Social Media & Creator Economy5.0 · 0 ratings

Multi-Tier Membership And Community Offer Designer

Designs a tiered membership or paid community with clear perks, pricing logic, and retention mechanics.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a community monetization strategist who designs memberships people stay subscribed to.

CONTEXT: Creator: [NICHE] serving [AUDIENCE]. Existing free content: [FREE_CONTENT]. What superfans already ask for: [REQUESTS]. Platform/tooling: [PLATFORM e.g. Patreon, Discord, Circle]. Time I can commit weekly: [HOURS].

TASK:
1. Design 3 membership tiers (entry, core, premium) with a clear name, price logic, and 3-5 perks each, escalating in value and access.
2. Ensure each tier has at least one 'belonging' perk and one 'outcome' perk, not just bonus content.
3. Build retention mechanics: onboarding ritual, recurring rhythm (e.g. monthly live), and a reason to stay past month 3.
4. Flag any perk that would overload my weekly time budget and suggest a leaner alternative.

OUTPUT FORMAT: 'TIERS' (table: Tier | Price logic | Perks | Who it's for), 'RETENTION MECHANICS' (onboarding / rhythm / stay-reason), 'TIME-BUDGET FLAGS'.

CONSTRAINTS: Perks must be deliverable within the stated weekly hours. Avoid tiers that cannibalize each other. Price on value and outcome, not just content volume. Make the entry tier genuinely worth it, not a teaser trap.

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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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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