Targeting & ICP
How to Target Companies by Employee Count
Employee count is a useful proxy for company scale and complexity, but it's a proxy, not the actual thing you care about. It works well when headcount genuinely correlates with the buying process, budget authority, and need for your product. It works poorly when a company's employee count doesn't reflect its actual operating scale, which happens more often than the filter's popularity suggests.
Practical guide · Published August 22, 2026 · Written by Jeffrey Huis in 't Veld
Why employee count is a popular filter
It's widely available, easy to filter on, and roughly correlates with organizational complexity for a lot of businesses. A company with 500 employees usually has more layers of decision-making, more budget, and a more structured buying process than a company with 15, which makes headcount a reasonable first-pass filter for many B2B products.
Where it breaks down
The correlation weakens in labor-intensive industries, where headcount reflects workforce size rather than operating scale or budget. A 300-person staffing agency and a 300-person software company are not comparable in revenue, budget authority, or buying complexity, even though they'd pass an identical employee-count filter. Relying on headcount alone in industries like this tends to produce a list that looks consistent but isn't actually consistent in the way that matters.
Choosing a sensible range
A useful range is usually derived from existing customer data, what headcount range do your best-fit customers actually fall into, rather than a generic assumption like "mid-market means 100 to 1,000." Where that data doesn't exist, a range grounded in your product's actual buying process, who typically has budget authority at that scale, is a more defensible starting point than an arbitrary band.
Pairing it with other signals
Employee count works best combined with a second filter, revenue band, industry, or business model, that confirms the headcount is actually tracking the thing you care about. A company that passes both filters is a much stronger signal than one that only passes the employee-count filter on its own.
Frequently asked questions
It depends on the industry. In industries where headcount tracks closely with revenue and complexity, it works reasonably well alone. In labor-intensive industries, it's much weaker without a second signal.
From existing customer data whenever it's available. That produces a range that actually reflects who buys and succeeds, rather than a generic industry assumption.
Revenue band or business model tends to work well, since either helps confirm that headcount is actually correlating with organizational scale for that specific industry.
Not directly, though a comparable idea applies, using a proxy signal that's known to correlate with what actually predicts fit, rather than relying on the proxy alone without checking it.
Wide enough to capture your realistic buyer range, narrow enough that companies at both ends of the range still share a comparable buying process. Too wide a range starts blending genuinely different types of buyers together.
Related topics
Work with Yotru
How Yotru uses employee count in list-building
When Yotru builds a target list, we treat employee count as one input, not the whole filter, pairing it with revenue band, industry or business model so headcount is actually confirming organizational scale rather than standing in for it alone. Where you have existing customer data, we'll ground the range in what your best-fit accounts actually look like instead of a generic mid-market assumption. .