How Our AI Email Sequence Builder Works

We built an AI agent that creates complete email sequences for DTC brands. Welcome sequences, post-purchase flows, win-back campaigns, referral asks. Full sequences with subject lines, preview text, body copy, and send timing. In hours, not weeks.

Four inputs

The email sequence agent needs four things:

1. Brand guidelines. Voice, tone, key messaging pillars. How formal or casual. Words to use and avoid. This ensures every email sounds like the brand, not like generic AI copy.

2. Product catalogue. Product names, descriptions, categories, prices, and relationships between products (what cross-sells with what). The agent uses this for personalised cross-sell and replenishment timing.

3. Customer reviews. Same reason we use reviews in ad creative. Reviews contain the specific language, benefits, and emotional responses that make email copy feel real. A review quote in a post-purchase email performs better than a marketing-written benefit statement.

4. Email platform. Klaviyo, Mailchimp, Omnisend, or whatever the brand uses. The agent outputs in the format the platform needs. The goal is direct import, not manual recreation.

What the agent builds

For a standard DTC post-purchase sequence, the agent produces:

12-15 emails with:

• Subject line (plus 2 A/B test variants)
• Preview text
• Full body copy (formatted for email, not blog-length)
• Send timing (relative to trigger event)
• Segmentation rules (who gets this email, who skips it)
• Dynamic content blocks (product-specific recommendations)

Flow logic:

• Trigger conditions (first purchase, repeat purchase, abandoned cart)
• Branch points (opened vs. didn't open, clicked vs. didn't click)
• Skip conditions (don't send cross-sell if they already bought that product)
• Wait periods calibrated to product category and purchase cycle

The review-grounded approach

The agent doesn't write generic email copy. It builds from customer reviews.

For the product care email: pulls specific questions and concerns from reviews to address proactively.

For the cross-sell email: uses language from reviews where customers mention using products together.

For the review request email: references specific benefits other customers mentioned, priming the recipient to think about their own experience in concrete terms.

This grounding in real customer language is the difference between emails that feel templated and emails that feel like they were written by someone who understands the product.

Output and iteration

The agent exports the complete flow in two formats:

1. Platform-ready import file. For Klaviyo, this is a JSON flow definition. Upload and activate.
2. Documented sequence map. A readable document showing the full sequence: timing, logic, email content, and the reasoning behind each decision.

After the first 30 days of data, we feed open rates, click rates, and conversion data back into the agent to optimise subject lines and send timing for the next iteration.

See the full 12-email sequence we built and the before/after results.