Author: Joe Knowles

Industrial Strategy-reasons behind the proposals

In January the government published a green paper on “Building our Industrial Strategy”. The report lays out 10 pillars consisting of wide reaching measures with implications for the whole economy. In my previous post I pulled out the proposals which I think are most relevant to the UK early stage tech sector.

In this post I wanted to discuss in more detail the report’s reasons behind those measures, some of which I agree with, some of which I don’t.

The macro problem: low productivity

The strategy is principally concerned with improving the productivity of the UK workforce.

It reports that despite strong GDP growth since 2010 (second only to the United States among advanced economies), and the lowest un-employment rate for 11 years, real wages have struggled to recover from the decline during the 2008 recession.

The paper points to the ‘productivity gap’ between the UK and its ‘competitors’ as the major cause of this stagnation in real incomes. Whilst the UK had started to close the gap in terms of output per worker (middle chart, below) with France, Germany, and to some extent the US, much of this progress was reversed during the recession.

More importantly, the UK remains far behind all three countries in terms of productivity per hour worked. As the right hand chart below shows, workers in the US, France and Germany produce as much in 4 days as UK workers do in 5.

As well as improving overall productivity, the strategy aims to correct stark regional disparities. As the chart below shows, productivity in London is now 72% higher than the national average with all other UK regions except the South East having productivity below the national average.

According to the paper, this is more pronounced than it is for our neighbours, although it is difficult to compare apples with apples given the differing geographies of different countries.

So what does this have to do with tech start-ups and investors?

Well the report rightly highlights technology innovation by early stage businesses as an important driver of productivity improvement and it specifies two main barriers holding this innovation back.

1. Insufficient access to R&D funding.

2. Lack of support for ‘scale-up’ businesses.

As I explain below, the report makes a good case for the first, but I’m not so sure about the second.

Access to R&D funding

The green paper concludes that there is a need for increased government R&D funding, highlighting a correlation between government support and business investment in R&D (BERD) as shown in the chart below.

The UK invests 1.7% of GDP in public and private R&D which is below the OECD average of 2.4% and far behind leading backers of innovation (e.g. South Korea, Israel, Japan, Sweden, Finland and Denmark).

This is a function of lower government spending but also a below average ratio of private to public investment.

The report also emphasises that whilst the UK has a strong record of early stage research, we are relatively weak at turning those innovations into commercial successes.

The UK has 3 of the world’s top 10 universities and 12 of the top 100 and it has the “most productive science base of the G7 countries”. However, the report claims that we have a long standing weakness in translating research into commercial outcomes and have “too often pioneered discovery without realising the commercial benefits”.

This may be partly due to the way we distribute funding across the different stages of R&D. Whilst our distribution is not hugely out of line compared to other European countries, we have a striking skew towards early stage research (basic and applied research rather than experimental development) compared to innovative countries such as Israel and many Asian countries. Notably China spends 80–90% of its R&D funding on later stage experimental developments compared to 30–40% for the UK (see below).

You can read about the proposed measures to boost R&D in my previous post.

Support for ‘scale-ups’

The paper highlights that whilst the UK has done a great job of creating a world class start-up environment, it has done less well at fostering those start-ups to reach ‘scale’.

The UK ranks 3rd for business start-ups but only 13th for scale-ups according to OECD research, and whilst 2015 was a record year with 5.4 million small businesses in the UK, a “lower proportion of UK start-ups grow into standalone businesses than in the US”.

According to the paper “some observers say we have an under-supply of late stage venture capital compared to the US” and this is presented as the main cause of our ‘scale-up’ under performance.

However, the report provides no evidence to support this, and as a ‘scale-up’ investor myself I haven’t seen any evidence of it in the market. Of course, it depends on how you define ‘scale-up’, but in the £2–15m range that we invest at Smedvig Capital, its doesn’t feel like there is a shortage of capital.

According to Beauhurst (a data provider) there are 76 funds who can invest up to £25m in equity finance in the UK, there are 112 that can provide up to £15m, and 247 than can provide up to £5m. So that’s somewhere between 76 and 247 funds chasing roughly 200 deals per year (I acknowledge there is a certain amount of ‘chicken and egg’ in this relationship).

