Sweat Pants Agency

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06/03/2026

Most brands try to fix churn after the customer is already slipping away.

Winback campaigns.
Discounts.
“We miss you” emails.
Cancellation flows.

Those can help.

But the bigger retention lever often happens earlier.

At acquisition.

What plan did they buy?
How was the offer framed?
Did they understand the product experience?
Were they gifted the product or did they choose it?
Did they buy monthly, prepaid, or annual?
Did you upsell them after their first positive experience?

Longer subscription intervals usually create better retention economics.

Not because they magically make the product better.

Because they give the customer more time to experience the value before making another decision.

Sometimes churn isn’t an email problem.

It’s an acquisition architecture problem.

06/03/2026

A lot of subscription brands accidentally weaken their own acquisition.

They say they want subscribers.

Then the website gives equal weight to one-time purchases.

The ads drive cold traffic.

The homepage shows too many paths.

The customer chooses the lowest-commitment option.

Then everyone wonders why CAC looks worse and LTV drops.

If subscription is the business model, the whole funnel has to support that.

The ad.
The landing page.
The offer.
The default path.
The incentive structure.
The post-purchase upsell.

One-time purchases can still exist.

But they usually shouldn’t be the front door unless you have a very specific strategy for converting them later.

Subscription growth is not just “run ads to a subscription product.”

It’s engineering the buying journey so the subscription feels like the obvious choice.

06/02/2026

Agency owners don’t talk about this enough.

Not all revenue is equal.

Some accounts create energy.

Some accounts drain it.

Some clients want to grow, move fast, test, learn, and make decisions.

Others want constant calls, constant explanations, constant reassurance, and tiny incremental wins that don’t justify the team’s time.

The hard part is that both may pay you.

But only one compounds.

When you have talented people, resource allocation matters.

Putting your best people on low-upside, high-friction accounts is one of the easiest ways to quietly damage an agency.

The question is not just:

“Can we service this account?”

It’s:

“Is this the best use of this person’s talent?”

Sometimes the best move is not hiring more people.

Sometimes it’s moving the right people to better opportunities.

05/29/2026

The best media buyers I’ve worked with are not just “Meta people.”

They’re marketers.

They understand creative.
They understand conversion.
They understand offers.
They understand customer psychology.
They understand when the problem is not inside the ad account.

That last one is the big unlock.

A mediocre media buyer sees bad performance and starts touching budgets.

A good media buyer asks:

Is the offer strong enough?
Is the landing page doing its job?
Are we sending traffic to the right page?
Are we measuring new customers correctly?
Are we testing meaningful creative angles?
Is this actually an account problem?

There is still skill inside the platform.

But the biggest wins usually come from outside it.

Creative. Conversion. Offer.

That’s the value chain.

The ad account is just where the signal shows up.

05/28/2026

A lot of Meta accounts don’t fail because the media buyer is dumb.

They fail because the account gets too clever.

Too many campaigns.
Too many ad sets.
Too many duplicated cost caps.
Too many micro-tests.
Too many ads with no meaningful spend.
Too many variables changing at once.

Eventually, nobody knows what’s working.

Worse, the algorithm doesn’t either.

I still see accounts where 100+ ads are technically active, but only a small fraction have enough spend to tell us anything.

That’s not testing.

That’s clutter.

A good account structure should make decisions easier.

What are we trying to learn?
What signal does Meta need?
What is the business goal?
What is the simplest structure that gives us reliable reads?

Complexity feels sophisticated.

But in paid media, simplicity often scales better.

05/06/2026

I used to think the subject line had one job: get the open.

The data says I was wrong.

I just analyzed 2,120 email campaigns across 19 brands from our portfolio.

What I found flipped my view.

The subject lines that win on opens are the ones that lose on revenue.

And the ones that win on revenue?

They're the ones marketers are told to avoid.

Here are the patterns:

→ ALL CAPS in the subject: 10 points less likely to be opened, but 11 points more likely to be clicked

→ A % discount in the subject: 19 points worse for opens, 5 points better for revenue

→ Urgency words ("ends tonight", "last chance"): 8 points worse for opens, 7 points better for revenue

→ Question marks: better for opens, worse for revenue

Read that again.

The features that look "spammy" are the features driving the actual money.

Here's why, and it's two mechanisms working at the same time:

One: deliverability.

Subject lines with %, $, ALL CAPS, and urgency get filtered to the Promotions tab. So they're not opened by your full list, just by the slice that goes looking for deals. Smaller pool. Pre-qualified.

Two: pre-selection.

A subject line with a number or a discount tells the reader what's inside before they click. They self-filter. The ones who open are the ones who want what's being offered.

A question mark does the opposite. It drives curiosity, not intent. People open because they want to know, not because they want to buy.

So here's the rule:

→ Want opens? Write curious. You'll land in the primary inbox and get clicks from anyone scrolling.

→ Want revenue? Write specific. You'll land in promotions and lose opens, but the people who DO open are buyers.

