Prospecting & Contact Data
How to Choose the Right Company Filters for B2B Prospecting
The right company filters are the ones tied to a real reason a company would buy. Start with industry, geography, employee count, revenue and business model, then add filters such as technology used or growth signals only when they clearly separate good fits from poor ones. A handful of well-chosen filters beats a long list of arbitrary ones.
Practical guide · Published September 20, 2026 · Written by Zaki Usman
Filters turn an ICP into a search
Your ICP says who is worth mailing. Filters are how you find them. A good filter is objective, available in the data you are searching and connected to why a company would buy. A poor one is easy to search on but says little about fit.
Industry
Choose industries because of a specific, explainable reason, such as a shared regulatory pressure or a common operational problem, not because they seem broadly plausible. Industry labels can also be too broad, so combine them with a second filter where needed. See how to choose industries for a B2B campaign.
Geography
Geography is a strong filter when it reflects a real reason, such as a service territory or a regional regulation. It is a weak one when it is used only because a boundary is easy to draw. Use it to narrow a list that is already filtered for fit. See how to target companies by geography.
Employee count and revenue
Employee count is a proxy for scale and complexity, and it works when headcount really tracks how the company buys. Revenue is similar, but for private companies it is often an estimate, so treat it as a range rather than an exact cut-off. See how to target companies by employee count.
Business model
How a company makes money often predicts how it buys. Whether it sells to businesses or consumers, runs on subscriptions or projects, or operates from one location or many can matter more than its industry label. This is especially useful when two companies in the same industry have very different needs.
Other filters worth considering
Depending on your product, technology in use, hiring activity, recent growth, ownership type or the customers a company serves can all separate strong fits from weak ones. Add these only if you can show they correlate with your best customers, and confirm the data source is reliable enough to filter on.
Combining filters
Start with three or four filters and separate the must-haves from the nice-to-haves. Must-haves define the list. Nice-to-haves can rank it, so the best fits are contacted first or receive a larger format. Too many hard filters at once returns a tiny list, and filters chosen only because the data exists tend to add noise, not fit.
Frequently asked questions
Usually three or four to begin with. Add more only if each one clearly separates good fits from poor ones.
Less than it looks. For private companies revenue is often estimated, so use it as a range and combine it with another filter such as employee count.
A must-have defines who is on the list at all. A nice-to-have is used to rank or tier accounts, for example to decide who gets a larger postcard.
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