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Wanna learn what Linkedin ads mistakes to avoid from someone who made plenty? 😉 I have been running LinkedIn ads for two years now. In that time, I have wasted budget on mistakes I did not even know I was making – and watched hundreds of other B2B marketers make the exact same ones. The thing about LinkedIn ads mistakes is that most of them are silent. Your campaigns look fine on the surface. CTR is decent. CPC is in range. But pipeline? Nowhere to be found. That is usually when you realize something is off with your targeting, your budget allocation, or your campaign setup – not your creative. This post pulls from three sources: our own experience running ABM campaigns on LinkedIn ($490k spent, $5.29M pipeline), the ZenABM 2026 benchmark report (211 companies, 161,256 ads analyzed), and expert sessions from the ZenABM ABM Bootcamp with 600+ practitioners – including a session by Max Herzeg, who spent 2.5 years working at LinkedIn before becoming an independent ads consultant. I have organized these by category. Feel free to jump to what is most relevant for you! 
This is where most LinkedIn ad budget dies quietly. You will not see it in your dashboard. Your CTRs will look normal. But you are paying to reach the wrong people, and you will never see pipeline from it.
LinkedIn has a feature called the Audience Hub that lets you see exactly who you will reach before spending anything. Most people skip it and go straight to campaign setup. That is a mistake. LinkedIn’s targeting filters do not always work the way you think. The Audience Hub shows you the actual job titles, skills, job functions, and locations of the people in your audience. You can catch problems before they cost you money. To find it: go to Plan > Audiences > Saved > Create Audience. Max Herzeg, who worked at LinkedIn for 2.5 years and now consults on LinkedIn ads, calls it “the most important thing when it comes to campaign setup.” He recommends checking it before every campaign launch and after every exclusion change. 
This one caught me off guard. When you type a job title into LinkedIn’s targeting, you are not just targeting that exact title. LinkedIn creates what they call “super titles” – groups of titles it considers similar enough to bundle together. Here is the problem: these bundles can be wildly broad. If you target “VP of Engineering,” LinkedIn also includes engineering specialists, infotech specialists, and construction specialists in the same group. You think you are targeting 20,000 senior engineering leaders. You are actually reaching 100,000+ people, many of whom have nothing to do with your ICP. As Herzeg put it: “Lots of people don’t know that. They think they’re targeting exactly the usual job titles, but LinkedIn’s translation is different.” How to catch it: Enter one title at a time in the Audience Hub and check the sidebar to see what LinkedIn actually includes. Then add job title exclusions for the irrelevant ones. 
When you upload a target account list, LinkedIn needs to match your companies to their platform profiles. The CSV template asks for several fields – company name, website, etc. – but one field matters more than all the others: the LinkedIn company page URL. Without it, LinkedIn guesses at matches. And it guesses wrong more often than you would expect. You should be aiming for a 90%+ match rate. If you are seeing 60-70%, check whether you included the LinkedIn URLs. Fix: Always include LinkedIn company page URLs. Use tools like Clay to enrich your lists before uploading. After upload, spot-check a sample of matches manually. 
LinkedIn lets you target by industry and company size without uploading a list. The problem? Companies self-report their industry on their company page. Amazon might show up under “Internet,” “Retail,” or “Cloud Computing” depending on who set up the page. Company size is similarly unreliable. A company showing “201-500 employees” on LinkedIn might actually have 1,000+ because not all employees maintain LinkedIn profiles. These filters can work for broad prospecting, but for ABM where you have a defined target account list, always upload your list directly. Do not rely on LinkedIn’s filters to find the right companies for you. 
Here is a rule most LinkedIn advertisers do not know: exclusions always override inclusions. Say you are targeting Company A, but you exclude Company B. If someone works at both (which is common with advisors, board members, or people with two active roles), that person gets excluded entirely. The exclusion wins. The same problem applies to seniority exclusions. LinkedIn classifies seniority inconsistently – I have seen software engineers with 12+ years of experience classified as “entry” level. If you exclude “entry” seniority to filter out interns, you are also removing experienced ICs. Fix: Only exclude specific job titles. Never exclude broad categories like seniority levels or job functions. 
