A major problem for private market investors – be it private equity, venture capital, or corporate development – is finding private company information.
More accurate revenue estimates result in a more accurate view of the company’s scale and if it sits within your investment thesis or not. If not, you would rather know that sooner rather than later.
To get this accurate revenue estimate, you need accurate data. But where can you find it for private companies? And will it take you and your team too much valuable time tracking it down?
Another wrench: Companies grow and shrink constantly. No database can house accurate information for long even if they have accurate data to begin with. The data is hard to come by particularly for middle market dealmakers whose universe of potential targets could be in the thousands of companies.
There are ways to get highly accurate revenue estimates if you have unlimited time. You can sit outside a law office and count their parking spaces to get a sense of how many employees work there. You can stake out a restaurant and count the customers that go each day. Plug your findings into a simple equation and come up with a highly accurate estimate. If you have unlimited time, private company revenues can be solved.
But you don’t have unlimited time and are often tracking a list of hundreds, if not thousands, of targets at any given time.
So what are the solutions to find revenue estimates?
The most common data point that investors use to calculate a revenue estimate is the revenue per employee model.
Can a revenue estimate equation be that simple?
According to Sanjay Menon, a Chartered Financial Analyst (CFA) and data scientist at Grata, “If your inputs are good, your calculations can be simple. It’s easy to do, it’s hard to do well.” Here are the issues dealmakers run into.
While sales data per industry is a US government published data point, employee counts for each company are not as accessible.
LinkedIn has made it easy for investors to see a company’s self-reported employee count, but there are some issues to consider:
There’s a wide array of employees at a given company. Does it make sense to calculate them all into your revenue estimates? They can be accurate and a good sense check, but hard to do at scale.
More complex revenue estimates consider revenue generating employees differently. Revenue generating employees will look different across sectors, they could be quota carrying sales reps for a technology company, doctors for an outpatient clinic, or lawyers for a law firm.
For some revenue by employee models, the equation includes estimated employee salaries. The US Bureau of Labor Statistics (BLS) publishes wage data by industry. Applying salary data to your models can help you sanity check your answer and set the lower bound for your revenue estimates, since any profitable business has to generate revenue greater than or equal to salaries.
“Profitable,” however, can sometimes be a big assumption. What about unprofitable businesses like venture-backed startups?
This is where the funding revenue model can be used. Funding is a strong data point that dealmakers should consider when estimating a company’s revenue.
Has a company received pre-seed funding or a Series D round? This will impact venture capitalists more than private equity firms, but is important to consider if your investment mandate includes investor-backed companies.
For example, if you know the round size and series, you can probably guess the revenue based on industry benchmarks. It makes sense because startups and VCs use round sizes and series names as “unspoken code” for a company’s revenue. A pre-seed company, for example, is code for “not generating revenue” in the venture world, while a Series D company and beyond is more likely to have meaningful revenue.
Finding a company’s mentions online – local newspapers, podcasts, awards, and social media – often yield valuable information about a company’s revenue in plain sight. Maybe they hit a milestone? Maybe they’re celebrating? Not only is this a good way to estimate a company’s revenue, but it also gives you a good reason to reach out and start a conversation if you’re interested in investing.
Even if revenue is not explicitly mentioned or shared in a conversation, you can use proxies of scale to estimate revenue. Every company has their gold standard. They may mention a fact like they have “100 happy customers” or “1000 members” or “100,000 subscribers” or “1,000,000 items sold.” You may see these numbers in a press release or even on the company’s own website as a way of building credibility. When you find a metric of scale, multiply it by the company’s pricing to estimate revenue.
Talk to industry experts. They often know the scale of companies in their industry. They can also help determine if you are using the correct benchmarks and if your industry standard is up-to-date. Better yet, consider talking to former employees of the companies you are evaluating. Even if they don’t know the exact revenue, they can give you a sense of scale.
Grata’s deep search technology, and data science, eliminate digging through multiple websites to find the information you need to estimate a private company’s revenue. Start sourcing smarter. Set up a demo.
