— 7 min read

Accurate private-company revenue data is crucial for dealmakers. 

Information about revenue provides decision makers with a more complete picture of their target company’s scale and how well it aligns with their investment criteria. 

But finding that data can be challenging, especially for investors focused on private companies in the middle market.

Below, we dig into the various methods for calculating revenue estimates for private companies and the tools that can simplify the process.

Estimating Revenue for Private Companies

The ‘Revenue Per Employee’ Model

The most common method that investors use to calculate a revenue estimate is the revenue per employee model.

Can a revenue estimate equation be that simple?

Sanjay Menon, a Chartered Financial Analyst (CFA) and data scientist at Grata, says,  “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.

Who has the most accurate employee data?

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:

  • LinkedIn does not ensure these numbers are accurate. 
  • LinkedIn includes two numbers: 1) a range (e.g. 15-30 employees) and 2) the number of employees on LinkedIn. There is also no guarantee that the number of employees displayed on LinkedIn is in between the range they provide. Frequently, it is not. Choosing between those 2 dramatically affects your revenue estimate.
  • There are several underrepresented sectors. Tech and professional services may be well represented on LinkedIn, but others like commercial services and healthcare are not.

How does employee role play into the equation?

‍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.

Do salary estimates belong in the equation?

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?

Funding Revenue Model 

While a company’s recent funding rounds are more relevant to venture capital or growth equity investors, funding data can still help dealmakers gauge the target’s revenue. It’s also important to consider if your investment mandate includes investor-backed companies.

If you know the round size and series, you can probably guess the revenue based on industry benchmarks. Startups and VCs use round sizes and series names as “unspoken code” for a company’s revenue. A pre-seed company, for instance, is code for “not generating revenue” in the venture world, while companies at the Series D stage and beyond are more likely to have meaningful revenue.

Alternative Data Used to Estimate a Company’s Revenue

Hidden Mentions

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 they’re celebrating. Not only is this a good way to estimate a company’s revenue, but it also gives you a reason to reach out and start a conversation if you’re interested in investing.

Proxies and Pricing

Investors can also use proxies of scale to estimate a company’s revenue. 

For example, a company’s website or press releases might highlight statistics such as: 

  • “100 happy customers” 
  • “1,000 members”
  • “100,000 subscribers” 
  • “1,000,000 items sold”  

When you find a metric of scale, multiply it by the company’s pricing to estimate revenue.

Industry Experts

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.

Competitor and Industry Comparisons

Investors can also leverage a target company’s competitors and similar public entities to estimate its revenue. 

Look for publicly traded companies similar in size and scope to your deal target. If your target company has about 25% of the public organization’s employee headcount, divide the public company’s revenue by 4 to find an estimate for your target’s revenue.

Key Tools for Finding Private Company Revenue

If it sounds like these revenue estimate methods involve a lot of digging, it’s because they do.

Investors might luck out and find revenue data for larger private companies on financial sites like Forbes, Bloomberg, and Moody’s — but what about smaller, middle-market companies? To gather as much data as possible quickly, investors should leverage dealmaking tech platforms like Grata.

One of the most effective ways to gain a fuller understanding of a company’s size and scale is by analyzing comparable public companies in the same industry.

Grata’s recently launched Market Research tools provide holistic views of deal data and public comps, including:

  • Precedent Transactions
  • EV/Revenue
  • EV/Gross Profit
  • Margins
  • Growth 

Simply define your market using Grata Search, industry classifications, keywords, or a list.

Grata users can then sort precedent transactions by recency, deal value, or deal type to find the information most relevant to their target company. 

Because Grata’s AI has scoped the entire business internet, we can accurately identify and associate transactions with smaller companies that other deal databases miss.

To see how Grata can make your revenue estimating process more efficient and accurate, schedule a demo today

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