Venture capital has a reputation for romanticising its approach to investment decisions – putting the charismatic team, exciting market or compelling product analysis before ‘the financials’. 

Ultimately, financial metrics present the unvarnished picture, although they must be interpreted with care to ensure their usefulness. Revenue, profits and cash flow are analysed meticulously for public companies, and greater rigour around the analysis of early stage startups may benefit them too.

Metrics such as lifetime value, churn and customer acquisition cost provide a dashboard of a startup’s progress, and its prospects to ultimately become a heavyweight. It can predict growth in both revenue and efficiency for the years ahead, the second of which is particularly important when a startup doesn’t yet generate profits.

Metric analysis to calculate efficiency

In the early days of a startup, it’s important to analyse the metrics that demonstrate efficiency, because the company may be putting in more resources of all kinds – including money and time – than they are getting out. Identifying opportunities to improve efficiency and growth will tell you about the future of a company and its potential. 

Understanding of your unit economics – the profit of serving a single customer – is paramount. Ideally, I first open up the financial model and let a startup explain itself through numbers. 

For me, there are three types of motion within a business that I want to understand: how it gets moving, starting from zero to signing its first few customers; and afterwards the two potential causes of slowdown or halt – either encountering a large external force that stops the business in its tracks (difficult to mitigate at any time), or more likely, a form of resistance or obstacle that builds up over time to slow its revenue growth. 

The data which depicts how this business ‘moves’ tells me an incredible amount about whether it is a worthwhile investment.

Data over time

To break this down further, I look at data in the context of a company’s timeline. At the early stage of investing, my goal is to establish whether a startup showed strong acceleration from zero to first delivery, and whether it has the potential to keep up its momentum. This is measured in two ways.

Firstly, I evaluate the rate at which branding converts to customers and analyse the pipeline conversion from qualified lead to signed client over a short period of time. The strongest startups show a growing number of newly closed deals every month, compared to the months prior. 

Secondly, I look at the CAC (customer acquisition cost) payback time which calculates the number of months it takes to break-even when acquiring a new customer, i.e. the sales and marketing expenses, over the gross margin earned per customer. For larger annual contracts (if available), a payback of less than twelve months would be great, as you will generate net profit from that customer in the first year. For smaller monthly contracts, a payback of less than three months is strong. Obviously, this assumes that not all customers churn after the first month.

Why an operating background is crucial to investment decisions

Moving onto the later stages of a startup, I consider the startup’s momentum over the past year, and what resources are required to prevent deceleration. This too, is measured in two ways.

I first look at the net dollar retention rate, a metric which depicts whether a startup is generating more revenue from existing customers than it is losing from customers churning or downgrading. A strong DRR of 120% shows that your existing customer base is growing 20% YoY, through upselling or cross-selling, already net of any churn encountered.

I then look at the cash burn multiple, calculated as net new revenue for the year divided by the total cash burn for the year. Essentially it shows how well you convert short-term viability (the burn rate) into long-term viability (continued revenue). Here we are looking for an outcome of 1x or higher to excite investors.

Metrics for success

Ultimately, excitement levels for investing are driven by strong pipeline conversion and CAC payback time at the early stages (pre-Series B stage). From there, my work turns into a forensic series of checks to make sure that everything we see on the surface is accurate and built on secure foundations. 

At the later stages of a startup, we can predict the journey the business is taking with greater accuracy. Trend lines can be drawn on every line item of the P&L and cash flow statement. My investment decision shifts to assessing the net dollar retention and cash burn rate. If solid, a unicorn exit might be on the horizon.

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