Nayan

Freelance Data Specialist

Verschelden BV

Data Specialist

comma

Freelance Performance Marketeer

Kennisjobs

Freelance Marketing Manager

Be Yourself ™

John Cockerill

Wind Turbine Technician

Actum Services

Mechanic

As a freelance tracking specialist, I help businesses with their web tracking & data visualization.

I graduated with magna cum laude for my master's degree in industrial engineering electromechanics from University Ghent, where I developed strong analytical, problem-solving, and technical skills.

I started out as a performance marketeer, so I know very well what is important to track for ppc & social ads specialists.

Lowie Verschelden

Marketing @ KlientBoost - The Performance Marketing Agency

Struggling to make your paid ads profitable? I can help.

I've generated $50M+ pipeline (& counting) for B2B Tech and SaaS companies through content marketing, paid search, and paid social demand generation and GTM strategies.

"We've never been able to make paid ads work for us." — common feedback from happy B2B clients.

Some of the leading minds in B2B follow my content for fresh LinkedIn and Google Ads growth recipes.

Right now, I'm leading marketing @ KlientBoost to add $250K MRR using the exact same strategies, principles, & processes we roll out for clients.

Here's how we can help you: 
- Done for you marketing—starts with a free marketing plan
- Fresh growth recipes to your inbox—klientboost.com/kitchen
- Follow me on LinkedIn to learn the latest winning B2B strategies

Got a burning question about B2B paid ads? My inbox is always open too.

LFGTM 🤘

Patrick Cumming

Two years ago, I'd drop a carousel on LinkedIn and get 300+ new ICP followers.

Last week, I posted what might be my most valuable carousel yet and got <50 followers.

LinkedIn is officially pay to play.

The bad news: Organic growth and lead gen just got harder.

The good news: You can stop chasing viral posts. Write for your audience knowing you'll promote it later.

Here's how I'm adapting my approach to the new age of LinkedIn "pay-to-play" social selling:

1. Create a list of the most common pain points your target audience is facing and add it to a spreadsheet.

2. For each pain point, summarize your POV on the problem and the solution you provide to solve that problem. Add these into new columns.

3. Aim for 7-10 common pain points. I call these category entry points. They're the problems your audience faces that move them from out-market to in-market.

4. Write 1-2 posts per pain point. This gives you 10-15 posts targeting your ICP with content that actually matters to them.

5. Publish 1 post per day over the next 2 weeks. Let them build organic engagement for 48-72 hours before promoting.

6. Before you hit publish, add a P.S. section at the end of each post with a short description of your main offer and a link to the offer page. Keep it simple and relevant to the pain point you just addressed.

7. Promote every post as a thought-leader ad. Now, you can push these posts to the exact audience you're trying to reach. Let your in-platform attribution data tell you what is and isn't working, not the organic algo.

I've been piloting this approach for ~30 days to a B2B SaaS audience and we're already seeing a lift in qualified inbound.

We're spending ~50% less to do it too.

If you're only relying on organic reach, you're leaving 90% of your ICP on the table.

The new play isn't groundbreaking, but it works.

It's what we should've been doing all along: understand your audience, write what they need to hear, and distribute it where they actually are.

And if you're serious about making LinkedIn a predictable revenue channel in 2025, you should be testing it.

Who's in?

Here's a fast and dirty way to estimate your optimal 2026 marketing budget, best suited to $1M-20M ARR B2Bs prioritizing demand capture and in-market audiences:

How to Calculate (and Sell) Your 2026 Marketing Budget

Every new marketing trend is "the one"... Until it flops.

Work with an agency that doesn't believe in shiny objects—only incredibly well executed marketing.

Easiest way to miss your marketing goals: 

Guess your budget and hope for the best 🫠

But that's still what most B2B SaaS companies do anyway.

We created a 6-step data-driven budget planning framework so you don't need to wing it (and it's CFO approved too 😉).

It's called the Math of Marketing. 

Here's how it works:

1️⃣ Map out conversion rates for each lifecycle stage from lead through to closed revenue. We use a simple spreadsheet. Focus on qualified leads who booked calls, not ebook downloads, otherwise the math breaks.