Yes, the UK is far behind the US in terms of scale-up successes but I am not sure that this is down to a lack of funding. I don’t have any strong evidence to say what the underlying cause is, but let us not forget that the UK is a fundamentally smaller market than the US (which is 5–10x bigger in most cases). For UK businesses to reach anywhere near the scale of similar US competitors they either need to go to the US or to multiple other markets. Given the challenges of entering new markets this must make it harder for UK businesses to reach ‘scale’.

Some of the current and proposed work by the Department of International Trade (including expansion of export finance) may well help with this by making it easier for UK businesses to scale internationally.

The paper also suggests that fund management incentives weaken long-term decision making in Europe as “funds are expected to deliver short term returns versus industry benchmarks”. At Smedvig Capital, we are lucky to have a very flexible mandate and we certainly see that many successful investments take longer than the 3–5 years that many companies are forced to aim for (our average hold period is 7 years).

The report also singles out lower levels of fixed capital investment for UK listed firms compared to other OECD countries as a possible symptom of short term incentives in public markets holding back long term investment (we have been in the lowest 10 per cent for 16 of the last 21 years).

If you have a view on this topic, the government has launched its business scale-up inquiry and is looking for feedback by May 3rd.

You can read about the proposed measures to help UK businesses scale-up in my previous post.

Conclusion — good proposals, not sure about the reasons

Whilst I definitely support the measures laid out by the report, I’m not sure I fully agree with all of the reasons behind them. In particular, I haven’t seen any evidence of a lack of ‘scale-up’ finance in the UK.

Industrial Strategy-implications for tech start-ups and investors

In January the government published a green paper on “Building our Industrial Strategy”. This week I got round to reading it and although it is long (132 pages) and far reaching, it does have some proposals relevant to the UK technology ecosystem.

I don’t necessarily agree with all of the report’s conclusions, but below I have summarised the key proposals that start-ups and investors should be aware of.

In my next post I discuss the main reasons behind these measures, some of which I agree with, some of which I don’t.

The government is looking for feedback on the strategy so if you have any, I would urge you to respond to its request for input by 17th April.

Proposed changes — 10 pillars

The strategy outlines 10 ‘pillars’ (copied below) aimed at increasing productivity and driving growth across the UK. The pillars are far reaching but several of them present potential opportunities to boost the UK’s early stage tech sector. Pillars 1 and 4 are particularly relevant.

There are many broad implications for business, but I will highlight the three main implications for early stage tech.

Implication 1: increased access to R&D funding

The first ‘pillar’ of the strategy aims to boost R&D investment and help drive commercialisation of research. There are many approaches discussed with varying levels of rigour, but the key proposals are:

 – Increase government investment into UK R&D by 20% — a further £4.7bn of funding by 2020–2021. Start-ups should keep an eye out for how to access this funding.

 – This will be coupled with efforts to optimise the funding and tax environment to drive up the ratio of private to public investment. Again, an important area to watch for start-ups and investors alike.

– Creation of UK Research and Innovation (UKRI) which brings together Research Councils with Innovate UK to develop a strategy for how to optimise spending of the additional R&D funding. The government seeks initial views which can be submitted here by 17th April. Start-ups and investors should have their say.

 – One project that is already underway is the Industrial Strategy Challenge Fund which creates a new funding stream for UKRI to back technologies where: the potential market is large, the UK has research strength and business capacity to meet the market need, there are significant social and/or economic benefits, and there is evidence that government support can make a difference. Start-ups should consider whether their sector might be applicable for Challenge Fund support.

 – Sectors that have been suggested are smart energy (including batteries), robotics and AI (including autonomous vehicles), satellites and space tech, healthcare, manufacturing and materials of the future, biotech, quantum technologies, and ‘transformative digital technologies’. But again, the government seeks suggestions.

Implication 2: increased support for ‘scale-ups’

Pillar Four is focussed on measures to help businesses scale-up, with the following proposals being of particular interest:

 – A Patient Capital Review will be launched in Spring 2017. Scale-up companies should follow how this review could help them.

 – Increased backing of institutions to catalyse private sector investment including an additional £400m for the British Business Bank. This could be a valuable source of finance for scale-up companies.

 – The government will ‘explore’ how its data (such as VAT returns, other HMRC data, or companies house data) can be used to help investors identify potential scale-up targets. Growth investors should input into what data could help spot potential targets and how this could best be accessed.

