So much is being said and written about AI. I wrote an article where I attempt to break down what’s here-and-now and what’s not, and what we should do about it.
Machine learning techniques have come of age, and will be harnessed to advance human potential by increasing worker productivity and alleviating mundane tasks. I argue that what we are seeing is an acceleration in machines’ abilities to perform tasks that they have already been better than humans at for decades. However, moving towards the broader vision – and threats – of AI and AGI would require significant additional breakthroughs.
Every entrepreneur, operator and investor active in the enterprise and SaaS space has heard of Sales Efficiency metrics such as Magic Number, CAC Payback and LTV/CAC.
Once at growth stage, Sales Efficiency or Unit Economics is one of the most important quantitative metrics that can help you determine whether you have a viable business, course correct as needed, and help inform various facets of strategy.
Yet, given the many challenges around measuring it consistently, the subjectivity involved, and confusing messaging around so many SaaS metrics, many tend to underestimate its importance.
Some focus only on the unit economics per sales person, which is necessary, but not sufficient.
Subscription oriented businesses lose more money the faster they grow, especially at the scaling stage (~$5M+ ARR, repeatable sales model in place). This, as we know, is because such businesses need to spend a significant amount of capital up front to hire and train sales people, then acquire and set up customers, and recoup value over time as the customer pays the monthly or annual subscription fee. Given the time difference between when the CAC investment (S&M expense) is made, and when the returns (contribution profits) are generated, high growth subscription businesses require significant upfront investment in customer acquisition. The more customers a SaaS business acquires, the deeper the total trough of losses.
The losses typically accelerate as the business grows from $5M ARR to $50M ARR, and looks to add higher levels of ACV each year. A rapidly growing SaaS business could have a rising burn rate for a good reason — the business is acquiring customers fast, and these customers will eventually be profitable for the business. However, a company could also be incurring heavy losses if it has an unviable business, via sub-optimal product/market fit, an inefficient sales or marketing organization, acquisition of marginal customers, operating in unprofitable geographies or inadequate pricing.
Every CEO, management team member and board member of a SaaS or B2B company that is losing money needs to understand very clearly which one of the above it is.
It is paramount to understand whether you would deliver returns on capital invested on customer acquisition — just like any other investment you would make in your personal or professional life. The Customer Lifetime Value (LTV) needs to eventually generate sufficient return on the Customer Acquisition Cost (CAC), to offset R&D and G&A expenses, reinvest into growth, and eventually generate profits. The commonly accepted rule of thumb, especially amongst venture investors and venture-funded companies, has been that of LTV/CAC > 3X for building a sustainable business. This benchmark has a good reason, and we illustrate this with data below. A simple explanation is as follows. For SaaS businesses at scale (~$100m revenues), R&D and G&A together typically average at 30–35% of revenues, down from higher % numbers earlier in the life of the company. CoGS/variable expenses average at another 30–35% of revenues. The predominant swing expense at that point is typically Sales and Marketing. An LTV = 3X CAC (or S&M = 1/3 of contribution margins) leaves about a sixth of revenues as capital for reinvestment into growth, and eventually profits.
Understanding the impact of Sales Efficiency on the viability of the business
To illustrate the impact of Sales Efficiency on business viability and capital intensity, we model a hypothetical SaaS company that ended the prior year with $5M ARR, and targets getting to $100M ARR by end of Year 5 (a commonly accepted threshold for considering an IPO or large M&A). We assume R&D and G&A expense trajectory in line with a basket of public comps, starting at levels consistent with Series B or C stage startups, and approaching an aggregate of 35% of revenues at $100M revenue run rate. We made market-based assumptions for contribution margins (70%) and simple assumptions for annual logo churn (12%) and dollar churn (-5%). Contribution margins adjust for not only typical CoGS items but also any account management and retention related expenses. We use the undiscounted LTV for the purposes of this analysis. We capped the customer lifetime at five years for the purpose of LTV calculation, and modeled various scenarios with different levels of LTV/CAC. We then made assumptions for S&M spend in each scenario such that the company achieves $100M in ARR at the end of Year 5.
The growth trajectory of our hypothetical future unicorn is consistent with that of many successful SaaS companies that have gone public over the past several years:
While each of our scenarios has a similar growth cadence (and hence overlapping curves in the chart above), let’s look at the S&M expenses required to generate this trajectory for each scenario.
With our aforementioned trajectory of assumptions for other expenses, the EBITDA numbers look as follows for this company at various levels of Sales Efficiency.
