Let's start with the simplest question: what even is AI Email Marketing for DTC, really?

AI email marketing for DTC (direct-to-consumer) brands refers to the use of artificial intelligence to automate and enhance every part of the email marketing workflow. From analyzing customer data and creating predictive segments, to writing on-brand copy, designing emails, and sending them at optimal times. AI enables ecommerce teams to spend less time on execution and more time on strategy. In 2025, top-performing DTC brands use AI to drive better results, faster workflows, and significantly higher ROI.

In this comprehensive guide, you'll understand the current state of AI email marketing for ecommerce brands, what tools are available, how to get to a fully automated AI email marketing workflow, and where ESPs help (or hurt) today.

Table of Contents

1. The 2025 AI Email Marketing Landscape

2. Five Core AI Capabilities for DTC Brands

3. How to Fully Automate Email Marketing with AI in 2025

4. Which ESPs Offer the Best AI Email Marketing Features?

5. Frequently Asked Questions

6. Citations

1. The 2025 AI Email Marketing Landscape

Here's the real headline:

In 2025, email marketing is about evolving your team from executors to strategic orchestrators.

You apply your taste and expertise while AI handles the majority of what used to be the email grind.

I've talked to hundreds of brands and marketers on this topic, and I can tell you that 2025 feels like a completely different sport, and 2026 is shaping up to the same. Three years ago the time allocation for email marketing looked like the following:

Strategy/planning, teams spent 30% of their time on data analysis and segmentation, 30% on copywriting, and 30% of their time on design, and 10% on building & sending.

All that time usually accounted for 15 hours a week or more. Now, not only is less time being spent per week, but it's 80% on the strategy and design side, and robots handle all the rest.

The 3 Big Changes in eCommerce Email Marketing with AI

Let's take a quick glimpse into what big changes happened in 2025 that began to unlock more AI email marketing capabilities for DTC brands.

The Democratization of Data Science

Tools like ChatGPT and Claude have made advanced customer analysis accessible without feeling like you have to have a data science background. For instance, everyone knows they need to do Recency, Frequency, and Monetary (RFM) analysis. Both to understand their customers better and for some basic segmentation. But very few people did it because it felt like you needed a PhD in statistics to figure anything out and it still took hours.

“AI enables marketers to make data-driven decisions faster, resulting in more effective campaign planning and messaging.” — Einat Weiss, CMO of NICE [1]

With ChatGPT, can use AI do basic RFM analysis for your ecommerce store in 5 minutes [2]. More than that, the entire process of traditional RFM is being completely automated by AI. For instance, at Raleon, we have 30 different machine learning models that automatically analyze a brands data to produce daily updated segments that are focused not on engagement, but behavioral intent. The kind of intent that drives sales not just opens.

eCommerce Brands and agencies have seen staggering numbers using Raleon's predictive segmentation: 40x ROI in the first month from a 13% - 53% incremental revenue. [3]

AI Agents (Teammates) for Email Marketing in eCommerce

Here's what's frustrating about 2025: while ESPs have rolled out features like smart send times, predicted LTV, and "channel affinity," they're all pretty rudimentary and generally underperform custom AI solutions. These features are built from a 2015 mindset that makes the human do the work. You still have to create a segment targeting next send date, manage that whole list, and babysit the automations.

THE AI EMAIL MARKETING AGENT APPROACH

• AI "teammate" manages everything automatically

• Auto-tuned and predicted for your specific brand

• AI handles: analysis, customer identification, segmentation, content creation, design, send timing, results optimization

• Humans focus on strategy: product promotion, brand messaging, customer experience

The RFM analysis example from earlier falls into this category as well. Yes, you could spend the time to drop all that data into ChatGPT and tee it up. Or you could use platforms like Raleon that will perform an even more detailed analysis faster because they already have all the data, in real-time, and your full brand context.

This is all real, and here today. According to Klaviyo's 2025 State of Email report, brands using AI-driven segments saw revenue per recipient increases of 18-45% compared to traditional demographic segmentation [4].

Our own analysis of efficient and fast growing DTC brands showed brands using Raleon's campaign planning and segmentation see a 40% decrease in the amount of time it took to send more emails each month.

The biggest win here isn't just coming from AI itself, but from freeing up human creativity and time to focus on what moves the needle. Your team isn't buried in the tactical anymore.

On-Brand AI Copywriting Is Good Now

We're going to start this one simple - AI copywriting for DTC emails works. I can tell you this because one of the many ways brands use Raleon every day is to write their email copy for them (and suggest how to lay out the email).

