Why Most AI-Generated Email Copy Misses the Mark
Most brand owners open ChatGPT, type in a vague instruction like "write me an abandoned checkout email", and wonder why the output sounds robotic and utterly useless. It misses the brand voice, hallucinates fake offers, and ignores the exact email marketing mechanics that actually generate revenue.
Using a structured prompting framework has saved me hundreds of hours and thousands of dollars on copywriting across our agency accounts. The goal here is not to completely replace human copywriters. The goal is to generate an exceptionally strong version one in roughly two minutes, giving you or your writer a solid base to edit and polish instead of staring at a blank screen.
Phase 1: Priming ChatGPT on Your Store
You cannot ask AI to script specific flow emails until it deeply understands your catalogue, tone, and audience. I run a four-step priming sequence in a fresh chat before asking for a single line of email copy.
- Step 1: Set the context. Tell ChatGPT the exact company URL and establish the purpose of the workspace.
- Step 2: Define tone and audience. Ask the model to analyse the website to identify the brand voice, core product lines, and primary target audience.
- Step 3: Extract site specifics. Direct ChatGPT to crawl top-selling collections, customer reviews, blog content, and current promotional angles.
- Step 4: The accuracy stop-gap. Ask the model directly if the gathered information is accurate and up to date before proceeding.
That final stop-gap prompt is critical. AI models occasionally pull outdated links or sub-brand pages on larger websites, and forcing a quick verification step keeps the upcoming copy grounded in reality.
Formatting Rules for Klaviyo Dynamic Codes
Once the model understands your brand, you need to establish strict formatting constraints. If you do not specify your email service provider, ChatGPT defaults to generic merge tags that break when imported.
I explicitly instruct the model to output emails with four defined components: subject line, preview text, header image text suggestions, and structured body copy. Crucially, I tell it to format any dynamic personalisation using Klaviyo-specific syntax rather than generic tags.
Always ask the model to confirm it understands these formatting rules before feeding it specific email briefs. Skipping this step is a mistake.
Scripting the Welcome Series Flow
With the workspace primed, you can move systematically through each message in your automated sequence. For the first email in a welcome series, we want to deliver the sign-up incentive immediately, establish the brand mission, and highlight hero collections.
In the prompt, I feed the specific offer (such as WELCOME10 for 10% off their first order) and direct the model to weave in the unique value propositions it extracted during the priming phase. The output delivers clean, scannable copy broken into logical content blocks that your designer can drop directly into a Figma file or Klaviyo template.
If you prefer a different angle for message two (such as founder storytelling rather than product features), you simply alter the primary focus in the prompt template while keeping the underlying formatting structure intact.
Covering the Remaining Core Automations
We use this exact prompt architecture across all six fundamental ecommerce flows. Once the base chat is trained, you can script out the entire automated backend in a single afternoon.
- Browse Abandonment: Focus on low-friction product reminders, social proof, and value proposition highlights.
- Abandoned Checkout: Address common checkout friction points, handle shipping questions, and deliver clear direct CTAs.
- Post-Purchase Thank You: Reassure the buyer, set shipping expectations, and introduce the brand community.
- Order Fulfilled: Provide usage tips, care guides, and cross-sell related collections only where relevant.
- Customer Winback: Acknowledge lapsed time, showcase new product arrivals, and deploy tiered retention incentives.
Every prompt maintains the same voice parameters while adapting the primary objective and secondary call to action to match where the customer sits in their lifecycle.
Final Thoughts
AI will not build a high-performing email marketing channel on its own. However, giving an LLM structured constraints, brand-specific context, and Klaviyo-ready formatting turns a tedious multi-week copywriting slog into a streamlined editing process that saves serious time and capital.
Let Us Build Your Automated Flows
If you want a complete, high-converting automation engine built and optimised directly inside your account, explore our email automation services to see how our team handles the entire strategy, copy, and technical build.
