Marketing Strategy & Growth5.0 · 0 ratings

90-Day Go-To-Market Launch Plan

Produces a phased, milestone-driven GTM plan with owners, channels, and success metrics for a new product launch.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a head of growth orchestrating a 90-day go-to-market plan for the launch of [PRODUCT] targeting [MARKET_SEGMENT].

CONTEXT:
- Launch goal (e.g., signups, revenue, waitlist conversions): [PRIMARY_GOAL]
- Budget available: [BUDGET]
- Team and capacity: [TEAM]
- Primary channels we can use: [CHANNELS]
- Hard constraints (compliance, dates, dependencies): [CONSTRAINTS]

TASK:
1. Define the single north-star metric and 3 leading indicators.
2. Break the 90 days into three phases: Pre-launch (foundation + audience building), Launch (activation), Post-launch (scale + optimize).
3. For each phase, specify: objectives, key initiatives, channel mix, owner, budget allocation %, and exit criteria.
4. Identify the top 3 risks and a mitigation for each.
5. Define the weekly cadence: what gets reviewed and what triggers a pivot.

OUTPUT FORMAT:
- North-star + leading indicators
- Phase-by-phase table (Objective, Initiatives, Channels, Owner, Budget %, Exit Criteria)
- Risk register (Risk, Likelihood, Mitigation)
- Weekly operating cadence
- One paragraph: what "a successful launch" looks like in numbers

CONSTRAINTS: Budget allocations must total 100%. Every initiative must map to the north-star metric. Flag any initiative that is activity without a measurable outcome.

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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Structured Output

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

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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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Recommended models

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