2️⃣ Next, calculate your cost per acquisition (CPA) for each stage. Use this equation: marketing spend ÷ volume at that stage. For example, $500K spend for 1,000 MQLs = $500 cost per MQL.

3️⃣ Work out what needs to be true to hit the primary business objective. Need 20% revenue growth? Based on current lifecycle conversion rates, calculate exactly how many leads, MQLs, or SQLs you need to do it. 

4️⃣ Take your marketing KPI volume target and multiply that by your current CPA baseline. If you need 2,000 leads, and CPA is $200, your marketing budget would be $400,000.

5️⃣ If only it were that simple. The truth is, ad costs are going to go up and you need to factor that in. Paid social costs are up ~20% and paid search costs are up ~2% vs last year. Add a 10-15% increase vs current baselines to account for it.

6️⃣ You've done the math. Now you can package that up into a board-ready doc and present a data-driven budget so leadership understands the investment required to hit their goals.

The whole process takes <1 hour and is 10X less stressful than guessing.

—

Here's why this framework is so powerful:

1. Translates marketing into financial language execs understand
2. Gives you leverage when negotiating marketing goals
3. Increases your chance of actually hitting goals

You can show exactly how increases and decrease in spend impact bottom-line revenue growth.

Now you're seen as an investment, not a cost centre.

🤘

—

P.S. Here's the link to the Math of Marketing calculator. Hit "make a copy" to save it to your Gdrive: https://lnkd.in/e52qZ27T

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Here's a no-BS framework to generate more SQLs with LinkedIn Ads, best suited to B2B SaaS companies tired of optimizing for a funnel that doesn't match how buyers actually buy:

The 4-Step Demand Gen Strategy To Increase SQLs

If I was a Head of Marketing at a $50M ARR B2B SaaS expanding into a new market, this is the exact 6-step paid ads play I'd run:

1. Use Ahrefs to analyze in-market category keyword volume in your new market. High volume means launch Google Ads first. Low volume means start with a LinkedIn demand generation play.

2. For Google Ads: Calculate budget by multiplying avg. CPC by clicks needed to hit your demo target using current demo form conversion rates from paid search.

3. For LinkedIn: Build your target segment and calculate budget to hit 80%+ reach and 10+ frequency over 90 days using cost per 1,000 member accounts reached benchmarks.

4. If budget is too tight, shrink your audience. Pick one job title or industry to saturate first. Add new segments incrementally as more budget opens up.

5. Start with creative that's already working in existing regions. Pain points rarely vary much by geography anyway. Scale what performs in the new market. Pause what worked elsewhere but fails here. Test 2-3 new creative angles per month.

6. If you're not seeing booked demos within 2 weeks, targeting is broken. Switch from native targeting to a company account list. Turn off audience expansion. Exclude any job titles who don't fill out demo forms based on historic data.

I ran this exact play for a 5-figure ACV B2B SaaS last year and pipeline was higher in Q4 than any other quarter that year.

That's pretty rare for most B2B companies that aren't in hyper-growth.

Expanding into new markets can feel daunting, but it's actually fairly straightforward when you approach it with data-driven performance marketing principles instead of guessing your way through it.

Who's testing this out in 2026?

—

P.S. Struggling to hit your paid ads pipeline targets? Have a KlientBoost - The Performance Marketing Agency Growth Strategist build your free marketing plan with proven new tactics like this one. It's fully personalized to your audience, industry, and goals.

Hit the link to request yours: https://lnkd.in/ediU_-Ru

Nobody really shares the brutal reality of day-to-day marketing on LinkedIn. 

I admit I'm part of the problem because I share as many wins as possible. It's good for business, okay?

But, reflecting on the last 12 months in this role, it wasn't always easy or pretty.

Here are the 5 biggest and scariest mistakes I made (typos not included). Hopefully there's a few lessons in there for you too:

1. Pulled $10K from Google Ads in April and tanked pipeline. Based on lift analysis, I estimate non-brand Google is driving ~50% more inbound than we can track. You have to validate attribution data with incrementality testing. Tracking alone isn't reliable.