If you target the US and Europe in the same campaign, here is what happens: LinkedIn does not balance your daily budget across time zones. The US wakes up, starts consuming your budget, and by the time Europe comes online, the daily budget is already gone. Fix: Split campaigns by continent or time zone. If you must combine regions, check your demographics report to see if spend is distributed evenly.
LinkedIn lets you upload lists of individual people using their email addresses. Sounds precise, right? In practice, match rates are terrible. LinkedIn can only match if the uploaded email matches the one on someone’s LinkedIn profile – and most people use their personal email on LinkedIn, not their work email. Contact lists also get stale fast. People change jobs, and suddenly you are targeting the wrong company. When it works: Short-run campaigns like webinar follow-ups where you have fresh, verified emails. For everything else, use company lists with ICP filters layered on top.
Audience Expansion lets LinkedIn show your ads to people outside your defined targeting. For ABM, this defeats the entire purpose. You built a target account list for a reason – do not let LinkedIn override it. Even worse: this setting can silently reset after you edit a campaign. Check it every time you make changes. The same goes for the LinkedIn Audience Network (LAN), which places your ads on third-party apps and websites. Turn it off for B2B campaigns.
LinkedIn is the most expensive paid social platform. These mistakes make it even more expensive while delivering less.
Maximum Delivery is LinkedIn’s default bidding strategy. It is also the most expensive one. It optimizes for maximum ad delivery within your budget, but you pay for impressions regardless of quality. Manual bidding gives you way more control. Herzeg shared a fun fact from his time at LinkedIn: “Manual bidding is so good that LinkedIn actually hides it from you. They even tried to remove it, but users demanded it stay.” Here is how to use it:
The one exception: Maximum Delivery can work with Thought Leader Ads + brand awareness objective, where it sometimes delivers lower CPMs and higher reach. 
If you are spending $2K/month on a 300K audience, nobody sees your ads often enough to remember you. LinkedIn ads are not like billboards – they need frequency to work. Here are the benchmarks that actually matter:
| Metric | Cold Audiences | Warm Audiences |
|---|---|---|
| Monthly audience penetration | 30-50% of your audience | 70-90% |
| Impressions per person per month | 6-10 total across campaigns | 10+ |
| Impressions per creative before fatigue | 2.5-3 per person | |
Also keep in mind: only about 50% of your target audience is realistically reachable in any given month. Dead profiles, infrequent logins, inactive users – they are all still counted in your audience size. From our benchmark data across 211 companies: monthly ad spend has the strongest correlation with pipeline (Spearman rho = 0.511, p=0.002). Top performers spend $6,576/month – 144% more than the median. If you are running LinkedIn ABM on $1K/month, it is probably not enough. Btw. use our Linkedin ABM Budget Calculator to avoid budgeting mistakes! 
LinkedIn has no native frequency capping per company. Without it, your largest target accounts eat a disproportionate amount of budget. I have seen cases where the top 5 companies consumed 3x more impressions than the next 50 combined. There is a workaround using dynamic exclusion lists:
The list updates automatically, so you do not have to manually manage exclusions. Companies cycle in and out as their impression counts change. 
Running 15 campaigns at $500/month each means none of them get enough spend to hit the frequency benchmarks above. LinkedIn needs a minimum spend per campaign to optimize delivery. Fix: Fewer campaigns, more budget per campaign. Aim for $50-100/day per campaign. Cap at 4-6 ads per campaign. If budget is tight, consolidate. 
This one is surprisingly common. The objective you select determines how LinkedIn optimizes delivery, and picking the wrong one means LinkedIn is working toward a goal you do not actually care about. The biggest trap: the “Website Conversions” objective. It sounds like it should drive conversions, but in practice it is just a more expensive version of “Website Visits” that rarely delivers better results. If you want people to sign up for a demo or fill out a form on your website, use the Website Visits objective instead. Here is a quick reference:
Bonus tip for lead gen: try optimizing for clicks instead of leads. Clicks are cheaper because everyone else is bidding on leads. You can sometimes get the same conversion volume for less spend. 
