The First
48 Hours
of a Deal.

I have been on both ends of an acquisition table. I helped build brands inside WIN Brands Group that other people wanted to buy, and I have written checks for businesses myself. The pattern that holds across all of it: most deals that die should have died faster. People sink three weeks and real legal spend into a brand that a sharp two-day look would have ruled out.

So I run a screen. The first 48 hours is not deep diligence. It is a deliberate, time-boxed pass that answers one question: is this worth a serious look, or do I walk now. I am not trying to value the business in two days. I am trying to find the reason to say no before it costs me.

Here is the exact pass, in the order I run it.

Speed is
the whole
point.

A full diligence cycle on a brand burns weeks and real money. Accountants, a lawyer, your own time pulled off everything else. If you run that machine on every deal that crosses your desk, you go broke and slow at the same time. The screen exists to protect that machine.

The first 48 hours is pattern recognition, not modeling. I am looking for the thing that kills the deal, because the thing that kills the deal almost always shows up early if you know where to look. Most of the killers hide in plain sight in the data room. You just have to read it the way an operator does, not the way a spreadsheet does.

Not how much.
How good.
How repeatable.

Top-line revenue tells me almost nothing in hour one. I want to know the quality of it. Is this revenue that comes back on its own, or revenue the business has to buy again every single month with ad spend? Those are two completely different businesses wearing the same number.

First read: the split between new and returning customer revenue. A brand where 60 percent of monthly revenue is returning customers is a real asset. A brand at 90 percent new is a paid-traffic arbitrage that stops the moment the ad account does. Second read: discount dependency. If the revenue only exists at 30 percent off, you are buying a promotion calendar, not a brand.

I also pull margin honestly. Gross margin after shipping, payment processing, and returns, not the rosy number on the deck. A brand can post strong revenue and make nothing once you load the real cost of getting product to a door. This is where I lean on having run the math myself across the LTV mistakes most brands make.

One channel
is a single
point of failure.

This is the check that has saved me the most money. I open the analytics and I look at where traffic and revenue actually come from. Concentration here is the quiet killer of DTC brands. A business doing well on the back of one Meta account, one viral TikTok format, or one Google campaign is one algorithm change away from a cliff.

I want to see the breakdown across paid social, paid search, organic, email, and direct. A brand with a real direct and organic base has earned demand. A brand that is 85 percent paid social has rented it, and the rent goes up every year.

The cohort
curve never
lies.

If revenue quality is the headline, the cohort chart is the truth behind it. I want to see how each monthly cohort of customers behaves over the following 6 and 12 months. Healthy brands show cohorts that flatten and hold, with a meaningful repeat rate. Brands in trouble show cohorts that decay to near zero, which means the business is on a treadmill, replacing every customer it ever earned.

The dangerous version is a brand whose recent cohorts are worse than its older ones. That tells me the unit economics are deteriorating under the surface even while top-line looks fine, and it usually shows up first in CAC payback stretching out by cohort. I have written more on these growth inflection points and why they matter so much at the point of sale.

Then the stack. I look at the Shopify app list and the broader tech setup. Two questions: is anything load-bearing and fragile, and is anything bleeding margin. A brand running 40 apps it does not need is fixable. A brand whose entire subscription program lives in one app with a sketchy contract is a real risk I need to price in.

Who actually
runs this
thing.

Two dependencies sink more brand deals than anything financial: supply and the founder. On supply, I want the supplier list and the concentration. A brand that buys 80 percent of its product from one factory with no second source is fragile in a way the financials will not show until something breaks. Lead times, minimum orders, and whether the relationship is contractual or a handshake all matter.

On the founder, the question is blunt: does the business work without them. If the founder personally holds the supplier relationships, runs the ads, is the face of the brand, and answers the support tickets, then I am not buying a business. I am buying a job, and the person whose job it is wants to leave. That is the single most common reason a brand looks great and falls apart 90 days after close.

Make the call.
Then commit
or walk.

At the end of 48 hours I have a clear picture. Not a valuation, a verdict. If revenue quality is decent, traffic is reasonably diversified, cohorts hold, the stack is sane, supply has a backup, and the business survives the founder leaving, then it earns deep diligence. If two or more of those fail, I walk, and I do it without apology.

The discipline is in honoring the screen. The deals that hurt are the ones where the screen said no and I talked myself into a yes because I liked the brand. Liking the brand is not a thesis.

If you are looking at a brand right now, the fastest thing you can do is run this pass before you spend a dollar on diligence. And once you are past the screen, the next read worth your time is the red flags that actually kill a deal versus the ones people overweight.