A candid Q&A with founder Matt Orlić on the bad bets, costly lessons, and smarter moves every brand needs to know.

Hey everyone,

Welcome back for another bite to chew on.

This newsletter is going to be a little different. 

Last week we hosted a Q&A with Matt Orlić, founder and CEO of Qure Skincare and Ecomm Architects, to talk about the marketing mistakes that nearly cost our brands millions.

Over 120 founders joined live as Matt and Ash shared brutally honest lessons from our biggest failures and how we bounced back.

Today, we’re breaking down the top 10 questions and the key takeaways every founder can use to avoid the same mistakes. Let’s get into it. 

P.S. You can watch the full webinar replay here →

Your Email Platform Knows What Happened Yesterday. What About Tomorrow?

You have 50,000 email subscribers, detailed purchase history, and behavioral data on every customer. 

But when it comes to predicting who buys next, you're still making educated guesses.

So you use that data reactively—blast a discount when revenue dips because discounts worked last quarter—treating rich customer data like a basic spreadsheet.

Meanwhile, Klaviyo takes that same customer data and uses AI to predict churn risk, forecast customer lifetime value, and time messages based on individual buying cycles.

Here's what predictive marketing actually looks like with Klaviyo:

• Predicts CLV automatically: Klaviyo builds a CLV model using your company's data and retrains it weekly

• Forecasts churn before it happens: Get ahead of churn by predicting whether a customer is likely to purchase again, when, and how much they're likely to spend

• Times messages for maximum impact: Klaviyo AI analyzes both the average time between a customer's orders and the date they're most likely to place another one

• Segments based on spending potential: Create segments based on each customer's spending potential, such as their average order value and predicted CLV

Guessing worked when CAC was cheap and competition was thin. Now you need data that tells you what happens next, not what happened yesterday.

👉 Stop guessing. Start predicting with Klaviyo

Putting all your eggs in one basket.

This happens in 2 ways: 

1) Over-relying on a single channel

Channel concentration will kill you. 

Matt lost $5M overnight when his biggest retailer went bankrupt. One distribution channel controlled his entire business, and when it collapsed, so did everything else. 

Today, we see DTC founders making the exact same mistake with Meta. Your business becomes completely vulnerable to algorithm changes, policy updates, or platform issues.

2) Obsessing over the wrong metrics.

Metric obsession is just as dangerous as channel concentration. After iOS hit, it became easy to get lost in vanity metrics that felt good but told you nothing useful. 

Spending $10K to generate $30K in revenue looks like a 33% MER win, but if that revenue is coming from the same repeat customers getting hit over and over, you're headed for a cliff.

We learned to separate new customer metrics from blended data. When you see revenue spikes, check if they're from new customers or existing ones (maybe from an email blast). Only scale when you're actually bringing in new people profitably.

TL;DR - diversify your channels and track what actually matters, new customer acquisition cost and contribution margin, not just pretty ROAS numbers.

1) Stop trying to do everything at once when you can barely do one thing well.

The complexity trap kills more brands than bad products. You'll see founders with one product trying to sell to four different audiences, with three different offers, across two channels, all with maybe one media buyer and a creative person. 

But they don't have the resources to execute all that properly, so everything performs poorly.

Strategy is about choosing what NOT to do. Master one avatar, one channel, one offer, one product before expanding. 

This feels limiting, but it's actually liberating, you can pour all your energy into making one thing work instead of spreading yourself thin across multiple mediocre attempts.

2) Don’t put “hacks” over fundamentals

It's tempting to spend years learning manual bidding and campaign hacks, but platform tactics become obsolete every time there's an algorithm update. Human psychology doesn't change.

Learn marketing psychology instead: price anchoring, copywriting, what triggers actually make people purchase. Study direct response principles from books like Breakthrough Advertising. 

Those insights work today just like they did decades ago, regardless of what platform you're using.

The upper funnel feels like a black box because most people track the wrong things.

ROAS seems like the obvious metric, but it's actually misleading. 

You can have campaigns showing 3x ROAS that are losing money because ROAS doesn't account for your actual costs or whether you're bringing in new customers versus hitting the same people repeatedly.

The real insight is separating new customer performance from everything else. 

When your retargeting campaigns show amazing numbers but your prospecting is struggling, you're not growing, you're just getting better at selling to people who already bought from you.

Track new customer acquisition cost and contribution margin instead. These tell you if your upper funnel is actually building your business or just recycling existing demand.

Platform data is great for optimization, terrible for scaling decisions.

Platforms are biased toward making themselves look good. Facebook will always show you data that makes Facebook look amazing. TikTok does the same for TikTok. 

But when you're deciding where to actually allocate budget, you need neutral data.

The trap is real and expensive. We've seen campaigns showing incredible CPAs in-platform while external attribution tools revealed double-counting issues, view-through attribution problems, and other measurement gaps that made performance look better than reality.

