Key takeaways

  • Location is the only required field. Combine 2 to 4 criteria alongside it, no more.
  • Combination logic: criteria within the same category work as OR, criteria across different categories work as AND.
  • The sweet spot is usually department head, director, or manager up to VP, not C-level.
  • Audience size: optimal 30,000 to 80,000 in the DACH region, retargeting from 300 up.
  • Audience expansion and the Audience Network: almost always off.

LinkedIn is expensive per click. That's exactly why targeting decides between success and wasted budget. No other channel lets you target as precisely by job title, seniority, industry, and company size. The price for that precision is that every imprecise filter costs you money right away. That same precision is exactly why LinkedIn's higher prices are often worth it in B2B, as the comparison with Meta shows.

Define your audience before you open Campaign Manager

The mistake usually happens before the first campaign even goes live: just diving in and clicking around in Campaign Manager. Work out your audience on paper first. Three questions are enough to sharpen it:

  • Who exactly? For example, HR leaders in the DACH region at companies with 51 to 1,000 employees. The more concrete your ideal customer profile, the less wasted spend.
  • What message? Which pain point hits this exact role? For example, "cut recruiting costs, fill positions faster."
  • What offer? Matched to the funnel stage: a guide at the top, a webinar in the middle, a demo at the bottom.

Decide upfront which companies you want (size, industry, specific company names for account-based marketing, ABM for short) and which personas (job function, seniority, skills). That way, you only spend budget on audiences who can afford your offer and actually want it.

What targeting criteria does LinkedIn offer?

LinkedIn groups its options into a handful of categories. You don't need to use all of them, but you should know the logic:

  • Work Experience: job function, job title, seniority, years of experience, skills. One detail about job titles that costs a lot of money: it's a free-text field, people enter whatever they want. Filter only by title and you lose decision-makers with unusual titles. Combining job function and seniority is more robust, and usually cheaper because it's less contested. Example: LinkedIn files most sales leaders under the Business Development function. Exclude that function and you lose them.
  • Company: industry, company size, company name (for ABM or exclusions). Company size is the best available budget indicator, larger companies have more resources. One nuance: at small companies, you're talking to founders and owners who decide on their own, at large companies you're more likely talking to the department level, because the decision is spread across more shoulders there.
  • Education: degrees, schools, fields of study. Mainly relevant for recruiting and further-education offers.
  • Interests and Traits: the strongest option is member interests around purchases (product and service interests), meaning users actively engaging with a topic. General interests are only useful for awareness.
  • Demographics: age and gender. Usually leave these open, professional criteria matter more.
  • Location: the only required field.
  • Matched Audiences: your own data (more on this shortly).

The combination logic matters: LinkedIn links multiple values within the same category with OR, and criteria from different categories with AND. Stick to two to four criteria beyond location. Target too narrowly and you make your audience small and expensive.

Practical tip

Our favorite size for cold audiences is 30,000 to 80,000 people, sometimes a bit above or below depending on the offer. That runs against the instinct to go as broad as possible, but the real effect comes from narrowing down: the more specifically your message matches your audience, the more engagement you get, and the less budget gets wasted on irrelevant clicks.

Combinations that work in practice

A few patterns that reliably work in DACH B2B:

  • Job function plus seniority: reaches knowledgeable decision-makers without the expensive job title filter.
  • Skills plus seniority: when job titles are too vague, for example with niche roles.
  • Interests plus seniority: the lever to pull when even skills data is too thin, for example with very niche topics.
  • Industry plus company size plus job title: the classic combination for new prospects with no prior contact.

Behind the last two lies a two-step approach that almost always works better than going straight for the title when a role is hard to reach. Filter tightly on a single job title and you quickly end up with just a few thousand people, which is too few: LinkedIn barely serves the ad and the click gets expensive. So build up volume first through skills or interests, where you often get a multiple of that reach, then narrow it down afterward with seniority and company size. One catch remains: members maintain their own skills and interests, so the data is uneven. Use them to build reach, not as your only filter.