Optimize for Performance” is LinkedIn’s default ad rotation. It sounds smart – let the algorithm pick the best ad. But “best” here means highest CTR, which is not always what you want. I have seen lead gen campaigns where the lower-CTR creative actually had a much better cost per lead. The algorithm would have killed it in favor of a high-CTR ad that generated fewer actual leads. When to use each:
These happen before you even log into Campaign Manager. And they are often the most expensive because they set up everything else to fail.
Herzeg told us this is the most common pattern he sees with new clients: “They want to start with targeting and campaigns right away. But they forget the planning. They start with LinkedIn and don’t look at the overall ABM strategy.” Before touching Campaign Manager, you need answers to: What is the commercial goal? What runs alongside LinkedIn (outbound, content, events)? When should sales follow up? What does your retargeting system look like? How will you measure success? If you cannot answer these, you are not ready to launch campaigns. You are ready to plan. 
Most companies sit on a goldmine of historical data they never look at before launching campaigns. CRM data, past pipeline, sales activity, Campaign Manager history, website analytics – it is all there. The question to answer first: where does your revenue actually come from? Which industries, company sizes, and personas close deals? What content drives conversions? Which close-lost deals could be reactivated? Some of the best ABM results I have seen come from campaigns targeting close-lost deals and churned customers. These accounts already know you. The sales cycle is shorter. Do not leave them out. 
Casper Rouchmann from SparkForce told this story at the Bootcamp: a company showed him their ICP work – 27 segments they wanted to go after. His response: “No way, folks. It’s way better to start small and then expand than the other way around.” Every segment you add needs its own budget, creative, and management time. If you are not big enough to support that, you are just diluting everything. Start with 2-3 segments. Nail those. Expand when the model works. Segmentation is worth it when personas genuinely need different messaging or offers. It is not worth it when you are segmenting for the sake of granularity. 
The idea that you take cold prospects through a tidy sequence of awareness > consideration > conversion is outdated. People do not move through funnels in order. Someone in a “cold” audience can book a demo on day one. Someone who has seen 50 of your ads might never convert. What matters is keeping touchpoints high with the right content in front of the right people. Retargeting is not about squeezing intent – it is about reinforcement. Keep showing up, keep adding value, and conversions will happen on the prospect’s timeline, not yours.
LinkedIn ads warm up accounts. Outbound closes them. Running them in silos means you are leaving pipeline on the table. At minimum, sales needs to know which accounts are engaging with ads so they can time their outreach. Marketing needs to know which engaged accounts turned into pipeline so they can optimize campaigns. This means shared data, defined handoff triggers, and a reporting cadence that keeps both teams aligned. Use intent signals from ad engagement to trigger outbound sequences – not random cold emails to accounts that have never heard of you.
This is one of those mistakes you cannot see because you are inside it. You think your product messaging is clear and compelling because you live and breathe it every day. But your audience does not care about your features or your tech stack. They care about their problems. As Herzeg put it: “You wouldn’t believe how many people don’t know their proper messaging. They live in a bubble, they have confirmation bias of how good they think their product is.” Test your messaging with real data, not internal opinions. If your ads get impressions but no clicks, the targeting might be fine – the message just does not resonate.
LinkedIn’s own research says 48% of users find B2B ads boring and 82% want more creativity. Our data backs this up: stock photos appear in 35% of the lowest-performing LinkedIn ads but only 12% of top performers. Zero stock photos among the 17 highest-CTR ads we analyzed. Use real people. Your team, your customers, your founders. Be bold with your visual style. If your ad looks like it came from a generic template, it will be scrolled past like one.
LinkedIn audiences are smaller than Meta or Google audiences. Ad fatigue hits faster. If you have a large budget and a small audience, you need MORE ads (10+) to keep per-ad frequency low. Do not set up campaigns and forget them. Test continuously, react to the data, and swap out underperformers. Monthly creative refresh is the minimum for ABM campaigns. 
Ishaant Shakunt from SpareGrowth tested the “Book a Demo” CTA against his offer scoring framework. Only 2 out of 10 checks passed. His verdict: “This is so bad that it’s not worth tweaking it. Just don’t run it.” Cold LinkedIn audiences just heard of you. They are not ready to invest 30 minutes in a sales call. Start with value-first offers – audits, templates, benchmarks, tools. Test at least 4 different offers. What you think will win almost never does.
