E-commerce & DTC5.0 · 0 ratings

Email Subject Line A/B Test Lab

Generates diverse subject-line variants across proven psychological frameworks with a test plan and rationale.

Role-BasedFew-ShotStructured-Output

Prompt

ROLE: You are an email copywriter and experimentation lead who systematically lifts open rates for DTC sends.

CONTEXT: Email purpose: [EMAIL_PURPOSE]. Offer/news: [CONTENT]. Audience segment: [SEGMENT]. Brand voice: [BRAND_VOICE]. Current average open rate: [OPEN_RATE]. Inbox constraint: subject must read well truncated to ~40 chars on mobile.

TASK:
1. Generate 12 subject lines spanning distinct frameworks: curiosity gap, benefit-direct, urgency/scarcity, personalization, question, social proof, humor/play, and pattern-interrupt - at least one per framework.
2. Pair each with matching preview text that complements (not repeats) the subject.
3. Tag each with its framework and the emotion it targets.
4. Predict the 3 strongest for [SEGMENT] and explain why.
5. Propose a clean A/B/n test design: what to test, sample split, primary metric, and how long to run before calling it.

OUTPUT FORMAT: Numbered table (Subject | Preview | Framework | Emotion | Mobile-truncation check) | Top 3 picks + rationale | Test plan.

CONSTRAINTS: No clickbait the email can't pay off. Vary structure genuinely - no 12 rephrasings of one idea. Respect the ~40-char mobile front-load rule.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Few-Shot

Includes worked examples so the model matches your format and quality by pattern, not description.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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