrics simply don’t stack up. As Bessemer spells out:
“To be very blunt with our perspective: professional services revenue is bad for cloud businesses in most cases. It’s low gross margin revenue that slows down your implementations and can only scale in proportion to your services headcount. For these and many other reasons, Wall Street investors and your customers hate to see a large mix of services revenue in cloud businesses. You should focus your product development, sales, and client success teams on reducing the implementation friction, time, and cost as much as possible.”
This is different to the “safe” and attractive mixed revenue, profit maximising business that many lean toward – but if you have accepted equity investment, that is not the path you are on. You and your board really need to understand this.
Yet another reading list (SaaS focussed, with David Skok featuring highly as he is the master of this stuff). See, I really really want you to get good at this:
I have had more than one startup CEO tell me “Oh I’m terrible with numbers.” To which I”m afraid my reply is “well get better fast or get a new CEO.” You don’t need to be a mathematician to know the essentials of reading a financial model and understand if that business is healthy or otherwise – including your own. Your job as CEO or founder of a startup is to turn a temporary, ever-changing organisation into a sustainable business. To quote Steve Blank:
“a startup is a temporary organization used to search for a repeatable and scalable business model.”
Business model optimisation and all the associated points above are in the official job description! You can’t absolutely, non-recoverably run out of money, but you can run very very close to the wire and still survive the startup phase. Understanding the basics of business financial management (which is counter-intuitive to personal cash management) is critical. On one occasion, the entire survival of one of my startups came down to extreme and inspired cash allocation management thanks to input from our accountant. (A tactical late tax payment or two and the strategic use of a weekend to delay payroll and we survived our biggest crunch). The pennies matter, and your understanding of the pennies and the timings of their movement in and out matter even more.
As and entrepreneur, CEO, founder (and in my view a board director) in a startup or early-stage company you must be able to read and produce a cash flow forecast and a basic financial model. You must be able to read and produce a P&L, sometimes called an income statement. You must be able to read a balance sheet and read a cash flow statement. Board directors and CEOs should be able to challenge or at least ask intelligent questions of their accountant or FD on each of these. I also recommend pulling the accounts for potential b2b clients so you can understand the real shape, health and priorities of their business – the last thing you need is a customer going out of business without paying.
Stick with me on this – if you don’t have it already get an online accounting tool like Freeagent or Xero (I use Freeagent when small, like now, and Xero when bigger than 12 people – but that’s my arbitrary rule!) This automates a lot of things for you and you’ll see some of this reporting generated “live”which makes it real. Your accountant can help, if required. Also, don’t re-invent the wheel on financial projection templates – these exist and are freely available, like the Virgin Startups one:
If the customer isn’t ultimately prepared to pay for your product/service you do not have a business. But more insidious is when you have the “wrong” type of paying customers – those that will never become profitable and simply lose you money, restricting your growth potential. How is this possible? Well, what if the cost to acquire, or the cost to serve a customer is higher than their lifetime value? What if they extract as much value from you up front as possible, then cancel, meaning you cannot recoup the cost of acquiring them. What if they subscribe to your highly subsidised free service and happily consume your resources, but do not obediently comply with your upsell/cross-sell plans like they were supposed to?
This can indicate a few problems – some fixable, some terminal. Fixable is that you are being sloppy in your marketing targeting and sales qualification/hygiene processes. Being more thoughtful in your customer segmentation and targeting prioritisation – outlined in my data analytics presentation below – means you can focus on profitable groups, conserving resources and enabling growth. Fixable once you recognise and act.
More problematic to the point of potentially being terminal without drastic remedial action – and an indicator of other issues, including lack of product-market fit, or problem/solution fit – is if the true cost of customer acquisition (not just marketing spend, but sales cycle and people time) consistently exceeds actual customer lifetime value. Either because the sales process is too slow and costly compared to what can be billed over the lifecycle of the customer, or customer churn is too high and/or the length of the customer lifecycle too short to allow marketing payback. For example, if your customer will only ever use your product for three months, yet it takes you six months to recoup their costs, you have to look at both your pricing model and your cost of acquisition as there is no repeatable and scalable business in this scenario.
Is your churn rate too high?
Acquiring new customers is one thing, but retaining them is even more important for most business types. Your customer retention rate indicates the percentage of paying customers who remain paying customers during a given period of time. The opposite of retention is churn (or attrition), the proportion of customers you lose in a given period of time.