2. Fumbled the KlientBoost Kitchen launch. I thought if content was world-class it would grow itself. Big mistake. As soon as I started promoting it regularly (thanks Kimberlee Meier), views and downloads went up 20X. Btw, don't be afraid to post links, it does work.

3. Didn't set any clear output goals. My logic was if we hire great people, output will sort itself out. The opposite happened. Nobody knew what to prioritise so we worked on 1,000 ideas but didn't ship enough in Q3. We're now aligned on output goals and are shipping more than ever.

4. Didn't act on research fast enough. We interviewed 182 marketing leaders in May and didn't synthesise it into content ideas until November. We're already seeing an increase in LinkedIn-sourced SQLs in Q4 since framing content around the findings. 

5. Could have pushed LinkedIn Ads ROI higher with segmentation. We went broad because most target industries have overlapping category entry points. But, we've realised it's SUPER important for prospects to feel like we get their biz and industry. Segmented campaigns are the best way to show them we do.

6. Spent $8K sponsoring a newsletter and FORGOT TO ADD THE UTM CODE. Seriously, who does that? It was super annoying because we had a HUGE incremental lift in SQLs but I couldn't attribute ANY of it directly back to the newsletter. That would have been EXTRA, important proof.

I'd be lying if I said it was always easy to shake off the mistakes. 

There were moments where it made me question if I was any good or what business I had posting about how to do marketing when I can't get it right day-to-day myself.

But, the truth is, the mistakes ARE part of the process. And, if you're trying to push boundaries, like we are, they're unavoidable.

Just gotta make sure you're always reflecting, learning, and adapting.

🤘

If I listened to what everybody says on LinkedIn, I'd have killed ads that generate the most pipeline.

Our best performing ads break every rule "experts" on here preach:

- Overused "If I was an [insert job title]" hooks
- Multiple em-dashes throughout the copy
- Direct sales CTAs to cold audiences

All things everybody says not to do.

Yet these ads drive more influenced pipeline and revenue than any other format we've tested.

(And only take 15 mins to write too by the way 😉)

The disconnect is real. LinkedIn's loudest voices optimise for engagement and vanity metrics. But engagement doesn't pay the bills. Revenue does.

Most advice you see is based on what performs well in the feed, not what actually converts prospects into customers. There's a massive difference.

This is why data-driven decisions matter more than popular opinion. Test what the crowd says doesn't work. Track it against pipeline, not likes or comments.

You'll be surprised how often the "wrong" approach is exactly what your B2B needs.

Stop letting the loud minority dictate your strategy. Let your pipeline data do the talking instead.

graphical user interface, text, application, email

The traditional funnel framework is broken.

TOFU, MOFU, BOFU assumes buyers move in a straight line.

They don't.

So I stopped forcing campaigns into funnel stages and started building around real buyer behaviour instead.

Now I run two campaign types that match how B2B buyers actually behave:

1. Demand generation campaigns target our entire target audience.

These campaigns have 2 goals:

- Attract in-market buyers in our audience
- Build recall with out-market prospects

Both goals can easily be achieved with the same ad providing it:

- Agitates a painful problem
- Highlights a desired outcome
- Shows a point of differentiation
- Positions your product as the solution

This will only work if you're hitting:

- 80%+ audience penetration
- 10+ frequency

And use strategic messaging backed by data.

That means talking about what your audience is needs to hear.

Not what you want to say.

2. Demand capture campaigns increase ad frequency for in-market buyers.

These campaigns exist to:

- Increase recall with in-market buyers
- Overcome objections
- Generate revenue

Here's how we build them:

Generic retargeting is out.

We only target high-intent behaviors:

- Service pages, pricing pages, offer pages.
- AI-driven intent signals from Dreamdata

Finally, we add strict audience filters to block poor-fit prospects from wasting budget.

We don't exclude active pipeline from targeting either.

We keep reinforcing why we're the right choice until the deal closes.