The government has launched its business scale-up inquiry and is looking for feedback by May 3rd.

I should say that whilst I’m absolutely in favour of increased support for scale-ups, as a scale-up investor myself, I’m not sure that I agree with the conclusion that there is a shortage of scale-up venture capital in the UK. More on this in my next post.

Implication 3: investment in tech infrastructure

There is a whole section focused on improving the UK’s infrastructure given our poor relative ranking vs other developed countries (ranked 24th globally on transport infrastructure quality by the IMF).

A wide range of infrastructure investments are planned, but most importantly to the tech-sector is a new £400m Digital Infrastructure Investment Fund to boost fibre broadband providers and a further £740m “earmarked” for:

 – “Full fibre broadband roll-out” for businesses and the public sector.

 – A “coordinated programme of integrated 5G and fibre projects to accelerate and de-risk the deployment of future digital technologies.

Conclusion — funding opportunities for R&D commercialisation and scale-ups

The government clearly acknowledges the early stage technology sector as an important part of the solution to the UK’s productivity problems. It proposes increased R&D funding (particularly aimed at later stage commercialisation) and support for ‘scale-up’ businesses as key steps to boost the sector, as well as improvements to the UK’s digital infrastructure.

There are many other implications for business more broadly, but I have chosen to focus on those which specifically effect technology start-ups. One example of a broader proposal is an expansion of export finance and the Department of International Trade (DIT) in an effort to boost exports and make it easier for UK businesses to scale internationally. If you are thinking of international expansion, I would recommend that you find out how the DITcan help.

Start-ups and investors should keep an eye on how these new measures evolve as they could present valuable opportunities for funding and support.

Importantly, the strategy is presented as work in progress and the government welcomes input from industry, you can respond here if you have any feedback.

In my next post I will look at some of the reasons behind the measures discussed in this article.

SaaS Metrics – how to improve?

In my last two posts I explained why LTV:CAC and CAC Payback are the two most important metrics for SaaS startups and how to use them to interpret the health and potential of your business.

But what do we do if we need to improve either of these metrics?

Unfortunately there is no easy answer. There are limitless tools and tricks, but with imperfect information there is rarely an obvious ‘right’ answer. Even if there was, the right approach would be specific to each individual business situation, so there is no generic playbook for how to improve.

In practice you have to be constantly testing and adapting, seeing what works and what doesn’t. It is a on-going tactical and strategic battle.

However, in this article I will discuss some high level steps that may help you to forge an informed path and give yourself a fighting chance of making the right moves.

Step 1. Measure

It sounds obvious, but it’s amazing how many businesses don’t track their LTV:CAC and CAC Payback. We have already discussed why these metrics are important, and if you are not tracking how they evolve on a monthly or quarterly basis, you should be.

Of course for an early stage business you can expect metrics to move around quite a bit as you make changes and your business evolves. But by measuring LTV:CAC and CAC Payback, you can see how the changes you make impact the fundamental unit economics of your business.

More on the specifics of how to actually calculate key metrics in a later post.

Step 2. Measure some more

LTV:CAC and CAC Payback are nice, concise metrics that give you an academic read on the overall health and potential of your business. But they are not actionable. To understand how to act to improve either of these two key metrics, we first have to measure their constituent components.

CAC Payback is a function of sales and marketing spend, new Monthly Recurring Revenue (MRR)landed by the sales team, and gross margin.

LTV:CAC is a function of average MRR (sometimes referred to as Average Contract Value, or ‘ACV’), gross margin and gross churn.

The simplest way to track these components is using a Monthly Recurring Revenue bridge (‘MRR Bridge’) as laid out below.

Here you can see what your opening MRR was at the start of the month and what closing MRR you finished the month on. You can see how the change between opening and closing was driven by new MRR from new clients, expansion or contraction in MRR from existing clients, and finally gross churn, which is MRR lost due to clients who have left.

It is important to track your gross margin for the month and your sales and marketing spend. I also like to track the total number of customers.

More on the MRR bridge and how to use it to actually calculate your key metrics in a later post.

Step 3. Segment your metrics

Sometimes you can improve your key metrics just by shifting your mix of customers, products or channels, without having to think about driving change in any given component.

