Filip Matekovic

Most marketing teams don't have a marketing problem. They have an operations problem. Too much manual work. Too many tools. Not enough systems. They're measuring vanity metrics instead of revenue.

I run marketing at Hunch, where we help modern marketers fix exactly this. We automate creative and media workflows for paid social - connecting your data, creative production, and campaign execution in one system. 

You can scale high-quality, personalized ads that resonate with audiences without hiring more people or burning out your team. You get the speed to test more, the volume to beat ad fatigue, and the metrics to prove what drives revenue

I've worked with Fortune 100 brands and led teams at award-winning agencies before Hunch. I specialize in marketing operations and go-to-market strategy. Now I use that experience to run marketing at a fast-growing platform, working with 100+ e-commerce brands.

I use AI and marketing ops to build revenue systems that actually scale. Revenue over vanity, every time. If you can't tie marketing to revenue, it's not marketing - it's just content. I share how we use AI at Hunch. Real customer results. What drives revenue. Systems that scale without hiring.

Follow me to learn how to:

- Scale personalized campaigns without losing your brand voice

- Use AI to supercharge creative storytelling

- Build marketing systems that drive revenue

- Choose a platform that blends automation with human creativity

Head Of Marketing

Hunch is the automated creative production and media buying platform that powers d2c brands, retailers and agencies.

Developing data-driven marketing strategies and tactics that drive positive ROI.  Growth hacking in a fast-paced environment in order to skyrocket Inbound MQL

- Complete ownership of the Hunch's marketing mix
- Responsible for achieving KPIs for inbound MQLs
- Building and scaling complex B2B marketing campaigns using ABM model
- Hunch Growth hacker and brand advocate
- Content author

McDonald's Germany ran a Ramadan campaign that's splitting opinions.

During fasting hours: empty packaging. After sunset: food appears in real time.
Clever, right? Tension underneath.

Comments section exploded with one recurring theme: McDonald's isn't halal in Western markets. So who's this campaign even for?

Fair point. But campaign featured mostly fries and McPlant items. No meat. Does that shift the equation?

Two perspectives I'm seeing:

1. Tone-deaf. You can't celebrate a community while ignoring their core dietary requirements. Performative at best.
2. Thoughtful. Muslim employees felt seen. Cultural recognition matters even when the product isn't a perfect fit.

And then there's the boycott context. McDonald's has been on lists for two years. Ramadan campaign doesn't reset that.

But here's what actually interests me from a marketing ops angle:

This is programmatic creative in the wild. Real-time triggers based on sun position data. Creative variants swapping across locations instantly.

Execution is genuinely impressive.

Problem? Automation amplifies your decisions. Good ones and bad ones.

You can trigger 1,000 creative variants and still miss if the strategic foundation has gaps. This campaign nailed the how. The what still has open questions.

Faster creative delivery doesn't fix a positioning problem. It just surfaces it faster.

Paid Social Playbooks | Head of Marketing @ Hunch | Predictable Revenue Systems | AI & Automation

Liquid Death's entire creative operation runs on a 5-person in-house team.

30 billion earned media impressions. Total spend - every production dollar, every talent fee - under $2 million.

Most beverage brands spend more than that on a single campaign.

Reason isn't the dark humor. It's the constraints.

Because the team knows what works, they handle everything from concept to execution in-house. No agency briefing cycles. No approval chains. No "too many cooks" problem.

But knowing what works only happens when you've defined what you are.

Liquid Death made one creative decision early: every piece of content would look and feel like it came from a heavy metal band, not a beverage company. Skulls. Dark humor. Anti-corporate tone. That's the aesthetic ruleset. Rigid as any brand bible.

Every time they make content, team asks one question: will this get shared? Likes and comments are fine. Shares are what they're after.

One filter, one aesthetic, one metric.

That's the system. Everything else is just execution speed.

Most creative teams operate with the opposite logic - maximum flexibility, minimum constraints. Every campaign is a blank slate. Every brief restarts from zero. Freedom feels productive. The output rarely is.

Constraints aren't a limitation on creative output. They're the reason output is possible at scale.

Liquid Death produces notable content a handful of times a month - and keeps the bar high. Not volume for volume's sake. High-quality output, fast, because the decisions about what they stand for were made once and never relitigated.

The 5-person team isn't impressive despite the constraints. It's impressive because of them.

I built a workflow that pings me on Slack every time an ICP prospect posts on LinkedIn.

Here's how it works:

We have a spreadsheet with names and LinkedIn URLs

Three segments:
(1) Customers -pulled from CRM
(2) Thought leaders in ICP space
(3) ABM accounts

n8n runs the workflow. Every day at scheduled time, agent scans profiles and batches everything into dedicated slack channel. Name, segment, context, link to the post.

Rule we built in to avoid burning API credits: only LN profiles that have posted in the last 2 weeks get scanned.

Interesting finding: only about 7% of our list of ~1,200 profiles is actually active at any given time. (customers, ABM targets, thought leaders combined). That tells you something about LinkedIn activity rates.

What this engagement actually gives you:

You're not chasing engagement. You're showing up consistently in front of the people who matter - customers, prospects mid-deal, the voices in your space. Your brand stays top of mind. Another touch in the sales timeline. Retention signal for customers.


Thing I had to figure out the hard way:
Real-time Slack notifications were a constant distraction. I had to time-block it - everything batches at 2 PM, I sit down, go through the list, comment where it makes sense, done. Close LN tabs.

