Eight Brands, One AI: What Are They Actually Doing With AI in Marketing?

A while back, I came across a Klaviyo AI trends report.

One number in it stopped me cold: nearly half of marketers say AI has noticeably boosted their productivity and performance.

Nearly half.

Think about that for a second. Two years ago, everyone was arguing over whether AI would replace them. Today, roughly one in every two marketers can't live without it.

But there was another set of numbers in the report — and they were even more interesting.

• 49% want AI to benchmark their performance against their peers.
• 44% want AI to surface that signup form at exactly the right moment.
• 32% want to use AI for testing and optimization.

See the pattern?

What people want is no longer just "help me write a couple lines of copy." They want AI to actually get its hands dirty inside their own business data.

So has anyone already done this? And how's it going?

Let me tell you eight brand stories. They share one thing: they all use Klaviyo's CRM as the foundation for AI — email, SMS, reviews, and analytics all on one platform, so the AI actually has something to chew on.

1. Culture Kings: Eight Million Customers, and They Stopped Sending "Blast" Emails

Culture Kings is an Australian streetwear brand with eight million customers worldwide.

Eight million. Picture what it would look like if, ten years ago, you blasted the same email to all of them.

Pajamas pushed to people in baseball caps. Winter coats pushed to customers on the equator. Unsubscribe, unsubscribe, unsubscribe.

Culture Kings used to run a fragmented marketing stack: email in Klaviyo, SMS in Yotpo, data that never lined up, personalization off the table. Then they moved SMS into Klaviyo too, and the data finally lived in one place.

Then AI stepped in.

They lean on three things above all: Segments AI slices those eight million people into precise cohorts (by region, by lifecycle stage, by SKU); Subject Line AI drafts their email subject lines; and dynamic product recommendations power personalized merchandising.

The result?

Global SMS click-through rate jumped 388% year over year. In Australia, SMS unsubscribe rates dropped — 43% lower for marketing emails, 64% lower for automated flows.

Jarrod Hinvest, Culture Kings' head of ecommerce, put it perfectly:

We have completely different customer bases across three regions, each needing its own playbook. Klaviyo plus its AI — that's exactly what this is for.

In plain terms, AI is doing the thinking work here: figuring out which email goes to whom.

2. Happy Wax: How AI Picks the Single Review Most Worth Showing

Happy Wax makes home fragrance — wax warmers, wax melts, that sort of thing.

They did something similar to Culture Kings: pulled email, SMS, and customer reviews all into one Klaviyo platform. Consolidating the tool stack alone cut costs by 10%.

But what really caught my eye was how they use AI to handle reviews.

If you run an online store, you've hit this problem: a product page stacked with hundreds of positive reviews — which single one is most likely to sway the customer who's hovering over the buy button right now? Pick by hand? You can't keep up. Show all of them? That's the same as picking none.

Happy Wax lets AI do it.

Inside their abandoned cart recovery and win-back flows, AI selects the single most relevant review for each individual customer and surfaces it.

This isn't "showing off reviews" anymore. This is one-to-one delivery — the right words, to the right person, at the right moment.

The numbers back it up: in August 2024, their Klaviyo SMS revenue rose 18% year over year; in the first hundred days after launching Klaviyo Reviews, review submissions climbed 27% year over year.

Rachel Fagan, VP of Marketing, says she now lets AI take the first pass every time she builds a segment:

Nine times out of ten, it's right.

Nine times out of ten.

3. Saranoni: One Form, in the Right Spot, and Submission Rates Climb 14%

Saranoni makes high-end blankets. They were already on Klaviyo, then briefly flirted with a cheaper platform, then came back.

Why come back? Deliverability and automation capability were worth the price.

In the first half back, the platform delivered 35x ROI, with 36% of attributed revenue coming from automated flows. Those flows expanded from just two email-only sequences to over twenty cross-channel ones.

But the sharpest move in this story was the form.

When the signup pop-up appears, and where it lands on the screen — that used to be a gut-feel guessing game. Saranoni used Klaviyo AI's form display optimization and let the machine run the tests. The winning version lifted form submission rates by 14%.

Fourteen percentage points — purely because the placement and timing were right.

Stephanie Contreras, lifecycle marketing lead at agency BMO Media, said it plainly:

Every brand is different. AI helps us figure out what actually converts for Saranoni.

Someone else's best practice can't be copy-pasted. What Saranoni computed was a best practice that belongs only to them.

4. LifeStraw: One Sentence, a Whole Automation Flow Generated

LifeStraw makes water filters. After switching from ActiveCampaign to Klaviyo, the share of ecommerce revenue coming from email jumped from 3% to 33%. In the first half of the year, Klaviyo ROI hit 69x.

But what I want to talk about is how AI saves time.

Eugenia Martin, head of DTC sales, once needed to build a "subscription confirmation" flow. How did that used to go? Map the structure, write the copy, configure the trigger, set the delays... a solid hour, gone.

This time she used Flows AI.

One sentence of prompt.

AI generated the entire flow structure on the spot.

Martin said that single move saved at least forty minutes. Her words:

It just built the skeleton of the flow for me. Mind-blowing.

Think about it — a flow that used to take a person an hour to assemble now starts from one sentence, needs a little tweaking, and it's ready to go. No wonder she describes Klaviyo's automated flows as "running day and night — we don't have to do a thing."