For example, you may find that the unit economics don’t stack up when serving customers below a certain size. You may decide to change your approach by cutting sales and marketing spend to that segment, or reducing their account management. In some cases, you could decide to just stop serving customers below a minimum threshold altogether – saying no can be a powerful tool.

But to make decisions about your segment mix, you first need to be able to measure the key metrics and their components at a segment level.

Segmented metrics is probably something I would only consider for later stage businesses (post Series B) because it only really makes sense if you have enough customers and use cases to segment meaningfully and if your product, and sales teams are sufficiently structured.

There are three common axes of segmentation.

1. Customer segments

The most common type of segmentation. Typically broken down by size (e.g. small, medium, enterprise), but sometimes by vertical or use case.

2. Channel segments

It can be useful to see how your key metrics vary by channel. For example, inside sales vs field sales vs re-seller partnerships, or online marketing vs direct mail. Also up-sell vs new sales.

3. Product segments

This is less common, but in some cases where you have different sales teams selling different products, it may be worth considering the economics of each product individually.

If you measure LTV:CAC and CAC payback for each segment you might find that one customer segment, or one channel, or one product group is pulling the rest of the business down. Conversely, it might be that you have one or two star segments with stellar economics where you should be focusing all your resources.

Step 4. Get tactical

You may decide that tweaking your segment mix is not the right approach and that you need to take corrective action to drive improvements in a specific component of your unit economics.

There are too many options, and the answer too dependent on the specifics of the commercial situation, to go into detail here. But below I have laid out some of the questions you might consider when trying to improve each component of unit economics. These suggestions are by no means exhaustive.

How can we increase average MRR (‘ACV’)?

– Is our product suite and pricing optimised to encourage cross-sell, up-sell and volume increases from our clients?

– Can we add functionality or features to drive more value for, and spend from our clients?

– Is our account management team properly structured and incentivised to deliver maximum value from our clients?

– In particular, how do we recognise and compensate up-sell vs the initial sale?

How can we increase gross margin (reduce variable cost to serve)?

– Can we streamline our processes or use technology to reduce delivery and support costs?

– Can we productise further to make the delivery and operations teams more efficient?

– How can we make our account management and support more scalable? Can we productise these services?

– Can we encourage more ‘self-help’ customer behavior?

– Are we offering too much support too cheaply to certain customer groups?

How can we reduce churn?

– Can the proposition be adapted to better serve high churn customer segments?

– Are there common reasons for churn and can they be fixed?

– Are there early warning signs of churn such as falling Net Promoter Score, or usage metrics?

– If so, can we implement processes to flag these signs before it is too late?

– Can we create more ‘sticky’ functionality and features or can we do more to become more embedded in our customers’ workflows?

– Can we see a high churn ‘bedding in period’ after which customers tend to stick around?

– If so, what can we do to increase engagement during this bedding in period to maximise the likelihood that a client becomes ‘bedded in’?

How can we increase sales efficiency?

In other words, how can we deliver more new MRR for the same or less sales and marketing spend?

 – Is the sales team structure and compensation mechanism optimised to match our desired customer and product segments?

– Can we tweak the sales process and compensation structure to shorten the sales cycle and increase sales cadence?

– Can we adjust our terms to shorten the time from landing a sale to revenue recognition?

– Can we improve our training and recruitment processes to reduce the ramp-up time for new sales reps?

– What is the variability in sales rep performance, what can we learn from this?

– What does our marketing funnel look like and where can we improve conversion?

– Which marketing channels are most effective, how can we optimise for this?

– Can we unlock attractive new customer segments with pricing and proposition adjustments?


Over the last three articles we have seen the importance of LTV:CAC and CAC Payback and how they can be used to indicate the health and potential of a business. Finally we have considered ways of improving these key metrics.

In reality it is a constant tactical battle which is never over. There are limitless tools and options and no easy right answer. But a good starting point is to at least measure your key metrics and their constituent components so that you understand what is driving performance. If you have sufficient scale, it can be useful to segment your metrics to see if certain customer groups, channels, or products are holding you back or driving you forward. Finally, there are a whole range of levers you can pull to try to boost the different components of unit economics.

SaaS Metrics – What am I aiming for?

In my last post I presented LTV:CAC and CAC Payback as the two most important metrics for SaaS businesses.