The difference between scenarios is stark. With an LTV/CAC of 4X, our hypothetical company is close to EBITDA profitability in Year 6 with $116M GAAP revenues, while with LTV/CAC of 2X, the company is still losing $45M a year, or nearly $4M per month in Year 6!
Now let’s look at the Capital Intensity in each scenario. The chart below shows the cumulative losses during the first five years after $5M ARR for this company. This analysis ignores the impact of up-front cash collections/deferred revenue and stock based compensation expense for simplicity. These vary significantly by company, but the trend below will hold after these adjustments.
With an LTV/CAC of 4X, the company requires $80M and gets to profitability in Year 6, while with 2X, the company requires over $180M in Years 1–5, and is still losing $45M per year in Year 6. This difference not only has a significant impact on returns for founders, employees and investors, but also brings to question viability of the company in scenarios where LTV/CAC is under 3X. While many kinds of companies are able to raise financing at preferred terms in bull markets, in normalized market conditions it would be hard for the company to continue raising private financing to fund its large losses during Years 1–5 in the first two scenarios above. On the other hand, in the last two scenarios above, the company may choose to continue to grow faster in Years 4 and beyond if it sees a large market opportunity.
We have used LTV/CAC as the primary Sales Efficiency metric here, and similar analyses can be conducted using other metrics such as CAC Payback and Magic Number. LTV/CAC, while harder to accurately measure, is more comprehensive and predictive.
How should you act on this?
At any given point of time, a business can choose to grow faster by deploying more capital into Sales and Marketing. But this only makes sense as long as this is done while maintaining the right Sales Efficiency. The growth rate and organizational processes (sales hiring, incentivize structures, focus on cross-sells and up-sell, customer targeting, conversion funnels, lead sources) need to be tempered and monitored closely to keep the overall company-level LTV/CAC in a healthy operating zone.
Based on looking at numerous growth stage subscription-oriented businesses over the years, here are my observations and recommendations based on Sales Efficiency, as evidenced by LTV/CAC. The absolute levels will vary by specific nature of business, current stage and other factors.
LTV/CAC greater than 5X: If the underlying methodology and assumptions are reasonably accurate, then an LTV/CAC at this level indicates that the business currently has significant immediate growth potential. Moreover, you are possibly leaving some growth opportunity on the table. Consider expanding your sales team, marketing channels or vertical focus more rapidly than you have been doing so far. You have the wind at your back. However, when we see very high numbers for LTV/CAC for high growth companies, it is often due to miscalculated LTV or CAC, e.g. during a company’s early days when the CEO and management team are doing most of the selling those efforts may not be fully incorporated in CAC, or very scalable. Another common pitfall is using an artificially low churn number (rather than renewal rates) at a high growth company to come up with an unreasonably high customer lifetime. I recommend capping the lifetime for the purpose of these calculations at 4–6 years depending on type of customer you serve, and taking a hard look at the underlying methodology if you have a 5 year LTV/CAC that is more than 5X
LTV/CAC of 3–5X: This is the optimal zone. Continue executing and find ways to augment your expansion rate without having the LTV/CAC fall below 3X
LTV/CAC of 2–3X: The company can potentially build a viable business, but it would be unlikely to generate VC-style growth or returns on total invested capital. These levels may be viable for later stage or public companies which have lower R&D and G&A costs as % of revenues, and potentially lower return expectations on invested capital
LTV/CAC < 2X: The business is unviable at present, and cannot continue to grow with current contours and growth rate. Our recommendation is to optimize Sales Efficiency by thoroughly reviewing the sales organization, incentive structure, sales targets, vertical focus, product expansion and partnership strategy; or trim the company’s growth rate to focus only on profitable channels, customers and geographies
In a later post, we will touch upon some of the practical challenges and common errors with measuring Sales Efficiency, and share best practices we have seen around this. Here are is a summary of some key items I recommend — Customer Lifetime Value should be calculated net of all variable costs including customer service, retention expenses, hosting fees and any others; For calculating real churn rates for businesses with annual customer contracts, use renewal rates rather than churn rates, which may artificially look lower; Use customer cohorts for understanding account expansion rates; For the purposes of the LTV/CAC calculation, cap the customer lifetime to a reasonable number, as no business is likely to have a customer lifetime of decades across its customer base in this era of rapid disruption cycles.
Given the aforementioned implications of Sales Efficiency on company viability and returns on invested capital and time, CEOs, management teams and boards would be well served by taking a close look at this metric as they finalize their strategy and budgets for 2017 and beyond.