Marketing ops · Production

Klaviyo email and SMS automation case studies: Callie's Hot Little Biscuit, Every Man Jack, and Tatti Lashes

The problem

Each brand faced poorly-timed or generic automated outreach that failed to match customer purchase cadences. Every Man Jack's previous platform sent repurchase reminders after 45 days even though customers typically ran out of products after 75 days, and Callie's customers averaged only two purchases per year despite likely buying more with the right incentives.

First attempt

Every Man Jack's previous automation platform did not support timeline customization, resulting in repurchase flows sent at the wrong time relative to customers' actual product consumption cycle.

Workflow diagram · grounded in source
1
Customer behavior triggers automation
trigger
“each message is based on a specific action someone has taken like browsing one of your product sets, adding an item to a cart, abandoning the site, or making a purchase”
2
Predictive analytics determines send timing
ai_action
“Predicted next order date, for example, informs an automated repurchase flow that goes out when Every Man Jack customers are most likely to be low on a favorite product”
3
Pre-filled cart repurchase email sent
output
“The flow sends a link to a cart pre-filled with their favorite product(s)”
4
Loyalty milestone order trigger
trigger
“A customer's second order in a year triggers an alert that they'll get V.I.B. (Very Important Biscuiteer) status with their next order. A customer's third order triggers an alert that they'll get free shipping on their next order.”
5
LLM generates personalized email content
ai_action
“Large language models are generating personalized email content more quickly, so brands are editing for style and voice rather than writing copy from scratch”
6
AI creates audience segments
ai_action
“With AI, marketers can describe their desired segment and create it in seconds”
Reported outcome

Callie's Hot Little Biscuit grew flows revenue 157.8% YoY; Every Man Jack achieved a 25% YoY increase in flows revenue; Tatti Lashes acquired 40K SMS subscribers in 3 months, drives a 30% click rate and 9% conversion on their welcome SMS flow, and now generates 35% of owned marketing revenue from SMS.

Reported metrics
flows revenue growth YoY (Callie's Hot Little Biscuit)157.8%
flows revenue growth YoY (Every Man Jack)25%
SMS subscribers acquired in 3 months (Tatti Lashes)40K
SMS welcome flow click rate (Tatti Lashes)30%
Show all 7 reported metrics
flows revenue growth YoY (Callie's Hot Little Biscuit)157.8%
flows revenue growth YoY (Every Man Jack)25%
SMS subscribers acquired in 3 months (Tatti Lashes)40K
SMS welcome flow click rate (Tatti Lashes)30%
SMS welcome flow conversion rate (Tatti Lashes)9%
owned marketing revenue from SMS (Tatti Lashes)35%
Tatti Lashes SMS welcome flow incomesix figure income
Reported stack
Klaviyopredictive analytics
Source
https://www.klaviyo.com/blog/email-automation-case-studies
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Callie's Hot Little Biscuit grew flows revenue 157.8% YoY; Every Man Jack achieved a 25% YoY increase in flows revenue; Tatti Lashes acquired 40K SMS subscribers in 3 months, drives a 30% click rate and 9% conversion…

What tools did this team use?

Klaviyo, predictive analytics.

What results were reported?

flows revenue growth YoY (Callie's Hot Little Biscuit): 157.8%; flows revenue growth YoY (Every Man Jack): 25%; SMS subscribers acquired in 3 months (Tatti Lashes): 40K; SMS welcome flow click rate (Tatti Lashes): 30% (source-reported, not independently verified).

What failed first in this deployment?

Every Man Jack's previous automation platform did not support timeline customization, resulting in repurchase flows sent at the wrong time relative to customers' actual product consumption cycle.

How is this marketing ops AI workflow structured?

Customer behavior triggers automation → Predictive analytics determines send timing → Pre-filled cart repurchase email sent → Loyalty milestone order trigger → LLM generates personalized email content → AI creates audience segments.

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