LTV:CAC tells us how profitable a business will be at maturity and CAC Payback tells us how much cash it will take to get there. Therefore, these are the two most important metrics, and entrepreneurs should monitor them religiously.

Management should strive to improve these two metrics. But founders often ask us “how good does my LTV:CAC and CAC Payback need to be?”

In this second post of three, I will explain why for SaaS businesses to ‘work’, they need to have LTV:CAC of at least 3x. I will also show that for capital efficient returns, CAC Payback should ideally be less than 12 months.

I will then demonstrate unit economics in action through a worked example.

LTV:CAC must be at least 3x, ideally 5x.

In a previous post I explained that LTV:CAC is a great predictor of profitability at maturity.

As it turns out, there is a direct mathematical relationship between LTV:CAC and ‘steady state’ contribution margin.

By ‘steady state’ we mean once the business has stopped investing in growth and is just spending enough on sales and marketing to replace churn and maintain a constant revenue.

‘Steady state contribution margin’ is the percentage of revenue that is left after taking off variable cost of sales, and sales and marketing costs (churn replacement only). It is what is left over to cover fixed overheads before getting to ‘steady state operating profit’.

The chart below shows how for a given gross margin, steady state contribution increases with increasing LTV:CAC. This improvement is steep at first, but as LTV:CAC increases, the rate of contribution improvement starts to slow.

So, what can we learn from this?

Well, below 3x LTV:CAC it’s going to be almost impossible to make a highly profitable business. Benchmarks (such as those published by Pacific Crest) tell us that even the largest SaaS companies have an overhead base of at least 30% of revenue. Therefore, to leave enough room for a ‘meaningful’ profit margin (say 10%) we need contribution margin to be greater than 40%. Unless LTV:CAC is at least 3x, this will be tricky.

Between 3x and 5x there is a steep improvement in contribution margin (roughly ten percentage points improvement). At 5x LTV:CAC, contribution margin is high enough that a very profitable business should be possible.

Beyond 5x, there are still benefits to be had, but we start to see diminishing returns. Doubling LTV:CAC from 5x to 10x only yields a further ten percentage points improvement in contribution margin.

So in conclusion:

LTV:CAC needs to be at least 3x for a business to have a chance of profitability, but really management should be aiming for 5x to make a great business.

I will explain the maths of this relationship in a later post.

Ideally CAC Payback should be less than 12 months.

CAC payback is an indicator of how much cash a business will need to spend on sales and marketing to reach a certain size in a certain time.

Again there is a mathematical relationship here, although it is more complex than the LTV:CAC rule. I will delve into the maths in a later post, but the rule of thumb that we apply at Smedvig Capital (and has been written about by various other commentators) is:

CAC Payback needs to be less than 12 months for a business to have a good chance of capital efficient growth. But for enterprise SaaS businesses with high value clients, this can probably be stretched to 18 or even 24 months.

This is a slightly more nuanced, less objective rule than the LTV:CAC rule because the amount of cash one is willing to invest depends on the expected size of prize and appetite for risk.

For most SaaS businesses, CAC Payback needs to be less than 12 months to provide the capital efficient growth that attracts investors to SaaS in the first place. But for enterprise SaaS companies with high value, low churn customers (and thus high LTV:CAC), a higher CAC Payback period (18–24 months) can work.

So that’s the theory, but to demonstrate the impact of unit economics, let’s do a worked example.

Thought experiment: unit economics in action

Imagine we have three SaaS businesses with identical P&Ls. Each is raising a £7m Series A round to invest in sales and marketing acceleration.

Three ‘identical’ P&Ls.

All three are run rating £2m Annual Recurring Revenue (‘ARR’) and growing 10% month on month. All three have a gross margin of 75% and all three are spending just under 50% of revenue on sales and marketing and a further 50% on overheads (tech, product, finance, admin). They are all loss making to the tune of -£0.5m. They look like three good, early stage businesses.

But with different underlying unit economics.

Company A has low CAC, quick CAC Payback, small contract values (Monthly Recurring Revenue, ‘MRR’), high churn, low LTV. This is the sort of profile we might expect from a consumer subscription business for example.

Company B has very high CAC, long CAC payback, large contract values, low churn and high LTV. This is more like the profile of an enterprise SaaS business selling large, bespoke, contracts into blue chip companies.

