Email and SMS underperforming? The fix isn't more sends.

Four surfaces, four tests, one week.

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The brands at 35-40% owned-channel revenue aren't better at email.

They're capturing more subscribers from the same traffic.

Across the brands I work with, email and SMS account for 18-25% of total revenue.

The difference between that and 35 to 40% almost always traces back to one variable: how many people who land on the site actually get on email and SMS lists.

Retention work tends to focus on what happens after someone subscribes - flows, segmentation, send cadence. If the capture rate on the front end is weak, optimizing everything downstream has a ceiling.

This newsletter covers the diagnostic to run first, then four specific tests - one per capture surface - to start moving the number.

Focus On List Growth

Email/SMS revenue has two inputs: list growth and revenue per subscriber.

List growth is largely ignored, while revenue per subscriber gets attention - flows, segmentation, and send frequency are optimized without considering the top of the funnel.

List growth is entirely a function of opt-in rate on the capture surfaces.

If you can move the site-wide opt-in rate from 2% to 4%, your list growth doubles on flat traffic, which compounds into owned-channel revenue over the following months.

The four surfaces where that rate lives are:

The site-wide pop-up
The exit-intent overlay
The SMS keyword graphic
The post-purchase capture screen

Operators have a number in their head for what SMS "should" cost per message.

That number is the reason a lot of brands run SMS at half the volume their list could handle.

Omnisend just dropped SMS pricing to $0.007/message. Same power as Klaviyo, but at a better price.

And the brands switching are saving up to 35% on their SMS costs.

The price drop matters, but the rebuild is what actually kills most migrations before they start.

So, Omnisend is migrating in 5 days, free:

> Humans manually rebuild your emails, automations, the whole setup
> 5 days from start to finish, not a quarter
> Pre-built paths for Klaviyo, Mailchimp, and Yotpo

That's where most of the brands I work with would actually be coming from.

See the new rates and what a migration would look like for your stack:

Learn More

Each Surface Has a Different Audience and a Different Test

Each surface reaches a different person at a different moment, which means the offer logic behind each one should be different too.

Treating them as a single unit is why most pop-up audits don't move the opt-in rate at scale.

The site-wide pop-up reaches cold traffic early in a session.
The exit-intent overlay reaches someone who's about to leave - higher intent, different offer receptivity.
The SMS keyword graphic is doing most of the work, converting paid social traffic into SMS subscribers.
The post-purchase capture screen reaches someone who has just bought, which is one of the highest-intent moments in the funnel and usually the lowest-effort asset in the stack - and each one requires a different test.

Offer Type Moves the Number, Not Design

The two variables that move the opt-in rate at the magnitudes that matter are offer type and the qualifying mechanism behind it.

The offer types worth testing against each other:

Discount-led (percentage off first order)
Free-gift-led (free sample or free shipping with first order)
Quiz or personalization-led (find your match, build your routine)
Early-access-led (join the list, get drops first)
Content or value-led (a guide, a routine, a resource)

The reason most A/B tests on pop-ups don't produce meaningful results is that they test variations of the same offer - different headlines on the same 15% off, different button copy on the same discount.

To move the opt-in rate, you have to test different offer types against the same traffic.

Three Numbers Tell You Where to Start

Before running any tests, three numbers tell you which surface to prioritize.

Pull opt-in rate by surface - site-wide pop-up, exit-intent, SMS keyword, and post-purchase. If this number can't be pulled cleanly by the surface, that's the first problem to fix. A single blended opt-in rate across all sources makes it impossible to determine where the leak is.

Pull 90-day second-purchase rate by acquisition source, separating discount opt-ins from non-discount opt-ins. The gap between those two numbers is the cost of the current offer mix.

Pull email and SMS as a percentage of total revenue. Below 25% points to the capture stack. Between 25 and 35% points to the offer mix. Above 35% points to flow architecture as the next variable to work on.

Different number, different place to focus. Running tests before pulling these three numbers means optimizing the wrong surface.

If you want a growth partner who is invested in helping you build a profitable business, someone who is going to push you to make changes that focus on profitable growth. Book a call - let’s chat.

One Test Per Surface, Run in Order

Site-wide pop-up

Run the current control against three alternative offer types: one discount, one non-discount incentive (free gift or free shipping), and one access or value angle (early access or a content offer) - minimum 14-day test window.

The winner moves to production and becomes the new control for the next round.

Exit-intent overlay

If there's no exit-intent overlay running, build one before testing anything else. The traffic leaving without converting is high-intent and currently getting nothing.

The test right now is 'exists' versus 'doesn't exist,' not optimization.

SMS keyword graphic

Test the offer hierarchy on the visual itself: free shipping vs. percentage off vs. free sample.

The graphic running on paid social is the conversion asset for the SMS channel.

Leaving it static is the same mistake as never refreshing the ad creative.

Post-purchase capture

If the order confirmation page or post-purchase email isn't asking for SMS opt-in when only email was captured, or for email opt-in when only SMS was captured, build that cross-channel ask first. It's the easiest capture in the stack and typically the most neglected.

Final Thoughts

Auditing all four surfaces simultaneously is the right long-term approach. In practice, most operators won't do that in week one.

Pull the three diagnostic numbers.
Find the surface with the highest traffic and the lowest opt-in rate.
Run the corresponding test from the list above and move the winner to production within 30 days.
Run the next surface in June.

The compounding effect on owned-channel revenue comes from making this a recurring quarterly process, not a one-time cleanup. The audit is the system.

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I appreciate you reading and as always if there's anything I can do to help you in anyway just respond to this email. I personally respond to every email I get.

- Kody ✌️