Because they're not won until they're won.

Funnel stages work great if buyers follow a script.

But they don't.

So we stopped marketing to a model and started marketing to reality.

P.S. I'm running a webinar tomorrow at 10 AM ET / 3 PM GMT walking through this new approach to LinkedIn Ads. Here's the link to sign up: https://lnkd.in/eVwT2E4E

Last year, a client and I hit a wall that made no sense.

We were running LinkedIn Ads to a high-value audience segment. We did everything by the book:

- Matched budget to audience size
- Consolidated campaigns
- Optimized for reach
- World-class creative
- Ran experiments to drive CPM down

But we couldn't push audience penetration past 60%.

That meant 40% of our target decision makers weren't seeing our ads.

It was driving me insane until I realized what was actually happening.

That 40% we couldn't reach weren't actually active on LinkedIn.

So I came to the next call with the fix: expand to Meta Ads.

But it wouldn't work with native targeting, so we needed a different playbook.

Here's what I recommended:

1. Use a 3rd party audience tool to get LinkedIn-level targeting precision on Meta Ads (we use Primer for this).

2. Take any wasted LinkedIn Ads budget and put into Meta Ads. CPMs are cheaper so you probably won't need additional budget.

3. Launch with the top 5 creative from your LinkedIn Ads campaigns. Those are the ads with the highest CTRs, dwell times, and CVRs to pipeline.

We're now recommending that same strategy to all of our clients who've plateaued on LinkedIn Ads.

The best part is you're not restricted to Meta Ads either.

You can take that same audience and target them on Google, Reddit, or YouTube, depending on where your audience is most active.

Next Wednesday, I'm running a 30-minute LinkedIn Live with Primer Co-Founder Keith Putnam-Delaney covering 7 new strategies like this to generate B2B pipeline from B2C channels.

Here's the link to sign up: https://lnkd.in/ebftE7nC

I was totally wrong about LinkedIn thought-leader ads.

For most of 2025, I told my followers to only promote organic posts that hit 100+ engagements.

It made sense. Until the algo changed and killed organic reach overnight.

Posts I knew my audience would usually love started getting <50 engagements.

I didn't trust the algorithm to tell me what's good anymore.

So I made a bet that felt risky: stop chasing engagement. Only write content solving marketing-related pain points for our priority ICP.

Marketing leaders at $10-100M ARR B2B SaaS companies.

I knew engagement would tank. I didn't care. I'd put paid behind everything anyway.

Here's what happened when I tested it last month:

Post with <50 organic engagements:
- 14s+ dwell time
- 4.6% CTR

Post with 100+ organic engagements:
- 12s dwell time
- 2.8% CTR

The post the algorithm ignored performed 64% better with paid spend.

This pattern repeated across multiple posts. The data was clear.

Organic engagement is a vanity metric. Paid performance is the only metric that matters because it tells you what your true ICP thinks of your content. That's all that matters.

Here's the new thought-leader ad flywheel I recommend for B2Bs who want more LinkedIn Ads pipeline:

1. Pull transcripts from every first-touch call of closed deals in the last 12 months

2. Identify the 5-7 pain points that come up repeatedly

3. Write thought-leader posts addressing each pain point using PAS or AIDA frameworks

4. Let posts sit for 48-72 hours, then add a soft CTA with a URL

5. Move every post to your thought-leader campaign regardless of organic performance

6. Analyze paid metrics only: dwell time, CTR, and inbound volume

7. Double down on what's working in paid, not what performed organically

We're already tracking a 60% increase in B2B SaaS SQLs vs the previous 2 months.

During November. One of the quietest months of the year.

The takeaway isn't that organic is dead. You can still win there.

But LinkedIn is aggressively moving to pay-to-play.

Stop optimizing for the algorithm. Start optimizing for your ICP.

Better to adopt this now before everyone else does and the law of shitty click throughs catches up.

B2B ads don't need to be less boring.

We've seen plenty of "creative" ads generate zero pipeline while "boring" ads drive predictable revenue.

The goal isn't creativity. It's growth.