Company C is somewhere in between. Perhaps the metrics of a SaaS product aimed at small and medium sized businesses.

It’s tricky to disentangle all the individual metrics to get a read on how the three businesses will perform overall.

But, they all have the same P&L so should all be pretty similar… right? Well, let’s see where they end up five years after the investment.

Very different outcomes five years later.

Company A: Disaster

To be fair, Company A has grown to a respectable £13m ARR. However, growth has all but stopped now. It burnt through the £7m investment in just over three years and had to raise another £2.6m. It is still not through break even. More worryingly, even if we strip out growth costs, the company would still be loss making (steady state EBITDA ~ -£1.3m).

Company C: Solid investment

Let’s jump to Company C. This has been a great investment. It is now at £22m ARR, growing 11% per year and has reached break even without needing any more cash. It is dropping £1.7m EBITDA whilst still growing, and if we strip out growth costs, its ‘steady state’ EBITDA is £3.5m.

Company B: Big win… eventually

Company B is a really interesting one. After 5 years it is smaller than Company C at £17m ARR. It burnt though the £7m investment in 23 months and needed to raise a further £4.6m — much worse even than Company A. However, it has reached break even (just). More excitingly, it is now growing the fastest at 18%, and if we strip out growth costs its steady state EBITDA is £4.1m. So it is poised to become a more profitable business than Company C and is arguably a more exciting business (depending on your risk appetite).

So, could we have predicted this outcome?

We should have seen this coming.

Well Company A had a LTV:CAC ratio of 2x which should have been a pretty clear warning that it would struggle to become profitable.

Company B had a super high LTV:CAC (15x) which highlights its potential to be a ‘big win’. However, its long CAC Payback period (24 months) was a warning that it would take a lot of cash and a long time to get there.

Company C had a solid LTV:CAC of 5x and a similarly strong CAC Payback of 12 months. This should have told us that it would get to a good level of profitability without burning too much cash. A nice, lower risk, investment even if Company B ends up being the bigger win.

So despite all three businesses having the same P&L, we could easily have predicted their divergent outcomes, just by looking at two metrics.

Avoiding traps: when to invest and when to hold back.

Finally, let’s look at how Company A and Company B evolved over time. This will demonstrate how unit economics can help us to avoid traps when deciding whether or not to invest in sales and marketing. We will ignore Company C for now because it is straight forward — a good investment from the get-go.

Take company A (red line) first. Because it has such a quick CAC Payback (6 months) it was able to acquire new customers and revenue very fast. It grew faster than the other two companies initially and after twelve months it had grown ARR 5 fold to £10m (left hand chart). Consequently its burn had come down the most, to about -£2.5m after 12 months (middle chart), and it had burnt through the least amount of cash, just under £4m (right hand chart).

However, because churn was so high (hence low LTV:CAC at 2x), as soon as it reached any scale, it had to invest huge amounts in sales and marketing to replace churning customers just to tread water. By 24 months, almost all of its sales and marketing spend was going on churn replacement rather than new growth and so growth all but stopped (left hand chart). EBITDA never got to break even and plateaued at -£1m (middle chart). The business continues to lose money today and will never become profitable (dotted line).

The trap: in the first 12–24 months, management could have looked at the stellar growth rate and decreasing burn and decided that everything was going smoothly. It would have been easy to make the mistake of investing further to accelerate growth when in reality they needed to do the exact opposite — cut sales and marketing spend and focus on fixing churn. A quick look at LTV:CAC would have told them this.

Company B (orange line) has a long CAC Payback (24 months) so it took a long time and a lot of money to get going. After 12 months it had only reached £5m ARR (left hand chart) and after 3 years it was still the smallest company despite spending the most on sales and marketing (right hand chart).

However, because it has such low churn (hence high LTV:CAC at 15x), as it began to grow it gathered momentum. The customers it acquired (at high cost) stuck around and spent lots of money. By the end of 5 years, it has a large, stable, base to build from and almost all new investment goes into growth. By year five it is growing the fastest (left hand chart) and is through break even (middle chart). Importantly, because it has a stable base of revenue, it can chose to ‘turn-off’ growth spending at any time to increase profit (dotted line, middle chart).