You can't do both with the same subject line.

The dashboard your team checks every morning is probably misaligned with the metric that pays the bills.

P.S. Length doesn't matter. Median subject was 34-35 characters across every quintile of every metric. Stop A/B testing length. Start A/B testing tone.

05/05/2026

So many things people accept as “best practices” in email marketing are just… wrong.

Here are a few:

Myth #1: Being aggressive upfront is a bad thing.

This is flat-out false.

In DTC, most subscribers who will ever buy do so in the first 7–10 days. After that, conversions drop off dramatically.

If you’re not being aggressive in that window, you’re missing the moment that matters most.

And there’s a second benefit: list hygiene.

If someone doesn’t open your first 5–10 emails, they’re probably not someone you should be sending to long-term.

Your welcome series isn’t just about revenue, it’s also your best filtering mechanism.

Myth #2: Subject lines are meant to get opens.

Not exactly.

We analyzed subject lines across a large portfolio of clients and audits, and saw something interesting:

The patterns that increased opens often decreased clicks and revenue.

Questions → higher opens, lower revenue

Urgency, numbers, promos → lower opens, higher revenue

Opens don’t pay the bills. Revenue does.

Myth #3: Unsubscribes are bad

Also false.

Higher unsubscribe rates are often positively correlated with higher revenue and revenue per recipient.

If no one is unsubscribing, you’re probably playing it too safe and leaving money on the table.

There are a lot more of these…

What “best practices” have you seen that don’t actually hold up?

04/29/2026

Everyone's talking about fully automating their ad accounts with AI.

I think that's a mistake.

Here's why.

When PayPal was getting destroyed by fraud in the early days, they had a hacker named Igor who kept breaking through. They tried full automation to stop him. It didn't work. Actually caused more problems.

So they tested something different. Algorithm plus human. AI flagged the patterns. Humans made the calls.

That combination is what eventually became Palantir. One of the biggest AI companies in the world. And they still use that same model today. AI with human workflow.

And that makes sense if you think about it.

If everyone has access to the same AI tools and everyone automates the same way, that just becomes the floor. The baseline. The minimum.

So where does the edge come from?

Not from automating everything. From automating the right pinch points and keeping humans in the loop for the decisions that actually matter.

I built a creative analysis tool that pulls 90 days of ad data, transcribes videos, generates scene notes, and maps performance to patterns. That used to take 6 hours manually. Now it runs in the background in 15 to 50 minutes.

But I still sit down and interpret it. I still make the calls on what to test next. The AI compresses the grunt work. The human finds the alpha.

Everyone's racing to remove themselves from the process entirely.

I'm racing to stay in it. Just at a higher level.

04/29/2026

I think a lot of people are looking at AI the wrong way.

To me, the biggest opportunity isn’t just automation or content generation. It is building a company brain.

For the first time, we can actually centralize institutional knowledge in one place.

Imagine this:
→ Your AI has access to call transcripts (Fireflies)
→ It can read Slack conversations
→ It understands your Gmail threads
→ It’s connected to your Google Drive and internal docs

When you connect all of these data sources, you’re no longer dealing with fragmented information. You’re creating a living, searchable, intelligent system that understands your business.

And this changes everything.

From a marketing perspective:
You can analyze reviews, ad comments, and support tickets to uncover real objections, identify winning angles, and spot patterns, not just anecdotes.

From a product perspective:
You can actually see what customers consistently like, dislike, and request, and make decisions based on signal, not noise.

From an operations and support perspective:
This “company brain” can evolve into first-line customer support, internal QA, onboarding, and more.

The real value of AI isn’t just doing tasks faster.

It is consolidating knowledge so every team can make better decisions.

The companies that win won’t just use AI.

They will build systems that think with them.

04/28/2026

We ran a test last week.

Took the ad copy and the video transcript from one of our top performing ads. Fed it into AI. Asked it to build a landing page that matched the messaging for cold Facebook traffic.

It rewrote the copy. Restructured the layout. Aligned every section to the ad the person just clicked on.

We launched it against our existing pages.

The result? Nearly 30% lower cost per new customer.

Not 30% more clicks. Not 30% better CTR. 30% cheaper customers.

And here's the wild part.

We found out days later that two of the three pricing buttons on the page were broken. They were sending people to a 404 error. The only button that worked was the monthly plan.

So the page was converting with one functioning checkout option. And it was still the best performer in the account.

Think about what that means.

The alignment between ad and landing page was so strong that people were converting even when the page was half broken.

Most brands spend months A/B testing button colors and headline fonts.

The alpha here is something different. You take a landing page that's already converting and align it with the specific ad that's driving traffic to it. The messaging matches. The angle matches. The promise matches.

I could see a future where every ad has its own landing page. A 1:1 relationship between the ad someone clicks and the page they land on. AI makes that possible now.

If you're running paid media and you haven't tested this yet, I'd highly recommend giving it a shot.

Address

231 Public Square Suite 300
Franklin, TN
37064

Telephone

+16612128533

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