Here's what happened with our best-performing ad this year:

1. Used a trusted "boring" template 
2. Took <15 minutes to write
3. Called out our ICP and pain point in the hook
4. Outlined exact steps to solve the problem
5. Added a CTA to our free marketing plan offer

Super simple by most standards and I've read a few marketers actively talk about how they dislike that specific template.

But it influenced 6 closed deals in the last 90 days on a cold campaign. That's ~$320K ARR from $1.3K ad spend.

It works because we achieved the most important objectives every ad has:

1. Link it to a relatable experience
2. Provide a clear value proposition
3. Make it memorable with distinctiveness
4. Appeal to emotion to make it engaging
5. Anchor it to your product and the pain you solve

If you can achieve all those objectives AND make it creative, it'll work 10x better.

But those are the first goals.

Creativity and cleverness are secondary.

We see this pattern repeatedly. Ads that prioritize clear messaging over flashy creative consistently outperform their "exciting" counterparts.

The market doesn't care how impressively creative you are.

They care about whether you can solve their problems.

For that you need to start and end with clarity.

🤘

Customer interviews are overrated.

There, I said it.

Most marketers treat them like gospel. But here's what they actually tell you: why existing customers love your product.

That's useful. But it's not the data you need to 10X performance.

Because your customers aren't your prospects.

Your prospects are still in pain. They're still searching. They haven't bought yet.

And that's the mindset you need to understand if you want your ads to drive serious pipeline.

So where do you find it?

First sales call transcripts.

Not the second or third call. The FIRST one.

This is where prospects tell you exactly why they showed up and what they're hoping you'll solve.

Here's a workflow we use to mine that data:

1. Extract a call summary from every first sales call
2. Export the data to ChatGPT (or your fav AI tool)
3. Assess the top 5-7 pains, gains, and jobs to be done
4. Use their exact words to build ad content

We rolled this out for a new campaign targeting B2B SaaS marketing leaders.

We're already seeing a 40% lift in B2B SaaS SQLs vs the previous 2 months.

No extra budget. Just tighter messaging based on what prospects actually care about before they buy.

The best part? This is way more accessible than running 50 customer interviews.

You're already recording sales calls. The data is sitting there waiting for you to use it.

Start mining it today and watch your messaging shift from generic to impossible to ignore.

Last year, a $1B+ B2B brought us in to run LinkedIn Ads to 200+ high-value target accounts.

We were optimising for clicks and conversions but no matter what we did, we couldn't reach more than 50% of our target accounts.

I pitched them something risky:

Stop optimising for clicks and conversions. Start optimising for reach.

This was considered bad practice on paid social. But, I had a hunch that the algo was prioritising distribution to the most active users. That meant 50% of our audience weren't seeing ads.

I also had a feeling the algo didn't understand the audience well enough to know who was most likely to click. If we ran this strategy we'd not only reach more accounts, but CTR would at least stay the same.

We ran a quick pilot A/B test and results were promising: 14% lower CPM meant we reached more accounts and no change in CTR.

We rolled out the strategy across the account.

3 months later and we'd reached 98% of those 200+ target accounts AND increased CTR from 0.5% to 2%+.

Even better results than we expected. No extra budget needed.

Here's why it worked:

1. We calculated budget using real CPM data so we knew we had enough to reach 80% of our audience with 10+ frequency every 90 days.

2. We promoted product-led content that tackled key pain points target decision makers faced that made them more likely to click.

3. Using the awareness objective set to optimise reach meant we could force the algorithm to push content to more accounts.

4. Because we understood our audience better than the algorithm we created content that increased CTR without needing to optimise for clicks and limit reach.

We're now using a similar process on our own account to reach 80%+ of our audience with 4%+ CTRs.

It wasn't just a one off win. 

It's a repeatable framework any B2B can apply to reach more accounts and generate more pipeline with LinkedIn Ads.

Next Wednesday at 10AM ET / 4PM CET, I'm teaching you the full playbook in a 1-hour LinkedIn live session with Dreamdata CMO Steffen Hedebrandt.