That said, the most common first objection we hear is that AI copywriting is terrible. Inevitably you have tried it, and the results were poor if not laughable. Or maybe you spent a good 3 hours setting up the project, and the results were OK, but not great.

I'll give you the hard truth - it absolutely works, you've just been doing it wrong. Mind you, it's not easy, but it is 100% possible because we see it every day. The reason this is important is because this is actually a huge timesaver.

Honorable Mention: Image Generation

Image generation really hit this year. We aren't going to spend a ton of time on this, but it is worth mentioning.

Here's the real truth about image generation for DTC use cases: As of July, while we're seeing some usage of AI image generation (mostly ChatGPT 4o), it's mostly some product imagery for PDPs, static ads, and some uses in email. As a whole, image generation is not fully there yet.

2. Four Core AI Email Marketing Capabilities for DTC Brands

Let's break down the specific AI capabilities that are driving results right now for e-commerce brands in 2025:

#1 Automated Campaign Strategy and Planning

Automated campaign calendars and strategy planning is when AI analyzes your entire business like inventory levels, seasonal trends, competitive landscape, past performance and then suggests complete campaign strategies. Previously not possible before reasoning models, this is where platforms like Raleon have leaned in and really help brands ave time.

What it delivers: Complete campaign calendars that factor in your product inventory, seasonal trends, past performance, and competitive landscape. The AI acts like a data analyst and strategist rolled into one.

Revenue impact: 50% less time taken on data analysis, calendar planning and segmentation suggestions.

#2 AI Segmentation (AKA Predictive Segmentation)

Predictive, AI segmentation uses AI to group customers based on their likelihood to take specific actions, such as making a purchase or churning. Instead of targeting based on past behavior, it focuses on future intent using behavioral data and machine learning. These AI segments different from most brands and agencies who group customers based on engagement or basic past behavioral rules like number of purchases.

We're not talking Klaviyo or Yotpo's "AI Segmentation" where you tell it what you want, like "customers that made more than 4 purchases in the last 6 months and who have spent more than $200 with us and bought X product" and it builds all the static rules for you. That's just 2015 segmentation with a different UI slapped on top. This video gives a great rundown as to why:

The real breakthrough here is leveraging the behavioral signals hidden in your data that lets you target customers not based on engagement but on whether they're actually likely to make a purchase. [5]

What it delivers: Instead of "customers who bought in the last 30 days," you get "customers with 78% probability to purchase in the next 14 days" or "customers at high risk of churning within 60 days who are most likely to buy if you offer them your Nike Jordan 1 product."

Revenue impact: A home decor brand using Raleon's predictive segments saw a 957% increase in revenue per recipient while sending to 92% less customers. While not predictive, Klaviyo reported that more targeted segments see a 2x increase in revenue per recipient (and we're seeing even better results with AI segmentation).

#3 AI Copywriting

AI can now write email copy that maintains your brand voice while adapting to individual customer preferences and behaviors. What's more, within platforms like Raleon, it also continuously learns your brand voice and what's working.

What it delivers: Email content, subject lines, preview lines that all adapt and shift as needed based on your adjustments. The AI learns from your existing email performance and customer responses to generate variations that resonate with different segments. We're talking getting the copy for 10 emails in 60 seconds.

Revenue impact: Massive time savings and writers block prevention. Not to mention better conversion rates as the copy is tuned for driving conversion based on past performance.

#4 Email Design & Generation

Here's where things get even more interesting… and where most brands still struggle. AI can now generate complete email layouts, choose appropriate images, and even create HTML that renders properly across email clients. While you can use AI to generate images for your email from scratch, we still see best results starting with a designer. Then those designs used as reference images.

What it delivers: Complete emails that include layout selection, image placement, and responsive design. The AI can adapt email structure based on content type (promotional vs. editorial) and audience preferences.

The Reality Check: For emails that aren't very highly designed, email generation can work. But for emails that are highly designed, it's going to fall over and be frustrating. The winning approach in 2025 is AI for structure and efficiency, humans for visual polish and brand consistency.

3. How to Fully Automate Email Marketing with AI in 2025

Before we dive into the tactical stuff, let me share what we've learned from implementing this across dozens of brands: while this is a transformation to how you execute email marketing the process itself changes very little. In other words, you don't need to blow everything up and start over.

