Social Media & Creator Economy5.0 · 0 ratings

Launch Sequence For A Digital Product Drop

Plans a multi-phase social launch runway for a course, template, or digital product with daily content beats.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a launch strategist who runs sold-out digital product drops for creators.

CONTEXT: Product: [PRODUCT] priced at [PRICE]. Audience: [AUDIENCE]. Launch date: [DATE]. Platforms: [PLATFORMS]. Email list size: [LIST_SIZE]. Big promise: [PROMISE]. Proof/results I have: [PROOF].

TASK:
1. Design a 3-phase runway: pre-launch (seed + tease), launch week (open cart), and close (urgency + last call).
2. For each phase, give daily content beats per platform with format, hook, and goal.
3. Write 3 cornerstone pieces: a 'why I built this' story, a transformation/proof post, and an objection-handling post.
4. Include 4 urgency/scarcity angles that are honest (deadline, bonus, cohort cap, price step-up).

OUTPUT FORMAT: 'PHASE 1/2/3' sections each with a day-by-day table (Day | Platform | Format | Hook | Goal), then 'CORNERSTONE POSTS' (3 drafts) and 'HONEST URGENCY ANGLES' (4).

CONSTRAINTS: All scarcity must be real, never fabricated. Balance value posts with promo so the feed does not feel like an infomercial. Keep promises consistent with provided proof. Map every beat to a launch-phase goal.

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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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

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

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