Ash caught this when testing two pixels simultaneously, Facebook showed great performance, but Triple Whale revealed he was double-counting conversions. 

Matt uses Northbeam for the same reason: unbiased attribution across all channels.

The approach that works: optimize within platforms using their data (because you have to play by their rules), but make budget allocation decisions based on tools like Triple Whale, Northbeam, or similar attribution platforms that give you the full picture.

Go organic first, and be systematic about it. Before spending a dollar on ads, prove demand exists through content.

The strategy is simple but requires commitment: post on TikTok 3-4 times daily for 30 days with different messaging and angles. 

The key insight most founders miss is that TikTok views don't come from followers. Every video hits the algorithm and reaches completely new people, which means you can test wildly different messages without worrying about brand consistency.

Each post finds its own audience, so treat it like a free focus group. Test different problems, solutions, hooks, and value propositions. 

See what resonates organically, then put ad spend behind the winners.

This approach saves you from the expensive mistake of spending thousands on ads for products nobody wants or messaging that doesn't connect with your market.

Think strategically about where each product fits in your customer journey.

Not all products serve the same purpose. Some are designed to acquire customers, others to increase order value, others to boost lifetime value. 

You need to know which role each product plays before you launch it:

For subscription products specifically, there's a balance to strike.

Both Matt and Ash said to focus on bundles (1-month, 3-month, 6-month supplies) to increase AOV while staying first-order profitable. Ash's strategy is similar, aim for first-order profitability, but test subscription offers to see what your take rates support.

The key is testing both approaches: some landing pages optimized for immediate profit, others for subscription conversion, then let the numbers tell you what works for your specific business model.

The market is always the final judge, regardless of how confident you feel.

Sometimes your best ideas become your most expensive lessons. Matt spent $2M launching Football Supplements with custom products for players, Real Madrid sponsorships, and Barcelona endorsements. 

On paper, it looked like a $100M opportunity. 

18 months later, he shut it down completely—zero product-market fit despite perfect partnerships and marketing.

We've seen this pattern repeatedly: amazing concept, solid execution, total market rejection. 

Ash experienced it when he bought a coffee brand with Post cereal licensing deals for Fruity Pebbles and Cocoa Pebbles flavors. The nostalgia angle seemed genius, but timing killed it. The market was moving toward healthier options, not sugary coffee.

The lesson: test small before you swing big. 

Even when you have money in the bank and confidence in your idea, validate demand with landing pages, samples, and small batch sales before full production. 

The market will tell you the truth faster and cheaper than any focus group or market research report.

No matter how sure you are, the market never lies.

There are 2 silent killers that feel like smart business moves but compound into major problems you don't see coming.

1) Over-promising to hit your numbers

When you're desperate for conversions, it's tempting to make claims you can't back up. 

Matt's skincare brand could promise "wrinkle-free skin in 2 weeks" because it converts better, but when customers don't see miraculous results, you've created negative word-of-mouth that kills your brand faster than any competitor could.

2) Launching products without getting immediate customer feedback

At Obvi, we learned this when we launched a superfood formula with cayenne pepper. Our team loved the spicy kick, but customers found it too hot. 

Without real-time feedback through our community, we would've spent months selling something people didn't actually want.

Both killers stem from the same problem: chasing short-term numbers over long-term customer experience. The fix is promising realistic outcomes and building feedback loops that catch problems in weeks, not months.

Failure is just expensive education; the key is reframing how you think about it.

Mentally, think of every failure as climbing a wisdom ladder; the more you learn from mistakes, the more money you'll make long-term. 

Matt's philosophy is simple: try to fail as fast as possible because the faster you fail, the faster you learn. 

There's no point getting emotional about something that's a prerequisite for success.

Practically, this means finding solutions fast. When campaigns fail, immediately tap your network for help. Ash will talk to 10 different media buyers about one ad account issue. 

Put your ego aside. Not knowing something just means you're still learning.

Financially, the strategy is the same: fail fast, cut losses quickly, extract the lesson, move to the next test. Don't throw good money after bad just because you've already invested.

Simplicity wins, but only when you know what message actually matters to your customers.

The human mind burns mental calories processing information. When you throw multiple messages at someone, their brain works harder and they tune out. 

Apple is a master at this. When they launched MacBook Air, their entire message was "Thinnest MacBook ever created." 

No processor specs, no battery life, no other features. Just one clear message repeated until it stuck.

Most brands try communicating every benefit at once, so nothing lands. But simplicity only works when you know what your customers actually care about. 

That's where building genuine relationships becomes crucial. 

When you're connected to your customers, building community, listening to feedback, knowing them by name, product development becomes obvious because they tell you exactly what they're willing to pay for.

At Obvi, 90% of our product decisions come from customer requests, not market research reports. We never wanted to make cotton candy collagen because none of us liked cotton candy, but customers kept asking. 

And it became a best seller because we listened instead of assuming we knew better.

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