"AI Email Marketing today is about figuring out the best way to layer AI into each step of your current email workflow." - Nathan Snell, CEO of Raleon

That's exactly what we're going to walk you through in this section. It's important to note here that the most efficiency comes from being able to work through all this in a single platform as opposed to trying to do all these things as one-off. There is still some efficiency using a point solution for each stage, over the course of the process overall you lose a lot of efficiency.

Stage 1: Data Intelligence & Analysis

What used to happen: You'd manually through your Shopify, Klaviyo, and Google analytics data. Even manually reviewing past emails that performed well. We often found folks export their data manually, spend hours in Excel creating pivot tables, and try to spot patterns.

What happens now: AI ingests your customer data, email engagement metrics, and business context to automatically identify patterns, predict behaviors, and surface opportunities in seconds.

Key AI Tools:

• Raleon for pattern analysis and insight generation all with the context of your brand

• ChatGPT or Claude to take your manually exported data and perform an analysis for you (we have a guide for you on how to do this)

Human Role: Define business objectives, provide context the AI might miss, validate insights that seem too good to be true.

Stage 2: Strategic Campaign & Flow Planning

What used to happen: You'd brainstorm campaign ideas in meetings, manually check what worked last year, and hope your gut instincts were right. You would also try to determine which flows need new A/B tests or might be worth creating if you have time to get to it.

What happens now: AI analyzes your inventory, seasonal trends, competitor activity, and past performance to suggest campaign strategies with predicted ROI. Great AI will also suggest what segments to send these emails to as well. AI should also suggest flow improvements to make.

Key AI Tools:

• Raleon automatically analyzes all your past performance, your brand, and what you told it you wanted and prepares a full plan for you including suggested segments to target

• Create a custom prompt in ChatGPT that gives you a starting list of ideas (not researched or data backed, but just ideation)

Check out our DTC AI Benchmark report for when to use Claude vs. ChatGPT [6].

The Result: You should be sending more emails each month that are more targeted, which will increase revenue. As a result, you're spending less time executing and more time applying brand judgment, creative direction, and business priorities to AI suggestions. Decide which opportunities align with your brand story.

Stage 3: Audience Segmentation & Targeting

What used to happen: Create segments based on basic demographics or purchase history. Maybe run some RFM analysis if you were feeling fancy.

What happens now: AI creates predictive segments based on behavioral intent, engagement health, and likelihood to perform specific actions.

Key AI Tools:

• Raleon's AI Segments are automatically created and managed for you, targeting customers your normal engagement would have missed

• Klaviyo's AI Deliverability health will keep your deliverability levels healthy

• We've honestly found ChatGPT and Claude quite poor at creating or suggesting good segments

The Result: As AI manages segments for you and finds customers you would have missed, you will save time and see incremental revenue (on average we see a 13% increase in revenue from AI segmentation and a 90% reduction in time spent on segmentation based on Raleon data).

Stage 4: Review Campaign & Flow Plan

Not a whole lot has changed here. Usually the following items are reviewed by the director of lifecycle, CMO, or founder depending on the size of the brand:

• Campaign ideas

• Campaign timing

• Suggested segments for campaigns

• Any potential promotions

• Flow additions

• Flow A/B test updates

Stage 5: Email Copywriting & Layout

What used to happen: Write subject lines, craft email copy, and hope everything resonates with your audience.

What happens now: AI generates multiple copy variations, selects optimal layouts, and continuously optimizes based on performance data… for every campaign in your plan at once.

Key AI Tools:

• Raleon writes on brand copy for every campaign and flow in your plan in 60 seconds, including subject lines

• Raleon suggests email layout and matches the copy to it

• Create a custom Claude project to try and tune your brand voice over time

  • We've heard from ~100 brands it takes 3 hours to get to an "OK" result on average and is time consuming to keep updated

The reason for Claude over ChatGPT here is it's better at copywriting [6].

The Result: Save on not having to hire a copywriter and hours of time starting from scratch. Every adjustment you make should cause the AI to learn and improve automatically (in the case of Raleon) or should be manually fed back to it (in the case of Claude).

Stage 6: Review Email Brief & Copy

This tends to be an optional step depending on the size of the brand. It's pretty straight forward, the copy of each email is given a final review before being handed off to design. There's 3 aspects reviewed in this step:

• The brief, which includes the suggested email layout

• Instructions of what may need to be in each section and direction there (such as highlighting a product)

• The copy itself

The value in reviewing each of these before handing off to design is less time wasted during the design stage (expensive) making changes that could have been caught earlier.

