Why B2B Brands Need to Stop Relying on LinkedIn’s Native Targeting

You know that feeling when you’ve built the “perfect” LinkedIn audience, but the results still fall flat?

We’ve been there too.

It’s not that LinkedIn’s targeting doesn’t work; it’s just that you aren’t steering it, it’s steering you.

We get it, you feel like you’re in control. You can choose titles, seniority, functions, skills, industries, all the knobs and levers that give you full confidence in your setup. 

But if you only use the native audience targeting, you’ll get what most others get: expensive reach, diluted relevance and inefficient ad spend.

We learnt this first-hand at farsiight.

When we started running LinkedIn campaigns for our own brand, we used all the standard filters: “Marketing Manager”, “Founder”, “E-commerce Director.” The ads got clicks, but the pipeline didn’t move. When looking at the actual companies we were targeting, it became very clear why. It wasn’t that LinkedIn didn’t work; it was the audience strategy unpinning it. 

We were targeting over 34k companies, so our budget was being spread so thin across companies we actually wouldn’t want to speak to in the first place. 

So we rebuilt from the ground up. 

The shift wasn’t another targeting hack or AI trick; it was a smarter way to approach our ICP. We stopped letting the platform decide who we reached and started treating LinkedIn like an ecosystem: one fuelled by clean first-party data, thought leadership, and long-term intent.

Start with your own list, not LinkedIn’s 

If you want to take control of your targeting, the first step is to build and upload your own audience lists. Instead of relying on LinkedIn’s native filters, create a curated list of companies that match your ideal customer profile. 

You can do this by exporting data from your CRM, scraping company domains, or using enrichment tools like Clay and Apollo to identify businesses that fit your size, industry, and location criteria.

Once you have your list, upload it as a Matched Audience in Campaign Manager. LinkedIn will map those company domains to active users on the platform, giving you a custom audience that’s far more precise than any title-based filter.

That’s the theory. Here’s where we got it wrong the first time.

Our first big mistake

Our first big mistake after leveraging native targeting was outsourcing the most important part of the process: the audience creation. 

We paid someone on Upwork to build a company list based off our inputs and uploaded it straight into Campaign Manager. Again, the in-platform results looked promising until we realised again that 2 in every 3 companies we were targeting were not ICP. The list hadn’t been cleansed, and most of the domains were irrelevant.

That was the turning point. 

Enrich before you advertise

We went back and rebuilt everything ourselves using Clay and ChatGPT. After manually reviewing each company, our list dropped from 7,500 to 2,500: smaller, sharper, and genuinely aligned with our ideal client profile.

Yes, CPMs rose as the audience shrank. But every dollar we spent was now going toward businesses we actually wanted to work with, B2B, SaaS, and tech companies with more than ten employees across Australia and New Zealand. The ads stopped feeling like broadcasts and started feeling like conversations with people who mattered.

An account list is only as powerful as the context behind it. We enriched every record with data points that shaped our messaging, things like headcount, sub-industry, and location. Clay handled the structural data, ChatGPT identified non-ICP, and our team verified everything manually.

The result? 

We weren’t just targeting “tech companies” anymore. We were targeting mid-market SaaS and IT businesses in ANZ, the segment that most often reaches out to us. 

Target humans, not job titles

Once our company list was solid, we turned our attention to the people inside it. The temptation is to cram every possible title into the mix, “Head of Growth”, “Demand Gen Manager”, “Marketing Director”, and hope the algorithm figures it out.

We build around functions and seniority, not job titles. We start broad, Marketing, Operations, and Founders, and layer seniority filters to reach decision-makers without excluding key influencers.

For us, Founders, CMOs, and senior Marketers consistently deliver the strongest engagement. We use Sponsored InMail to speak directly to decision-makers, while standard feed ads reach the broader teams who help shape recommendations. It’s a balance: decision-makers drive action, but influencers build consensus.

Offers that match the mindset

The most important lesson we’ve learnt: people don’t buy because you target them better , they buy because you meet them at the right moment with the right message.

At the top of funnel, we rely heavily on founder-led thought leadership. Most of our awareness comes from organic posts shared directly by Ben and me. The tone is informal, curious, and occasionally funny , humour performs surprisingly well when everyone else is taking themselves too seriously.

At the middle of funnel, we focus on social proof. Think client wins, testimonials, logo walls, and bite-sized stories that showcase what partnership with us feels like. These ads build familiarity and credibility.

At the bottom of funnel, we’re about to launch our Free Growth Roadmap offer , delivered via InMail to warm and high-intent accounts. It’s a full walkthrough of what a data-driven growth plan looks like, the same audit process we use to assess potential clients before they sign.

That combination , personality at the top, proof in the middle, and practicality at the bottom , is what turns clicks into conversations.

Patience over panic, play the long game.

One of the biggest mindset shifts for us was understanding how long LinkedIn actually takes to pay back. Only about 5% of our market is in-market at any given time. That means our sales cycle from first touch to signed client often sits between six and twelve months.

We track the usual metrics in-platform to guide creative decisions, CTR, CPM, CPC, cost per MQL, but our north stars are aCAC and opportunity creation. They’re what tell us whether the system is actually producing growth, not just engagement.

HubSpot houses the core reporting, with visibility dashboards in Fibbler so the team can see weekly trends. We’ve learnt to treat surface metrics as signals, not scores. A rising CPM isn’t always bad if it means we’re reaching the right people more often.

The takeaway

LinkedIn’s native targeting is a good fine-tuning mechanism, but it’s not the core part of your audience targeting. 

To build demand that compounds, you need to own your audience, enrich your data, speak to humans, and align creative with buying intent.

When we rebuilt our own campaigns this way, the numbers didn’t explode overnight; they matured. Fewer wasted impressions, more qualified conversations and a pipeline that clearly shows LinkedIn Ads is working.