This workflow doesn't work without that discipline.
Otherwise you've just built a new way to get distracted.

This isn't a "comment to get the template" post.

If this was useful and you're thinking about building something similar - just do it. (save the post)/ Everything can be built today.

⚡️ Only thing that matters is whether AI use case brings real value to your workflow.

Linkedin Engagement Agent

Problem isn't AI creative tools. It's how brands use them.

Here's the pattern I see across accounts doing this wrong: they treat AI as the strategy, not the production layer. They generate 500 variations, throw them at Meta, and wait for the algorithm to figure it out.

Everyone assumes it's a production problem. Generate more. Test faster. Feed the algorithm.

Wrong game.

After working with 200+ accounts, we saw that AI scales what you already know. If you don't know what resonates with your audience, AI will just help you fail faster at scale.

Brands actually winning aren't generating more. They're coming in with proven hooks, tested templates, real audience insights - and using AI to remove the production bottleneck between knowing what works and having enough of it live.

Losers treat AI as the strategy. 500 variations, no framework, no signal. Just volume and hope.

AI scales production. It can't manufacture strategy you don't have. If your current ads aren't working, more of them won't fix that. You'll just fail faster and spend more doing it.

AI is a production engine. It amplifies what you already know works.
Volume without strategy is expensive noise.

"AI replaces teams" debate is the wrong conversation.

Everyone's arguing about headcount. Nobody's asking what the team actually does with their time.

For solo operators building simple products? Maybe. For B2B SaaS running outbound, positioning, events, demand gen, and partnerships simultaneously? 
Not even close.

What actually happened at Hunch: we removed everything repetitive. 
First drafts, research, briefing, reporting, monitoring. AI handles it. 

Our team handles everything that actually matters:
Strategy. Positioning decisions. Partnerships. GTM sequencing. The judgment calls you can't automate.

AI made our output 8x. It didn't touch our thinking.

What AI can't touch: positioning decisions, partnership judgment, GTM sequencing, reading a room on a sales call. Work where context and pattern recognition from years of experience actually matter.

"Smaller team, same output" framing is still thinking about this wrong. 
Real unlock is the same team doing work they couldn't access before - because the noise is gone.

Should you hire that next marketer?

Shopify's CEO says not until you answer this question first.

"Prove AI can't do it before you ask me for a hire." That's Tobi Lütke's rule for every team at Shopify.

He built Shopify because every e-commerce tool he tried was garbage. That scrappy, build-it-yourself mindset still runs the company 20 years later.

His core operating principle: If I do something three times, I automate it.

In 2023, he deleted every recurring meeting of 3+ people. 322,000 hours freed. That's 150 full-time employees worth of time.

Then in 2025, he raised the bar again: Before you ask for headcount, prove AI can't do it first. Some teams were already hitting 100x output with AI. Same people. Better systems.

This is how Tobi thinks: Problem is never talent. It's always process.

Manual handoffs. Repetitive tasks. Meetings about meetings. That's what kills output. 

He's spent 20 years proving that your best people aren't slow. Your workflows are.

40% of your team's capacity goes to QA.
Not testing. Not optimizing. Just verifying that 500 locations are running correctly. This is where agencies hit their ceiling.

Managing multi-location campaigns manually isn't just slow - it's a structural bottleneck that limits how much business you can actually service.

Each location needs localized creative, regional messaging, store-specific offers, and audience targeting. Manual workflows can't scale this without breaking.

Manual workflows bend at 20 locations.
They break completely at 50.

Budget changes require clicking through hundreds of ad-sets. Promo updates take entire afternoons. Execution speed collapses before strategy ever does.

I've watched agencies turn away clients not because the strategy was wrong, but because they couldn't operationally service the volume.

Bottleneck isn't creative thinking. It's campaign infrastructure.

When one agency managed 747 locations with six people doing daily manual updates, they weren't optimizing performance - they were maintaining existence.

This is the trap: either hire for repetitive work, or cap your growth.

Template-driven workflows change this completely. One spreadsheet becomes campaign operating system. Update a date, budget, or creative element once - it syncs across hundreds of locations automatically.

Each location gets its own localized creative, messaging, and offers - without manual production cycles.

That 40% QA capacity? It goes back to testing, iteration, and actual optimization.

Execution stops being the constraint. Strategy becomes the lever again.

Managing 20+ locations? See how it works → https://bit.ly/4b3QUf7

Most Meta advertisers obsess over targeting. But when Meta spends 70% of your budget on 65+ year olds, you set the wrong goal.

Algorithm is doing exactly what you told it to do. You just set the wrong task.

I saw this across 100+ accounts. Teams spend weeks on audience architecture - layering interests, adding exclusions, building targeting structures that feel increasingly precise. Meanwhile Meta has 12 creatives a month to work with.

Jon Loomer wrote about this recently - when to actually restrict your audience on Meta. His conclusion: almost never. And the reason is always same. It lives upstream from targeting.

Algorithm doesn't need better instructions on who to find. It needs more raw material to test against. When you give it 12 creatives, you're not running a targeting problem. You're running a data starvation problem, and no amount of audience refinement fixes that.

Benchmark I see across accounts that actually scale: 80+ variations per month. Most brands are at 12.

Teams are optimizing the wrong variable. Constraint isn't who Meta is finding - it's how much you're giving Meta to work with.

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