Stage 7: Email Design

What used to happen: If you were really prepared your designer would use a component design language in figma to start as a foundation for each email. This would speed up design some, but still a very manual process.

What happens now: If you have very high quality designed emails with lots of "breaking of the box", your process will be largely the same right now. If your emails designs are not as magazine-esque high quality designed, AI can automate a good portion of your email design.

Key AI Tools:

• Raleon's Email Generation acts as a junior designer, takes the copy from Stage 4, and automatically creates your email with your assets (or generate new ones).

• Ripple can be used for more basic templates

• ChatGPT can be used for generating new images if you still want to do design more by hand

• Flux1 Kontext can be used to change text in images if you don't want to use an editor to do it

The Result: Depending on how highly designed your emails are, you can save as much as 90% of your time, or as little as 5%. Email design is one of the weaker areas of AI email marketing today and has the smallest efficiency gain right now.

Stage 8: Review Email Design

Generally your final stage before the email going out the door. The following details are usually reviewed here:

• Final pass on the copywriting

• Making sure promotions are correct (if applicable)

• Brand guidelines are met (color, font, size, logo use, etc)

• Brand design quality is met (image selection, style, tone, etc)

While you can actually use AI here to do a first pass on the email, we would not recommend starting there.

Stage 9: Build the Email & Preview

What used to happen: An ESP specialist would take the design, usually an image exported from figma or canva, and slice it up, then rebuild it in the ESP's email builder. They would make sure what can be text is text, put the right links in on the images, and make sure mobile responsive looks correct.

What happens now: AI builds it all for you. You still need to do previews to test links and all as before.

Key AI Tools:

• Raleon builds the campaign and email for you (if designed by AI or human-in-the-loop in Raleon)

• Email Love builds the email for you (if designed using their tool in Figma)

The Result: Usually 30 minutes to an hour of time savings. While tedious and annoying, this step does not generally take a ton of time.

Stage 10: Send Email & Monitor Performance

What used to happen: You schedule the email to send, them monitor performance. Performance monitoring is usually checking basic metrics (open rate, click rate, order rate, deliverability), maybe export some data to Excel for deeper analysis.

What happens now: You still check those metrics. But now AI continuously analyzes performance, identifies winning patterns, and automatically applies learnings to future campaigns.

Key AI Tools:

• Raleon automatically analyzes performance, does pattern recognition across campaigns, makes future strategy adjustments and updates predictive models

Klaviyo has some basic built in performance monitoring, but it's not automated with full context like what we're describing. Its deliverability monitoring is awesome.

The Result: Future campaigns and flows have built-in context and will be automatically optimized in the future.

AI Email Marketing Workflow Summary

Here's your TL;DR on this section of the ai email marketing workflow, and how much you should expect AI to take of the tedious workflow, vs. how much you as the managing human still need to be involved.

1. Data Intelligence & Analysis - 75% AI

2. Strategic Campaign & Flow Planning - 90% AI

3. Audience Segmentation & Targeting - 75% AI

4. Review Campaign & Flow Plan - All human today

5. Email Copywriting & Layout - 90% AI

6. Review Copywriting & Layout - All human today

7. Email Design - 5% - 50% AI depending on design fidelity

8. Review Email Design - All human today

9. Build Email & Preview - Could be 100% AI or all human, depending on the email

10. Send email & monitor performance - 75% AI

As you can see, while the process is almost identical to what email marketing workflows look like today, the who does the work in those workflows is changing. This is why 71 % of CMOs reported they intend to allocate over $10 million annually to AI—up from 57 % the prior year [7]

4. Which ESPs Offer the Best AI Email Marketing Features?

Let me be blunt about something most guides won't tell you: none of the major ESPs are really leading this AI transformation. They're all playing catch-up with bolt-on capabilities that don't hit the mark. Over the course of more than 100 conversations we had with 7-figure brands about what AI capabilities they were using from ESP's today, we discovered:

• Only 3% said they use AI capabilities like segmentation, predictions, or copywriting from their ESPs today

• 95% said they at least tried using ChatGPT in some way to help with their email marketing

The question, then, is which ESP is investing most in AI currently.

Klaviyo: The Best ESP, But Not AI-First

Klaviyo is the best of the traditional ESPs in general, and for AI features.

Their challenge is they're still built on the old paradigm of making humans do the work. You still have to create segments, manage lists, babysit automations, and do everything else in the workflow above by hand. They've added some AI sprinkles on top of a fundamentally manual system.

