8 Brands That Turned AI Marketing From Buzzword to Bottom Line

A few days ago, I came across an AI trends report published by Klaviyo.

The numbers were pretty interesting. Nearly half of marketers said AI had "significantly improved" their work efficiency and output.

But the second half was even more interesting. This group of marketers who'd been steeped in AI for two or three years? They started complaining.

49% wanted AI to help them with competitive benchmarking — to see where they stood compared to their peers. 44% wanted AI to automatically decide when a website pop-up should appear. 32% wanted AI to run their A/B testing.

Notice something?

They're no longer asking AI to "help me write a sentence." They're asking it to "help me make decisions."

AI in marketing is evolving from toy to tool, from tool to colleague.

Today, I'm going to tell you the stories of 8 brands. Let's see how these companies actually used Klaviyo's AI to turn "we're using AI too" into real revenue and profit.

Culture Kings: 8 Million Customers, and No "Spray-and-Pray"

Culture Kings is an Australian streetwear brand. 8 million customers, spread across 3 regions, with wildly different audiences.

How did they used to do marketing? Blast campaigns. One email template for everyone. The result? A young sneaker buyer gets a notification pushing kids' clothing. Do you think this brand understands you? Chances are, you'd unsubscribe.

The first thing they did was move SMS from Yotpo to Klaviyo, merging it with their email.

The core purpose of the merger was one thing: unified data. The same customer's email behavior and SMS behavior, visible in one dashboard. Then they used Klaviyo's Segments AI for audience segmentation.

The results? Global SMS click-through rates jumped 388% year-over-year. In the Australian market, campaign unsubscribe rates dropped 43%, and automated flow unsubscribe rates dropped 64%.

Culture Kings' head of ecommerce said something that really stuck with me: "Our audience spans 3 regions, and each one needs a different approach. Klaviyo's AI features are our accelerator."

Happy Wax: AI Picks Better Reviews Than Humans Do

Happy Wax makes home fragrance products. Wax warmers, wax melts — the average order value isn't high, so they rely on repeat purchases and word of mouth.

They did two smart things.

First, they moved email, SMS, and customer reviews all onto Klaviyo. One platform managing three things. Tech stack costs dropped by 10% immediately. Attribution became clear too. Before, when an order came in, was it from email or SMS? Endless arguments. Now the data's all in one place — crystal clear.

The second thing was even more interesting. They used AI to automatically select customer reviews and plug them into their cart abandonment flow and win-back flow.

What does "selecting reviews" mean? When a customer "added a product to their cart and then left," which review do you use to pull them back?

The traditional approach is for a marketer to manually pick a good one and paste it in. But here's the problem: everyone cares about different things. Some people care about the scent. Some care about how it looks. If you paste "smells great," it won't move someone who cares about aesthetics.

Happy Wax's approach was to let AI automatically match the review most likely to resonate with each user based on their past behavior. The result? In August 2024, SMS-driven revenue was up 18% year-over-year. In the first 100 days after launching Klaviyo Reviews, review submissions were up 27% year-over-year.

Their VP said something telling: "I now start every segmentation exercise with AI. Nine times out of ten, it's right."

Nine out of ten. Think about what that means.

It means a decision that used to require a marketing director's seasoned judgment can now be made by AI at 90% accuracy.

Saranoni: Left, Came Back, and Realized It Was Worth It

Saranoni makes premium blankets. They took a detour.

To save money, they switched from Klaviyo to a cheaper platform. The result? Email deliverability dropped, and their automations couldn't keep up. After struggling for a while, they came back.

In the first 6 months back, they saw 35x ROI. 36% of Klaviyo-attributed revenue came from automated flows. They expanded from 2 email flows to over 20 cross-channel automations.

They used AI for two things.

First, form display optimization. That pop-up on the website — how many seconds after the user arrives should it appear, where should it appear, how should it be positioned on mobile vs. desktop? AI tested automatically and picked the best version. The winning variant saw form submission rates jump 14%.

Second, they used Segments AI for geo-targeted segmentation. Every segment created saved at least 10 minutes.

10 minutes doesn't sound like much. But think about it — if you create 20 segments a week, how much is that over a year?

Over 170 hours. That's more than a month of a full-time employee's workload, swallowed by AI.

Lifestraw: From 3% to 33% — What Happened In Between?

Lifestraw makes water filters. A category that sounds essential but is notoriously hard to market.

They used to be on ActiveCampaign. Email revenue accounted for only 3% of total revenue.

3%. That basically meant the email channel was dead.

After switching to Klaviyo, in the first half of 2024, email's share of revenue jumped from 3% to 33%. A 10x increase. 69x ROI.

Their DTC lead said something that made me laugh out loud: "These automated flows are like a workhorse — they work day and night without stopping. We don't have to do anything. It's incredible."

