The US just killed the $800 de minimis exemption.

Every package into the US now faces 10 145% duties.

No exceptions.

Testing Okiela on a real Shopify store this week.
First thing it flagged:
a SKU with strong GMV, 28% discount rate, 18% refund rate, and estimated payment fees eating another 3%.
Net margin: roughly 4%.
Before COGS.
The founder knew it was "not their best product".
They didn't know it was this close to zero.
That's not a data problem.
That's a "I was flying blind and the instrument panel just turned on" moment.
That's the moment I'm building Okiela for.

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#buildinpublic #analytics #data #shopify #ecommerce #saas #solofounder #okiela #shopifytips #ecommerceprofits #ecomtips #shopifytutorial #dropshippingtips #shopifystore #smallbusinessowner #aitools #profit #pricing

Social commerce will hit $2.6 trillion globally in 2026.
50.6% of US social media users made at least one social purchase last year.
Incredible scale.
But here's the uncomfortable question nobody asks:
Which brands are actually making profit from it?
TikTok Shop drives impulse buys.
Instagram drives aspiration clicks.
Both can destroy your margin if your unit economics are broken underneath.
Revenue through social is easy to celebrate.
Profit through social is something you have to deliberately engineer.
Knowing your real numbers per channel is not optional anymore - it's survival.

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87% of ecom merchants raised prices in 2026 to fight tariffs and inflation.

Most survived. Some thrived.
A few made a quiet mistake: they raised revenue, but not profit.
Higher price tag + same COGS + higher ad spend to justify the new price point = margin stayed flat or got worse.
The lesson from every inflationary cycle in history:
raising prices only works if your cost structure is honest.
If you don't know what your real cost per SKU is,
you're repricing in the dark.
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Apparel brands in 2026: up to 40% return rate.

Electronics: 8 10%.

Beauty: 4 10%.

The "buy 3, keep 1" behaviour is now a business model risk, not just a customer quirk.

During the Great Depression, lipstick sales went up.

During the 2008 recession, cheap beauty boomed.

In 2026, the same thing is happening again.

Ecom data confirms: beauty and skincare are outperforming luxury categories while EBITDA margins in mid-market DTC brands are compressing to 7 8%.

I m not the podcast every week / webinar every month kind of founder.
I m the stare at a spreadsheet at 11:30pm trying to understand why net profit and vibes don t match kind of founder.
For a while I thought that was a weakness.
Now I m trying to turn it into the whole point of Okiela.
Most of the people I m building for are like me:
- they don t want another hype dashboard,
- they don t want to become full time data analysts,
- they just want to know, in plain language,
which products and channels are actually worth the stress .
So instead of trying to become a louder founder,
I m trying to make the product do the talking:
1. clear sanity checks vs Shopify numbers,
2. honest this is estimated vs this is verified ,
3. simple raise / cut / kill suggestions tied to real profit.
If that resonates with you, you re basically the reason Okiela exists.
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I keep asking myself one annoying question while building Okiela:
How fast should a founder get to their first real oh shit moment?
Not another chart.
Not another KPI acronym.
A real punch in the gut insight, like:
This SKU that looks like a hero is actually leaking money every month.
This channel only works because you re underpaying yourself.
If you keep this discount structure, your bestseller will never make sense.
My current benchmark for Okiela v1:
From the moment a Shopify founder connects or uploads data,
it should take a few minutes to:
1. sanity check vs Shopify s own numbers,
2. see the 3 biggest leaks by SKU / channel,
3. get 1 2 moves they can actually make this week.
If it takes longer than that, I assume it s my fault, not theirs.

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I used to think revenue up = we re doing fine .
Then I started doing FP&A and realized how easy it is to lie to yourself with pretty dashboards.
You can have:
record high revenue,
okay ROAS,
a busy team
and still quietly bleed cash because of COGS, fees, refunds, shipping, discounts all pulling in different directions.
That s basically why I m building Okiela:
to give founders one brutally honest view of what s actually left after everyone else gets paid .
No growth hacks, no magic AI.
Just boring, explainable profit math that doesn t change depending on who s pitching the story.
If you ve ever had that feeling of
the numbers look good but my bank account doesn t ,
that s the feeling I m trying to fix.
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#buildinpublic #analytics #data #shopify #ecommerce #saas #solofounder #okiela #shopifytips #ecommerceprofits #ecomtips #shopifytutorial #dropshippingtips #shopifystore #smallbusinessowner #aitools #profit #pricing

I ll be honest:
before building Okiela, I also got hyped by profit dashboards .
The screenshots always look amazing:
big Net Profit numbers, pretty charts, dark mode.
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But once you sit down with real founders and real data, a bunch of common issues keep popping up:
- Some tools call it profit , but it s literally just revenue minus COGS.
- No payment fees, no platform fees, no shipping cost, no COD failures, no overhead.
- Looks great in a screenshot, feels very different when payroll and ad invoices hit.
- Some tools import from Shopify, but their GMV and order count don t match Shopify s own reports.
The answer is usually we calculate it differently .
Which is basically a nice way of saying just trust us .
- Refunds often get lumped into one vague line.
Full refunds, partial refunds, shipping only refunds, refunds hitting next month all mashed together.
- Good months look amazing. Refund months feel like a mystery.
And onboarding
Connect all your tools, map all your costs, fill in every COGS and overhead line then we ll show you something.
Meanwhile, most founders have 15 minutes between calls, or half an hour at night after putting kids to bed.
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I don t think those products are bad .
They re just not built for how messy real life looks.
So when I started working on Okiela, I forced a few rules on myself:
Call things what they are.
- Revenue is revenue.
- Gross profit is gross profit.
- True Profit only appears when the math is actually there.
Make the first step a sanity check against Shopify/the platform.
If GMV and order count are off, we need to explain why.
No it s close enough, don t worry .
Treat refunds like first class citizens.
Every refund event, per line item, including which fees are kept or returned.
BFCM sales in November, refunds in January they need to show up clearly in the timeline.
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Don t hold value hostage behind a huge setup.
The flow has to look like:
1. Check numbers vs Shopify.
2. Add basic COGS/costs.
3. See 2 3 obvious profit leaks.
4. Get 1 2 moves you can actually make today.
I m not trying to build the flashiest analytics tool on the market.
I m trying to build the one screen a founder can open and say:
If we stopped selling tomorrow, here s how much money we really made in the last 12 months.
If you ve ever stared at a profit number and felt that something was off, reply profit or DM me.
I d rather you plug your own data into Okiela, break it if you can, and then tell me whether it deserves to exist.
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