What they offer

• Predictive analytics

• Smart send times

• Smart attributes like "Next purchase date" and Predicted LTV

• Basic content optimization

• Deliverability monitoring (this is actually awesome)

What they're missing

• True predictive segmentation and segment management

• On-brand, good content generation and copywriting

• Strategic campaign planning

• Easier to use predictive models (looking at you "product feed" masquerading as product recommendations)

• Email generation

• Automated analysis

Omnisend: Solid Basics

What they offer

• Smart send times

What they're missing

• AI segmentation and segment management

• On-brand, good content generation and copywriting

• Strategic campaign planning

• Easier to use predictive models (looking at you "product feed" masquerading as product recommendations)

• Email generation

• Automated analysis of performance

• Automated learning

Mailchimp: Playing It Safe

What they offer

• Better AI segmentation than others, but still basic

What they're missing

Pretty much everything that makes AI email marketing exciting in 2025.

The New Players to Watch

While these are not ESP's, if you want to get to the dream state of fully automated ai email marketing in the DTC space, you're going to need to use some (if not all) of the tools below:

• Raleon: Covers everything in the marketing workflow above

• Email Love: Does a great job accelerating design creation in figma

• Ripple: Is similar to Klaviyo's content generation. It fills out email templates for you

• Revamp: Adds some great AI personalization to specific flows

The fundamental difference is architectural. Traditional ESPs are trying to bolt AI features onto systems designed for manual management. AI-first platforms are designed around the assumption that AI handles the execution while humans focus on strategy.

Conclusion: Teams are Moving from Execution to Orchestration

If you're reading this, you're already ahead of the 43% of marketers saying they don't know how to use AI well! [8]

What's critical to understand are three things:

1. Fully automated AI email marketing for your brand can happen right now, and is easier to get to than you think

2. Email generation and design is the biggest laggard in capability today

3. AI email marketing isn't just about better segments or copywriting - you can fundamentally change how your marketing team operates to be more efficient

Ready to get started? Try out the best AI email marketing workflow out there for Shopify brands right now with Raleon. Alternatively, you can check out the guides in our citations and try it all manually after a few weeks.

7. Frequently Asked Questions

Q: How much customer data do I need to get started with AI segmentation?

A: You need at least 2,000 customers with 6+ months of purchase data for meaningful results. Less than that and you're better off with traditional RFM segmentation. Don't let anyone tell you that 500 customers is enough, it's not. More than that, though, and you're leaving money on the table with traditional RFM segmentation.

Q: Can I use AI email marketing with any ESP?

A: If you're talking about external tools, it depends on what ESP they have integrations with. Most have some form of integration with Klaviyo and Omnisend. In an ESP directly, none of them can complete the AI Email Marketing Workflow on their own.

Q: Do I need coding skills to implement AI email marketing?

A: It depends. If you want to go more "free" or "on the cheap", then yes, you should expect to do a lot of prompt engineering and vibe coding. If you're wanting something faster and more out of the box, no.

Q: Does AI Email Copywriting Work?

A: Yes, it can absolutely be on-brand. It will either take a lot of prompt engineering and tuning, or using a more out of the box product.

Q: With AI Segments Do I Have To Personalize Every Email?

A: No, this is a common misconception with ecommerce brands. AI segmentation that is not engagement focused (like what we've described in this article) can be sent the exact email you are already sending and see incremental lift. Remember, what it's doing is identifying customers your engagement failed to. Now, can you send more personalized emails? For sure, and it will also drive more revenue.

Q: Can I Just Use ChatGPT For All My Email Marketing?

A: You can definitely use ChatGPT for parts we mentioned in the ai email marketing workflow. The challenge we often see with brands or agencies doing that is it ends up being a lot of extra manual effort, and the results are not as good because it lacks the business context.

Citations

[1] https://www.businessinsider.com/einat-weiss-nice-cmo-ai-marketing-2024-6

[2] How to Use AI to do Basic RFM Analysis

[3] Raleon's own case study data shows the 40x ROI and incremental revenue increase

[4] Klaviyo's State of the Brand 2025

[5] Ultimate Guide to Understanding AI Segmentation

[6] Raleon's DTC AI Benchmark

[7] https://www.businessinsider.com/marketing-leaders-ai-strategies-cmo-insider-breakfast-cannes-lions-2025-6

[8] https://digitalmarketinginstitute.com/blog/10-eye-opening-ai-marketing-stats-in-2025