She used Flows AI for one specific thing: she generated an entire subscription confirmation flow with a single sentence.

One sentence. 40 minutes of work, saved.

Her exact words: "Flows AI basically built the flow structure for me. I think that's incredible."

Force of Nature: A Small Team's AI Playbook

Force of Nature makes eco-friendly cleaning products. Small team, switched from Mailchimp to Klaviyo.

52% year-over-year growth. Automated flow revenue up 140% year-over-year. Flow revenue accounted for 46% of Klaviyo-attributed revenue.

They used Segments AI for precise audience segmentation — not just for email and SMS, but also to guide their ad targeting on Meta (Facebook). Segments built in Klaviyo were exported to Meta to power lookalike audiences, and both customer acquisition cost and ROAS improved compared to before.

Their CMO said something straight and true: "Klaviyo lets a small team like ours use enterprise-grade tools."

Tata Harper: 30 Days, Sign-ups Up 65%

Tata Harper makes plant-based skincare. They used AI to optimize how their registration form was displayed.

Because all their data was in one platform, they had AI generate 20 variants in one go, covering different positions and timing across desktop and mobile.

AI tested on its own and picked the winner. Within 30 days of the winning version going live, sign-ups were up more than 65% year-over-year.

20 variants, left to AI to run. If you asked a marketing team to do that manually, just scheduling the tests would be a serious time sink.

Every Man Jack: The Replenishment Email Was Off by 30 Days

This is the story I think best captures the value of AI.

Every Man Jack makes men's personal care products. Annual revenue over US$100 million, with channels including their own ecommerce store, Target, and Whole Foods.

The core of men's personal care is repeat purchases. But their replenishment email was hardcoded to send 45 days after purchase.

Here's the problem: their customers, on average, didn't repurchase until 75 days.

45 days vs. 75 days — a 30-day gap. Every email sent during those 30 days was wasted. Worse, if you push a customer to buy more before they've even finished the product, it feels like you're harassing them.

Klaviyo's predictive analytics calculated a "predicted next order date" for each customer, and the replenishment flow fired based on that personalized timing.

In 90 days, predictive segments contributed 12.4% of Klaviyo-attributed revenue.

Their head of retention marketing said something I strongly agree with: "I trust Klaviyo AI because it saves time and helps me personalize — but most importantly, the control stays in my hands."

That's a crucial point. Simply put, AI helps you make sharper decisions, but you're still the one calling the shots.

Willow Tree Boutique: A 30-Year-Old Store's New Weapon

The Willow Tree Boutique has been around for over 30 years, with multiple physical stores, an online shop, and a livestream shopping app.

They'd always been able to segment customers by email open behavior, browsing behavior, and app usage. But one challenge remained unsolved: segmenting by spending power.

The result? Budget-conscious customers received high-price product recommendations — and got scared off.

The way predictive analytics solved this was simple: segment customers by their "predicted next purchase time" and spending power level. Push expensive items to those who can afford them, and push value options to those who are budget-sensitive.

In the first 6 months, email marketing revenue was up 53%.

Even more interesting was BFCM (Black Friday Cyber Monday). In 2023, they pulled out the "no purchase in 60 days" segment for a special promotion (they normally only targeted the 30-day no-purchase group) — and it was their highest-revenue BFCM ever.

8 Brands, Done. What's the Pattern?

Think back over these 8 brands. They sell completely different things: streetwear, home fragrance, blankets, water filters, cleaning products, skincare, men's personal care, boutique women's fashion.

But what they're actually doing comes down to 4 things:

First, unify the data. Email, SMS, reviews, behavioral data — all in one place. When data is scattered everywhere, no matter how smart AI is, it can't perform without fuel. Culture Kings, Happy Wax, and Force of Nature all integrated first before talking about AI.

Second, let AI handle segmentation. Let AI automatically slice audiences based on behavioral data, replacing marketers going on gut instinct. Culture Kings handled 8 million customers across 3 regions. Force of Nature used segmentation to guide their Meta ad targeting.

Third, let AI run the testing. Saranoni and Tata Harper both let AI automatically run form variants — one saw a 14% lift, the other 65%. If you did that manually, there's no way you could run 20 variants.

Fourth, use predictive analytics to get the timing right. Every Man Jack calculated replenishment timing. Willow Tree calculated spending power and repurchase windows. This is the highest-ROI use of all, because when the timing is right, everything else falls into place.

In Klaviyo's report, there's a set of numbers that's particularly worth dwelling on. Nearly half of marketers say AI has significantly improved their efficiency. But the other half is saying: AI isn't deep enough yet.

Not deep enough where? In competitive benchmarking, in automated decision-making, in testing optimization.

In other words, AI has proven it can save time and boost efficiency. The next battleground is letting it help you make decisions.

8 brands are already ahead. What about you?