5. Force of Nature: Move Over From Mailchimp, Then Double and Double Again

Force of Nature makes eco-friendly cleaning products. They moved from Mailchimp to Klaviyo.

After the move, Klaviyo-attributed value rose 52% year over year, flow-driven revenue climbed 140% year over year, and flows accounted for 46% of attributed revenue.

Why move? Because they needed AI-driven segmentation.

Eco-friendly cleaning products have repurchase cycles, different SKUs, different purchase stages. Force of Nature used Segments AI to slice customers finely by journey stage, then put those segments to work in two ways: SKU-level repurchase reminders, and feeding Meta ads for lookalike audience expansion.

CMO Melissa Lush nailed the key point:

Segments AI lets us build segments fast and accurately — as granular as we need.

"As granular as we need." That's where AI segmentation gets genuinely valuable. The few minutes saved building a segment is secondary; the real point is, you can now reach audiences that were simply impossible to isolate before.

6. Tata Harper: AI Tests 20 Versions and Picks the One That Converts

Tata Harper makes plant-based skincare. After moving to Klaviyo, they had AI do something impressively thorough: test the placement and timing of their email and SMS signup forms.

Desktop, mobile, across different timing and placement combinations — AI spun up 20 versions to run at once.

In the thirty days after the winning version went live, submissions for both form types rose more than 65% compared to the month before the test.

Heidi Jessop-Maund, SVP of Digital, laid it out clearly:

This Klaviyo solution lets the brand genuinely put its customer data to work — using AI for real-time optimization that drives strategy.

The keyword is real-time. Set it once at the start of the year and ride it for twelve months — that old approach doesn't cut it anymore. You need to keep running, keep picking the optimal version, continuously.

7. Every Man Jack: Predicting When Each Customer Will Place Their Next Order

Every Man Jack makes men's personal care. Annual revenue tops $100 million, and their distribution includes big-box retailers like Target and Whole Foods.

The lifeblood of personal care is repeat purchase. But their old email platform had a killer limitation: replenishment reminders could only fire at a fixed 45 days post-purchase. Their customers' actual repurchase cycle was 75 days.

A full month off.

Either the reminder fired too early — the customer hadn't finished the product yet and found it annoying — or it never fired at all, because the system only knew how to pull the trigger at day 45.

After moving to Klaviyo, AI's predictive analytics calculated a "predicted next order date" for each subscriber, and the replenishment flow fired against that date.

In ninety days, predictive analytics segments alone contributed 12.4% of Klaviyo-attributed revenue.

Troy Petrunoff, senior retention marketing manager, said what he values most is the sense of control:

I trust Klaviyo AI because it saves me time, activates my customer data, and personalizes timing. Most importantly — how I use it, and when, is entirely my call.

"AI does the work, humans make the call." That's exactly where AI belongs.

8. Willow Tree Boutique: Pushing the Premium Pieces to the People Who Can Actually Afford Them

Willow Tree Boutique has been selling for over thirty years. They have brick-and-mortar stores, an online shop, and a free mobile live-shopping app.

They started segmenting by email activity, browsing behavior, and app usage early on.

But there was one slice they couldn't cut: by purchasing power.

The result: some subscribers received product pushes far beyond their spending level. Great products, but the wallet couldn't stretch that far — all for nothing.

Then they turned to Klaviyo's predictive analytics and started segmenting by "predicted next purchase date" and spending power.

In the first half after launch, email-driven revenue rose 53%.

The playbook is direct: push high-ticket items to the cohort that predictive analytics flags as having the spending power. During big sales events, adjust the cadence — for BFCM (Black Friday Cyber Monday) 2023, they pulled out the cohort that hadn't purchased in over 60 days (normally 30 days) for a dedicated send, and delivered their highest single-event revenue ever.

Jade Richardson, email strategist at agency EK Creative, said:

After building segments with Klaviyo's predictive analytics, every single one of our metrics improved, and revenue climbed hard. It's like a whole new world opened up.

Stack These Stories Together — What Do You See?

Eight brands, eight stories. But stack them together, and a few main threads jump out.

First, the data has to live in one place. Almost every story starts the same way: "first, move email, SMS, reviews, and analytics onto one platform." No matter how smart the AI is, it can't work magic without unified data. Happy Wax cut costs by 10% after consolidating; Culture Kings could only do cross-channel tracking after consolidating. The prerequisite for AI is unified data.

Second, where AI really earns its keep is the work buried deep in the business. Writing copy barely makes the list. What's genuinely valuable is this kind of work: which review to show to whom, predicting when someone will repurchase, when a form should appear, generating an entire flow from one sentence. This work is both specific and tedious — in the past it either required a small army of people, or it simply didn't get done. Once AI takes it on, people are freed up, and the results are better.

Third, humans haven't left the building. Troy Petrunoff's "AI does the work, I make the call," and Stephanie Contreras's "helps us figure out what actually converts for Saranoni" — they're saying the same thing: AI is a tool, the judgment is still human. The best state of play is AI computing fast and granular, and humans deciding how to use what it computes.

Over four in ten marketers say AI has already made them more capable. These eight brands are, in all likelihood, among the frontrunners of that group.

There's no special secret to it.

They just put AI in the position where it can really do the work.