Klaviyo Case Studies: What Top Brands Report From Flows
I read eight published Klaviyo case studies for the pattern. Club L got two thirds of its email revenue from two flows. Here's what actually moved the numbers, and what none of them mention.
Most Klaviyo case studies get read wrong.
Founders skim them for the big number, feel a little jealous, and close the tab. I did the opposite this week. I opened eight published Klaviyo case studies, wrote down every number and every tactic, and looked for what repeats.
Here's the short answer. Across these Klaviyo case studies, the gains come from a few core flows (welcome, abandoned cart or checkout, browse abandonment) plus tighter segmentation, not from sending more email. Club L gets 33% of its revenue from Klaviyo, and two automated flows produce two thirds of that. Two flows. That's the pattern.
And there's one thing none of these case studies talk about. We'll get to it.
The brands in these case studies didn't win by sending more. They won by sending fewer emails to the right people, through a handful of flows that run every day without anyone touching them.
What do Klaviyo case studies actually report?
Every number below comes from the brand's own case study page on klaviyo.com. I'm quoting them as published, with their timeframes. These are Klaviyo's success stories, so read them as the best cases, not the average.
| Brand | What Klaviyo reports | The move behind it |
|---|---|---|
| Club L | 33% of revenue from Klaviyo; welcome and abandoned cart produce two thirds of it | Welcome offer converting 11%, cart email within an hour, second email the next day |
| Saranoni | 36% of Klaviyo revenue from flows in the first 6 months | Went from 2 flows to 20+, welcome variants per sign-up channel |
| Hint Water | Flow revenue up 133% period over period in the first 3 months | Cross-channel nurture and post-purchase flows for leads and one-time buyers |
| Minnow | Flow revenue up 37% year over year, year to date | Split abandoned cart for prospects vs returning customers, fewer full-list sends |
| Dagne Dover | 44% week-over-week revenue lift in the abandoned cart flow | An AI flow audit found the first email was being blocked |
| Maison Miru | Abandoned checkout flow added 3% to annual revenue; browse abandonment added 2% | Purges non-openers aggressively, list still grew from 50K to 110K |
| Taylor Stitch | 60% increase in revenue per recipient | 40 to 50 behavior-based segments a month, half the email volume |
| Boston Proper | 54% of ecommerce revenue from Klaviyo in 2025 | Channel affinity and RFM-triggered flows |
One caveat on Taylor Stitch: that case study covers January and February 2017. Old, but the lesson aged well, so it stays.
Source: each brand's Klaviyo case study page on klaviyo.com. Club L reports revenue contribution from email and SMS; Boston Proper reports 2025; Montana Knife Company reports the last 12 months.
Which flows show up in almost every Klaviyo success story?
The same three, over and over.
The welcome flow. Club L gives new subscribers a saving on their first purchase, and Klaviyo reports that welcome flow converts at 11%. Saranoni didn't stop at one welcome flow. It built separate versions for different sign-up channels, because someone who joins from a pop-up on a product page isn't the same person who joins from a giveaway. If you're building yours, the Klaviyo welcome flow examples post breaks down what the good ones say in email one.
The abandoned cart or checkout flow. Club L's first cart email goes out within an hour and converts nearly 11%, and the second, sent the next day, converts a further 7%. Maison Miru's abandoned checkout flow added 3% to annual revenue. Minnow added conditional branching so a first-time prospect and a returning customer get different messages. The nine teardowns in our Klaviyo abandoned cart flow examples post show what that split looks like in practice.
Browse abandonment. Smaller, steadier. Maison Miru's browse flow nudged people a couple of hours later to come back for a reward and added 2% to revenue. Our Klaviyo browse abandonment flow guide covers timing.
Here's the thing. Minnow runs 22 live flows. Dagne Dover runs 30+. But when these case studies explain where the money came from, they keep pointing back to the same two or three. Flow number 23 is a rounding error. Flow number one is the business.
A brand with 22 flows and a brand with 3 good ones look different in the dashboard. On the bank statement, the gap is smaller than you'd think.
How did segmentation change the results?
This is the part founders skip, and it's the part I'd copy first.
Taylor Stitch built 40 to 50 segments a month and spent, by its own account, an hour at the start of the month and an hour in the middle building them. Then it tested. Sending to an engaged segment (people who'd opened more than three emails in 180 days) produced a 40% open rate, 3% click-through and 36 purchases. The broad send got an 11% open rate, 0.5% click-through and zero purchases. Same email. Different people.
The payoff: Taylor Stitch sent 50% of the emails it sent the previous two months, drove the same amount of traffic, and saw a 60% increase in revenue per recipient.
Minnow made the same call more recently. It cut back on full-list campaigns and split customers into one-time and long-time purchasers. Campaign click rate grew 126% year over year.
Maison Miru went further and purged subscribers who don't open. And the list still grew 190%, from 50K to 110K.
So the segmentation lesson is blunt. The blast feels like reach. It's really noise, and your best customers learn to ignore you.
Where does AI show up in these Klaviyo results?
This is where it gets practical, because two of these are about AI doing real work, today.