Churn is bad but inevitable, so it’s important to track and improve your churn rates over time. You have to get churn down as part of satisfying your customer and getting product-market fit – and you can’t survive excessively high churn for too long. If you are in long sales and contract cycles – like enterprise software – you need to look for proxies for churn before it occurs, as you can’t afford to learn after a year that everyone decided your product was useless 10 months ago but didn’t tell you. Measure logins, the number of active users, frequency and duration per user – look for advance indications of churn so you can act, rather than react. This is where a good product manager really comes into their own.
Each sector has its own metrics, but the mythical 5 % annual churn is a great benchmark to aim for if you’re a fairly established SaaS targeting the enterprise. (There aren’t enough customer in enterprise for you to survive too high a churn rate). If you’re earlier-stage or targeting SMEs, you can potentially expect churn to be closer to 5% per month. As your product continues to iterate towards market fit and your revenue model settles, you should get better at closing and retaining good fit customers, so your churn rate will improve over time. You’ll need to do some research to find out what normal looks like for your market, and that may mean asking around amongst former employees of competitors – this example is for SaaS:
“A typical “good” churn rate for SaaS companies that target small businesses is 3-5% monthly. The larger the businesses you target, the lower your churn rate has to be as the market is smaller. For an enterprise-level product (talking $X,000-$XX,000 per month), churn should be < 1% monthly. Most early-stage SaaS companies I’ve observed typically have churn around 10-15% for the first year as they work out exactly what their product needs to do, then they’re able to reduce it pretty quickly.”
Finding the optimal number of people for your startup is a huge headache – and sometimes you can get trapped in the investment loop because you think more people are inevitably better. If you only had more people all will be well. But too many and you will add complexity, slow things down, burn through too much cash, and increase management overhead for no real benefit. Too few and you will be resource constrained and unable to grow as fast as you’d like. And if you’re so late more people seems like the only answer, Brooks Law and the mythical man month kicks in – the summary of which is “adding manpower to a late software project makes it later”.
I must confess, I wish I had hired fewer, more specifically experienced people earlier on and run on a team of 5 – 10 (as opposed to 18 – 25) for as long as possible. Turns out I am not alone in that thinking. Writing on optimal team sizes this AVC post concludes the optimal team is something like:
“5 or less while you are building product, 10 or less when you are finding product/market fit, and 25 or less while you are working on generating revenues and locking down the business model. That’s a rule of thumb for software based businesses that don’t require a large direct sales force or some other significant labour cost.”
More people also add communication complexity, as shown in this diagram by Bob Gower:
Hiring in response to investment and board pressure (as opposed to your development stage) can be particularly problematic as it adds not only complexity, overheads and wage pressure, but also potentially has a destabilising effect on culture and reduces productivity.
My personal hard-learned advice here – keep your team small and highly executional until you have product-market fit, don’t carry management costs before you need them and can afford them. And when you do hire executives remember that the very nature of the term means they are supposed to execute – as in actually do stuff. The startup CEO typically knows this intuitively and does everything – often for too long, but typically up to at least the first 30 people. Execs coming in from larger or more established companies may never have learned the necessity of being hands-on and self-servicing and can happily let the CEO carry on doing everything, which is rubbish all round. You can’t afford passengers, so measure employee performance on execution based deliverable at your early stage.
Are you missing your real hidden treasure?
Sometimes the most valuable asset in your business is not what it seems. For example, I hear a lot of startups say we will do x, y, z and then we’ll become a data play. Well no and yes. Becoming a data play isn’t as simple as we’ll collect our customer data and sell it to the highest bidder and/or back to our customer but prettier. Nevertheless, there are really interesting opportunities to use data sets to add significant commercial value – for example by generating segmentation, predictions, models, classifications and to make those commercially available as APIs or integrations with other products.
Process innovation is patentable, brand protection is valuable, the one good feature of a dog of a product that people still buy anyway just to get it is a hidden diamond in the rough. As you go through your startup journey, think like a farmer. Keep turning the soil to see what grows when exposed to the light, and allow tender shoots to flourish into a structured test. The chances of you getting it absolutely right with plan A are remote – so have a culture that allows for the possibility to keep surfacing your hidden treasure, long after the grown-ups have told you to stop playing.
Do you really have a business yet?
How are you going to make money? How will you acquire customers and how much will that really cost? How long will the customers stay and what will they be worth? How many people and operating costs are you throwing at all this? If you can’t answer these questions, you may have a startup, but you don’t have a business yet.
That is perfectly OK, provided you behave and spend like a startup while you fill in the blanks, prove out your sustainable commercial model and find product/market fit before you escalate costs and headcount. Do it the other way round and your chances of success are very remote.
Vicky Brock is a serial founder & entrepreneur, and the founder of award-winning AI and data technology startup Clear Returns.