One example: HR leaders in the DACH region, combining location, seniority (department head through VP), company size 51 to 1,000, and job function Human Resources, comes out to around 38,000 people, comfortably in the sweet spot. Deliberately not filtered too tightly, so the click stays affordable. Segment further by the biggest pain point: HR leadership (talent shortage), finance leadership (cost control), and IT managers (security) each get their own message.

Address the committee, not the person

In B2B, a decision is rarely made by one person, it's made by a buying committee, typically six to ten people: the initiator, the subject-matter decision-maker, the budget owner, the technical gatekeeper, and the eventual user. Each role has a different pain point, researches independently, and needs a different message. Advertise only to the managing director, and you won't convince the people who have a say in the solution day to day.

Practical tip

Write out the buying committee cleanly once, before you build any audiences: one line per role with their biggest pain point and the right format. In practice, that means one ad group with its own message per role, instead of one ad for everyone. It costs ten minutes of upfront work and saves you wasted spend later.

Your own data beats LinkedIn's data: Matched Audiences and ABM

The strongest audiences are built from your own data. On LinkedIn, these run as Matched Audiences: website visitors through the Insight Tag, contact lists from your CRM, and company lists for ABM.

For ABM, company lists clearly beat contact lists, because the match rate reaches up to 90 percent instead of 10 to 20. ABM isn't just list-based targeting, though, it follows its own logic: first select the right accounts, then reach them with relevant messaging, then hand off warm accounts to sales. The Company Engagement Report in Campaign Manager shows you which target companies engaged with your ads. Those are exactly the ones you pass on to sales. For how to turn this into a complete program, from your target account list to the handoff, see the guide to LinkedIn ABM.

What you should always exclude

Exclusions aren't a minor detail, they save you budget continuously:

  • Competitors (via company name) and your own company.
  • Existing customers, so you don't pay for contacts you've already won.
  • Very small companies (1 to 49 employees), who rarely buy your offer.
  • Interns, entry-level hires, and unpaid positions.
  • Your own company's followers, who you already reach organically.

After the first week, check the Demographics tab: which segments barely click, recruiters or the advertising industry, for example? Exclude those too, and shift the budget to the segments that matter. For how to systematically derive the right exclusions from bad leads, see the guide on lead quality.

Three filters you're better off avoiding

Not every filter LinkedIn offers delivers on its promise. Three look tempting but lead you astray, because the data behind them is unreliable:

  • Company growth rate: LinkedIn calculates it from headcount. After a restructuring, a company can shrink and still have more budget. So this filter can sort good accounts right out of your audience.
  • Revenue: how LinkedIn sorts companies into revenue brackets is opaque and often doesn't match reality. Unreliable as a standalone criterion.
  • Age: LinkedIn estimates it from years of education. That's imprecise, and in B2B, role and seniority are the better signals anyway.

The order of data sources, on the other hand, is a clear recommendation: if you have enough website traffic, start with retargeting, then contact and company lists, then pure profile attributes for new prospects, and finally Predictive Audiences, but only with a large, clean base to build from. LinkedIn's real strength lies in combining these filters with retargeting to qualify your website traffic.

Fine-tuning settings almost nobody uses

A few small switches make a big difference and are almost always overlooked:

  • Set the language to English. Sounds paradoxical, but it's correct: many German-speaking professionals use LinkedIn in English. Choose German and you exclude them. English covers everyone, including German profiles.
  • Set location to "Permanent Location." That way you only reach people who actually live in your target market, not business travelers or tourists who happened to be logged in there.
  • Split large audiences. Above roughly 100,000 people, it's better to split into two ad groups, for example by company size. 120,000 becomes two clean groups of 40,000 to 70,000 each, and you can evaluate their performance separately.
  • Product interests for software. If you're advertising a software product, use the member interests around purchases category. It identifies users who are actively researching a solution like yours right now.

Two switches you almost always turn off

Audience expansion and the Audience Network are on by default, and in B2B they belong off, because both dilute the exact audience you just carefully built. The two-minute check for this, and the risks in detail, are covered in Optimizing Your Campaigns.

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The Targeting Playbook

The targeting steps, the best criteria combinations, and our exclusion list, all in one compact playbook that lets you set up your first converting audience in under an hour.