Sign up using the link in the comments 👇

I've shared a new LinkedIn Ads playbook every week in Q4 to help B2B SaaS companies hit their demo targets.

I'm 100% confident the playbooks work. But they'll still fail for many companies that try them.

Not because the steps are wrong. Because the creative is weak.

Here are 7 principles for creating strong ad creatives that drive more booked demos:

1. One message per ad. Don't cram every feature and benefit into one creative. 7 ads with 1 message > 1 ad with 7 messages.

2. Lead with the pain, finish with the gain. People are 10X more motivated to avoid pain than chase gain, so hook with the problem they're running from.

3. Always relate ads back to your product. That's how you build recall so prospects remember you when they're ready to buy.

4. Clear beats clever. If your ad takes more than 3 seconds to understand, it will fail. Leave no doubt about how you can help.

5. Call out the ICP in the hook. This makes sure users know the ad is for them. That gets more of the right eyes on your content.

6. Add a sales CTA at the end. If your content is valuable, prospects won't mind a soft sales message. This works even on cold audiences.

7. Write what your audience wants to hear, not what you want to say. For example, my audience cares about pipeline, so I write about pipeline.

Most companies blame the playbook when campaigns don't work.

But the playbook usually isn't broken. The creative is.

Fix the creative first. Then suddenly the playbooks start working like they're meant to.

A few weeks ago I posted a LinkedIn Ads strategy to generate more qualified demos for B2B SaaS companies.

I was so confident in it, I launched it on our own account to prove it works.

After 30 days, the results are in:

- 1 closed deal
- 13 high-intent, qualified leads that booked calls with sales

More of those will turn to SQLs this month after they book follow-up calls (usually a 1-2 week lag).

And LinkedIn underreports actual influence. So that's low-balling it.

This strategy was not complicated. It took less than 2 hours total to set up.

If you want to emulate it, here's what you need to do:

1. Build an account list you can fully saturate with your budget

2. Create 7-10 thought-leader ads teaching prospects how to solve painful problems

3. Add a URL that sends in-market users to a demo or book a call page

4. Set campaign objective to awareness and optimize for reach with a 7 freq cap

5. After week 1, kill ads with low landing page CTR and create more posts similar to those with high CTR

It took me around 90 mins to write the posts and around 30 to set up the campaign.

But here's the big caveat.

This strategy will NOT work if the content quality is vague, low-relevance, and disconnected from the problem you solve.

This worked for us because I built the posts around pain points we discovered after interviewing nearly 200 ICP prospects and analyzing hundreds more sales calls.

You can emulate the settings, but if you skip that step, this strategy WILL fail.

But if you get it right, you might find you're back on track to hit those tough Q4 demo targets.

Who's testing this?

CPM is a vanity metric. Track cost per 1,000 member accounts reached if you want more pipeline.

CPM measures impressions. Not unique accounts. You could be hammering the same people over and over while missing new in-market buyers.

I've seen this play out in our LinkedIn Ads account:

Campaign A: $69 CPM, $102 cost per 1,000 accounts reached
Campaign B: $52 CPM, $250 cost per 1,000 accounts reached

Campaign A also had an 4X higher conversion rate to pipeline.

Lower CPM doesn't always mean better reach. It often means wasted frequency.

Here's how to check yours:

1. Go to columns
2. Select delivery
3. Scroll all the way right

CPM and cost per 1,000 member accounts sit next to each other.

4. Sort by lowest cost per 1,000 accounts
5. Cross-check conversion rates to pipeline

If your low cost per 1,000 accounts reached also have higher pipeline conversion rates, kill the "cheap CPM" ones and reallocate budget.

It's not gonna transform pipeline overnight.

But making small optimizations like that over the next 90 days will make it a whole lot healthier.

taplio

The Battle

Lowie Verschelden

Patrick Cumming

Followers

Posts

Engagements

Likes

Performance ScorePatrick Cumming's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Lowie Verschelden

Patrick Cumming

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Patrick Cumming's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScorePatrick Cumming's LinkedIn Performance