The trap: management may have lost their nerve and chosen not to invest further when confronted with sluggish growth and high burn early on. This would have been a mistake. Now is exactly the right time to accelerate sales and marketing to win market share and push through the cash trough (right hand chart). Armed with CAC Payback and LTV:CAC numbers, management could have seen what was going on and had the confidence to press on.


Over the last two articles I have demonstrated the importance of LTV:CAC and CAC Payback. Management teams need to be totally focussed on keeping LTV:CAC above 3x and driving up towards 5x. Almost as important is keeping CAC Payback down, ideally below 12 months.

I will discuss various approaches that management can take to improve LTV:CAC and CAC Payback in my next post.


Note: this analysis assumes that the addressable market is large enough, and the competitive environment stable enough, to maintain constant metrics. This is a simplification designed to isolate the impact of metrics from other important factors.

SaaS Metrics — What really matters?

At Smedvig Capital, one of the most common topics we end up discussing with entrepreneurs is metrics.

Investors obsess over metrics because they provide an objective measure of the current and future health of a business. But for the same reason, they should also be an essential part of the entrepreneur’s tool kit.

However, with so many metrics out there now, choosing and making sense of the most important ones can be a daunting task.

When we discuss metrics with founders, they usually ask three questions:

  1. Which metrics are the most important?
  2. What do ‘great’ metrics look like?
  3. How can I use those metrics to add value to my business?

Last week we gave a presentation to a room of SaaS CEOs at Silicon Valley Bank where we tried to answer these three questions from an investor perspective. Over a short series of posts, I will lay out our answers one at a time, starting with “which metrics are the most important?”.

Ultimately, only two questions matter.

The ‘value’ of your business will be driven by two specific questions:

By ‘maturity’ we mean, once a business has reached a ‘fair’ share of its potential addressable market and has stopped investing heavily in growth.

These two factors will eventually define the financial return to the founders, the management team, and the investors.

So how can we go about answering these questions for an early stage business?

These questions are tough to answer.

Sadly, this is easier said than done. Most early stage businesses are investing heavily in growth, growing really fast, and losing lots of money. This makes it difficult to answer these two key questions simply by looking at the P&L.

With SaaS companies, the problem is exacerbated because value is realised through recurring revenues spread over a long period of time. Businesses typically have to spend a significant amount of sales and marketing budget upfront to acquire a customer (Customer Acquisition Cost, or ‘CAC’) and then receive regular, relatively small payments over a long period of time.

This means that high top line growth can mask a fundamentally flawed underlying business, and conversely, many great businesses may need to burn through a lot of cash before realising their potential.

So how can we assess the potential of a business if the P&L can be so misleading? The answer is unit economics, and in particular, two ‘killer’ ratios that tell us everything.

Luckily, two ratios tell us everything.

By looking at the economics of a single (average) customer, we can get a sense of how the economics of a businesses will unfold as it scales.

There are many different metrics of unit economics, which can tell us about different aspects of business performance. But there are two specific ratios, which tell us how all these different aspects aggregate up to answer our two fundamental questions.

These two ratios are ‘Lifetime Value to Customer Acquisition Cost’ (LTV:CAC) and ‘Customer Acquisition Cost Payback Period’ (CAC Payback).

LTV:CAC is the ratio of the total gross profit we expect to receive from an average customer during its total lifetime, versus the average cost of acquiring a customer (sales and marketing spend).

LTV:CAC is a powerful metric because it tells us how profitable the business will be at ‘maturity’. High LTV:CAC means high profitability.

CAC Payback is the number of months of recurring gross profit from an average customer, that it takes to payback the average cost of acquiring a customer (sales and marketing spend).

CAC Payback is an indicator of how much sales and marketing spend will be required for a business to reach a certain size. It is therefore a great proxy for how much investment the business will need in order to reach its next milestone. High CAC Payback means high cash burn.

I will discuss in more detail how these metrics are calculated in a later post.

So the answer is…

LTV:CAC tells us how profitable a business will be at maturity and CAC Payback tells us how much cash it will take to get there. Therefore, these are the two most important metrics and entrepreneurs should monitor them religiously.

These two metrics are not only vital for proving the potential of your business during fundraising but should also be used as a constant barometer of business health.


In my next post, I will demonstrate the impact of these metrics through a worked example and will try to answer the question “what is a ‘great’ LTV:CAC ratio and CAC Payback?”.