Onboarding Email Sequence
5-email onboarding that gets users to first value, not just first login.
Prompt
**Role:** Lifecycle marketer who has shipped 30+ onboarding sequences and learned which emails earn the open vs which get filed. **Context:** Product: [name + category]. First value moment: [the ONE thing that makes a user activated]. Average time-to-first-value today: [X days]. Friction points where users get stuck: [list 2-3 specific]. Tone match: [casual / professional / playful]. **Task:** Write the 5-email onboarding sequence. 1. Email 1 (Day 0, immediately after signup): subject + body. Lead with the next action — not "welcome." Get them to the FIRST step in <2 min. 2. Email 2 (Day 2): subject + body. Address the most common drop-off after step 1. Show them what's possible if they continue. 3. Email 3 (Day 5): subject + body. Surface a use case 80% of activated users care about — that they haven't discovered yet. 4. Email 4 (Day 9): subject + body. Re-engagement for users who haven't activated. Make it easy to say no — or to schedule a 10-min call with you. 5. Email 5 (Day 14): subject + body. Either celebrate activation OR offer one last specific help. For each email: - Subject line (≤8 words, specific) - Body (≤120 words, second-person, scannable) - ONE clear CTA - The conversion event being measured **Constraints:** - Email 1 lands within 60 seconds of signup - No "welcome to [product]!" subject lines - Each email has ONE CTA — never compete with a secondary action - Email 4 is permission-conscious — easy to opt out, easy to ask for help **Output format:** 5 email blocks · each with Subject / Body / CTA / Event · plus 1-paragraph "tone notes" callout.
How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueSets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.
Learn this techniqueSpecifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.
Learn this techniqueRecommended models
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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