This one shocked me. From our correlation analysis of 33 companies with complete pipeline data: CTR has a negative correlation with pipeline (Spearman rho = -0.170). High CTR does not predict more pipeline. In some cases, it predicts less. The metric that actually correlates with pipeline? Ad spend (rho = 0.566, p=0.0006). Spend more, get more pipeline. CTR is a vanity metric for ABM – treat it that way.
Last-click attribution gives 100% of the credit to the last ad someone clicked before converting. For B2B, with buying committees of 6-10 people and sales cycles of 3-6 months, this means every awareness touchpoint that built trust gets zero credit. The result: your Thought Leader Ads look like they generate no pipeline, your retargeting looks like it generates all of it, so you cut TLAs and double retargeting. Pipeline drops. You conclude ABM does not work. The problem was never the campaigns. It was the attribution model. Influence-based attribution – crediting every campaign that touched an account before a deal was created – gives the real picture. When we switched, our reported pipeline influence increased by over 3x.
Campaign Manager shows you campaign-level numbers. Impressions, clicks, CTR, CPC. What it cannot show you: which specific companies are engaging, how deeply, and whether they are progressing toward a purchase. LinkedIn does offer some native company-level data if you upload your target list – you can see engagement per company on a list basis. But it is limited to a top-25 view and does not connect to your CRM or pipeline. For full account-level engagement tracking, you need a tool that pulls company data from LinkedIn’s API and maps it against your target list. ZenABM does this automatically – showing every company that engaged with your ads, their engagement trends, and connecting it all to pipeline data in your CRM. 
| Category | Mistake | Fix |
|---|---|---|
| Targeting | Not previewing audience | Use Audience Hub before every launch |
| Targeting | Super title bundles | Check one title at a time, exclude irrelevant ones |
| Targeting | Missing LinkedIn URL in lists | Always include company page URL |
| Targeting | Broad seniority exclusions | Only exclude specific job titles |
| Targeting | Audience expansion on | Turn off, check after every edit |
| Budget | Maximum Delivery bidding | Use manual bidding, start 30% below recommended |
| Budget | No impression capping | Dynamic exclusion list for high-impression companies |
| Budget | Budget dilution | Fewer campaigns, $50-100/day each |
| Settings | Website Conversions objective | Use Website Visits instead |
| Strategy | No plan before campaign launch | Define goals, sales alignment, measurement first |
| Creative | Untested messaging | Test 4+ offers with real data |
| Measurement | Optimizing for CTR | Focus on pipeline per dollar spent |
Targeting mistakes are the most common and the most expensive. Not previewing your audience in the Audience Hub, not understanding how LinkedIn bundles job titles into “super titles,” and using broad exclusions that accidentally remove your ICP. These mistakes are invisible in your dashboard – CTR and CPC look normal, but you are paying to reach the wrong people.
Manual bidding in almost every case. Start with a bid 30% below LinkedIn’s recommended range and adjust based on your daily spend ratio. Maximum Delivery is usually inefficient. The one exception: Thought Leader Ads with a brand awareness objective, where it can deliver lower CPMs.
For cold audiences: 6-10 impressions per person per month total, max 4 per campaign. For warm audiences: 10+ per month. Per creative: replace after 2.5-3 impressions per person, which is when returns start declining. Monthly audience penetration should be 30-50% for cold and 70-90% for warm.
Because CTR does not predict pipeline. Our data from 33 companies shows a negative correlation between CTR and pipeline. What does correlate? Ad spend. The most likely issue is that you are not spending enough to reach your target accounts with sufficient frequency, or your targeting is reaching the wrong people entirely. Check your audience composition and bump your budget before optimizing creative.
Website Visits for driving traffic and demo signups. Engagement for in-feed content and building retargeting audiences. Lead Generation for gated content. Avoid Website Conversions – it is a more expensive version of Website Visits with no meaningful improvement in results. Only use Brand Awareness for Thought Leader Ads when your goal is maximum reach.
