Reusable prompt
Create messaging that nudges users through activation, retention, and expansion.
Task type: Lifecycle Messaging
Objective: Create messaging that nudges users through activation, retention, and expansion.
Context:
- [Project, product, or topic]: [Project, product, or topic]
- [Audience and situation]: [Audience and situation]
- [Constraints, must-haves, and things to avoid]: [Constraints, must-haves, and things to avoid]
Inputs to provide:
[Paste source material here]
Expected output:
1. Journey stages
2. Touchpoints
3. Message variants
4. Metrics
5. Interventions
Quality bar:
- Be specific and avoid generic advice.
- State assumptions explicitly.
- Prefer actionable next steps over broad theory.
- If important information is missing, ask up to 3 clarifying questions before answering.
- For time-sensitive or factual claims, label what is known, inferred, and needs verification.Worked example
The example below fills the same prompt for a realistic Marketing scenario. It is intentionally modest: the goal is to show how the prompt behaves, not to pretend one template solves every Marketing problem.
Task type: Lifecycle Messaging
Objective: Create messaging that nudges users through activation, retention, and expansion.
Context:
- [Project, product, or topic]: A real Marketing task using the Lifecycle Messaging prompt
- [Audience and situation]: A teammate who needs a useful answer and clear next steps
- [Constraints, must-haves, and things to avoid]: Be specific, state assumptions, avoid unsupported claims, and keep the output easy to act on.
Inputs to provide:
Sample material: The team needs help with Lifecycle Messaging. The current situation is messy, the goal is clear enough to start, and the answer should separate facts, assumptions, risks, and next actions.
Expected output:
1. Journey stages
2. Touchpoints
3. Message variants
4. Metrics
5. Interventions
Quality bar:
- Be specific and avoid generic advice.
- State assumptions explicitly.
- Prefer actionable next steps over broad theory.
- If important information is missing, ask up to 3 clarifying questions before answering.
- For time-sensitive or factual claims, label what is known, inferred, and needs verification.How to use this prompt
- Replace the placeholders with the actual Lifecycle Messaging task, audience, source material, and constraints.
- Keep the requested output sections unless you have a strong reason to remove one; they are there to make the AI answer easier to evaluate.
- Paste the finished prompt into your AI assistant, then ask one follow-up question that tests assumptions or missing evidence.
What a good answer should contain
- 1. Journey stagesUse this section to make the answer concrete: Journey stages.
- 2. TouchpointsUse this section to make the answer concrete: Touchpoints.
- 3. Message variantsUse this section to make the answer concrete: Message variants.
- 4. MetricsUse this section to make the answer concrete: Metrics.
- 5. InterventionsUse this section to make the answer concrete: Interventions.
Why this prompt works
- Lifecycle Messaging starts with an explicit task type and objective, which reduces vague answers.
- It asks for context, source material, and constraints before the model writes the final response.
- The 5 output sections make the answer scannable and easier to compare across attempts.
- The quality bar tells the assistant to ask clarifying questions and mark claims that need verification.
Common mistakes to avoid
- Leaving placeholders untouched and expecting the model to infer the missing context.
- Removing the output structure, then asking for a final answer that is hard to review.
- Using the prompt for time-sensitive facts without checking sources or dates.