How to Estimate Any Private Company's Revenue in Under 5 Minutes (Without a $40K Subscription)

The Raw Ingredients Already Exist

Enterprise data subscriptions run $12K to $40K per year and the numbers they contain are frequently 12 to 18 months stale. Even the best platforms cover a fraction of the 6+ million private companies in the US. The coverage gap is enormous, especially below $50M in revenue where the vast majority of lower-middle-market targets sit.

But the raw inputs for a solid revenue estimate are sitting in free public sources right now. They are scattered across a dozen places, which is why most people assume the data simply does not exist. It does. You just have to know where to look and how to combine signals.

This is the exact triangulation process our team uses. It produces estimates within 15 to 25 percent of actuals, validated against companies that later disclosed financials through acquisitions or Inc. 5000 listings. The whole thing takes about five minutes once you have the muscle memory.

Step 1. Get the Employee Count (60 Seconds)

Employee count is the single strongest predictor of private company revenue. The relationship between headcount and revenue is remarkably stable within industries because labor costs are 40 to 70 percent of total expenses for most businesses. You cannot hide employees. They have LinkedIn profiles, they leave Glassdoor reviews, they file state taxes.

Where to look.

• LinkedIn company page (shows a range like 51 to 200 or 201 to 500)
• Actual LinkedIn profile count using the "Current company" filter (far more precise than the self-reported range)
• Glassdoor employer profile
• State annual reports (California, Texas, and Florida require employee disclosures in various forms)

Step 2. Apply Industry Revenue-Per-Employee Benchmarks (30 Seconds)

Once you have headcount, multiply by the appropriate sector benchmark.

A B2B SaaS company with 140 employees multiplied by the $215K median gives you roughly $30M in revenue, with a defensible range of $21M to $49M. That is already enough to determine whether the company is in your strike zone.

Step 3. Cross-Reference with Two or Three Additional Signals (2 to 3 Minutes)

The employee-based estimate is your baseline. Now you corroborate.

Government Contracts (Free via USASpending.gov)

If the company has federal contracts you have exact dollar values for that revenue stream. Even if government is only 20 percent of their total business, a $6M contract floor implies $25M to $35M in total revenue. This is the highest-reliability public signal that exists.

Inc. 5000 or Deloitte Fast 500 Listings

These lists require companies to verify revenue through audited figures. The exact numbers are not public, but the 3-year growth rate plus the year of listing let you back-calculate with reasonable precision. A company showing 300 percent 3-year growth and listing in 2023 with a minimum $2M revenue threshold is doing $8M or more today.

Funding Rounds and Implied Valuation

If the company has raised venture or growth equity, stage benchmarks tell you a lot. Series A SaaS companies typically sit between $1M and $5M ARR. Series B is $5M to $20M. Growth equity implies $20M to $100M+. The multiples at each stage are well documented.

Job Posting Velocity

A company with 30+ open roles is almost certainly doing north of $20M in revenue. They would not hire that aggressively without the revenue to support it. Enterprise sales roles with $100K+ OTE imply $30M minimum.

Step 4. Triangulate and Pick the Conservative Estimate (30 Seconds)

Now you have 3 to 5 independent data points. The decision framework is simple.

If signals converge within 20 percent of each other, you have high confidence. Take the midpoint.

If signals diverge, take the lowest credible estimate. You are underwriting, not selling. Conservatism protects your process.

If one signal is vastly different from the others, investigate why. Maybe they outsource heavily (high revenue per employee), or they are pre-revenue and burning cash (high headcount but no product-market fit yet).

Worked Example

Let's size a hypothetical B2B SaaS company called TechFlow Solutions.

1. LinkedIn shows 220 actual employee profiles. At the $215K median that gives us a $47M baseline.
2. USASpending shows $8.2M in active federal contracts. Total revenue floor is $30M+ assuming government is not their only vertical.
3. Inc. 5000 listing in 2022 and 2024 with 180 percent growth in the first year. Trajectory implies $40M to $55M current.
4. 18 open roles including a VP Sales and 4 enterprise AEs. Consistent with $40M+ revenue.
5. Raised $15M Series B in 2021 at roughly $80M valuation. Implied $10M to $15M ARR at raise, three years of growth puts them at $35M to $50M current.

Everything converges at $40M to $50M. High confidence. Conservative pick is $40M. Total time spent, about four minutes.

What This Means for Your Process

If you evaluate 10 companies per week, this method saves roughly 30 to 40 hours of analyst time. More importantly it changes the economics of your funnel.

You screen faster. You drop unqualified targets in minutes instead of days. You walk into first meetings knowing their approximate size, which signals competence to sellers and intermediaries. You avoid the embarrassing mismatch of calling a $5M company about a $50M+ mandate (or vice versa).

The math on analyst productivity alone makes this worth systematizing. A 2-person deal team that can screen 15 companies per week instead of 4 has fundamentally different deal flow economics over a fund life.

What We Built

Internal Insight automates this entire triangulation. Employee count, industry benchmarks, government filings, press signals, job data, funding history. Synthesized in seconds with full source attribution. Same rigor, zero manual work.

Try it free →