Dagne Dover's case study is my favorite of the eight. Its director of marketing ran a flow audit through Klaviyo's MCP server with Claude. The audit noticed something odd: the second email in the abandoned cart flow was getting the most opens. Why would email two beat email one? Because a Smart Sending setting was quietly blocking the first email for anyone who'd recently engaged with a campaign. Klaviyo reports the fix produced a 44% week-over-week revenue lift in that flow. She estimated it would have taken days to diagnose alone.
That's the honest version of "AI for email." The AI didn't write a magic subject line. It read the setup and spotted the broken pipe. If you're choosing a tool for that kind of work, I compared eight in the best AI email marketing tools for ecommerce, sorted by whether they read your store data.
Saranoni used Klaviyo's Segments AI to build zip code segments from a text prompt, saving 10+ minutes per segment, and tested AI-generated pop-up variations, one of which lifted form submit rate 14%. Hint Water used channel affinity to stop sending email to people more likely to act on a text, and vice versa.
If you want a quick read on where your own flows stand before you audit anything, start with the grader below.
What do Klaviyo case studies leave out?
Now the thing I promised.
Every one of these flows ends with a click. And every click lands on a page. The welcome email sends a new subscriber to a product page. The abandoned cart email sends a hesitant buyer back to the same product page that didn't close them the first time.
None of the case studies talk about that page. Fair enough, it's Klaviyo's story. But it's your money.
I learned this one the slow way. Flows are the messenger. The product page is the closer. A great messenger delivering people to a page that can't close is just a faster way to disappoint them twice.
Run the math on a store like this (a hypothetical). Its flows send 2,000 clicks a month back to product pages. The page converts 2.0% at an $80 average order value. That means revenue per visitor is $1.60. On 2,000 clicks, that's $3,200.
Same flows, same clicks. The page gets rebuilt to answer the buyer's real question ("will this actually work for me?") and converts 3.0% at a $95 average order value. Revenue per visitor is now $2.85. On the same 2,000 clicks, that's $5,700.
Conversion rate x average order value x 2,000 clicks. Before: 2.0% x $80. After: 3.0% x $95.
You didn't touch Klaviyo. You didn't write a new email. Every flow just got more valuable.
That's what we saw on a bedding brand's pages. Before: conversion rate 1.0%, average order value $125, so revenue per visitor was $1.25. After the rebuild: conversion rate 3.5%, average order value $231, revenue per visitor $8.10. On 10,000 visitors, that's $12,500 before and $81,000 after. See the full case study numbers. Real client numbers, not typical results, and not a promise of what your store will do.
Your flows decide who comes back. Your product page decides what they're worth when they get there.
There's more on writing a page for people who arrive from your inbox in how to write a Shopify product page for email traffic, and more brand stories in our ecommerce case studies roundup and the Shopify case studies post.
How do you copy the Klaviyo case study pattern on your own store?
Short version, in order:
- Check the core flows are live and firing (welcome, abandoned cart, abandoned checkout, browse).
- Split the abandoned cart flow: first-time prospects vs returning customers.
- Cut full-list blasts. Send to engaged segments.
- Audit settings like Smart Sending that can silently block an email.
- Fix the product page those flows click through to.
Then measure each flow on revenue per recipient and compare it with the Klaviyo benchmarks for your peer group. The full build order for every flow is in our Klaviyo flows for Shopify guide.
What to do next
Pull up your abandoned cart flow today. Look at which email gets the most opens. If it isn't email one, something is blocking it, and Dagne Dover just showed you what that's costing.
Book Your Profit Audit
Your Klaviyo flows can only bring buyers back to the page you already have, and if that page can't close, every flow underperforms. Book a profit audit and we'll show you exactly where your page is leaking, then show you how to rebuild a high-converting product sales page in less than 15 minutes.
Or go here to check it out → revenueflows.ai
P.S. The case studies prove flows can bring buyers back. Whether they buy when they get there is up to the page.
Frequently asked questions
What results do Klaviyo case studies report?
Published Klaviyo case studies report results like Club L getting 33% of revenue from Klaviyo with two flows producing two thirds of it, Saranoni earning 36% of its Klaviyo revenue from flows in its first six months, and Hint Water's flow revenue jumping 133% in its first three months. Each number comes from the brand's own case study page on klaviyo.com.
Which Klaviyo flows drive the most revenue in case studies?
The welcome series and the abandoned cart or abandoned checkout flow show up in almost every Klaviyo case study as the money makers. Club L credits those two flows with two thirds of its Klaviyo revenue, and Maison Miru reports its abandoned checkout flow alone added 3% to annual revenue.
Are Klaviyo success stories realistic for a small Shopify store?
The tactics are realistic, the headline numbers are not a forecast. Most featured brands have big lists, like Dagne Dover's 1.2 million active profiles. Copy the moves (a segmented welcome flow, a split abandoned cart flow, fewer full-list blasts) and measure against your own baseline, not theirs.
How many flows do successful Klaviyo brands run?
Featured brands run a lot of them: Minnow has 22 live flows, Saranoni went from 2 to 20+, and Dagne Dover manages 30+. But the case studies credit most of the money to a handful of core flows, so start with welcome, abandoned cart and browse abandonment before you build flow number ten.
Can AI help improve Klaviyo flows?
Yes, and there's a published example. Dagne Dover's case study says an audit run through Klaviyo's MCP server with Claude found a Smart Sending setting blocking the first abandoned cart email, and the fix produced a 44% week-over-week revenue lift in that flow.