Plan a product launch
A launch plan with tiering, timeline, assets, channels, owners and launch-day runbook.
This is a practical, copy-paste process for a feature or product ships in the next 2–8 weeks.. Use it when you want a clear structure, then add your own details and the linked evidence.
Published by Deepstory Research. Reviewed Sep 2026.
How to use this method
- 1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
- 2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
- 3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.
The prompt
Paste it as-is. The AI will ask for anything still in [BRACKETS].
# Plan a product launch Method by Deepstory Research: deepstoryresearch.com/method/product-launch-plan You are a product-marketing manager. Follow the method below step by step. Goal: A launch plan with tiering, timeline, assets, channels, owners and launch-day runbook. ## My inputs - What is launching: [WHAT_IS_LAUNCHING] (example: new mobile app) - Launch date: [LAUNCH_DATE] (example: 15 Nov 2026) - Audience: [AUDIENCE] (example: existing users and new prospects) - Assets available: [ASSETS_AVAILABLE] (example: screenshots, demo video) Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source. ## Steps to follow 1. Choose launch tier (major, medium, minor) and justify. 2. Define goals and success metrics. 3. Build a T-minus timeline with owners. 4. List assets: announcement, email, social, landing page, sales enablement, PR. 5. Write a launch-day runbook and post-launch review plan. ## Deliver the output in this structure - Launch tier & goals - Timeline - Asset checklist - Channel plan - Launch-day runbook - Review plan ## Quality rules - Every task has an owner and a date. - Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION. - If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED]. - End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.
What you need to give the AI
| Input | Placeholder | Example |
|---|---|---|
| What is launching | [WHAT_IS_LAUNCHING] | new mobile app |
| Launch date | [LAUNCH_DATE] | 15 Nov 2026 |
| Audience | [AUDIENCE] | existing users and new prospects |
| Assets available | [ASSETS_AVAILABLE] | screenshots, demo video |
Use it when
- A feature or product ships in the next 2–8 weeks.
What you get
- Launch tier & goals
- Timeline
- Asset checklist
- Channel plan
- Launch-day runbook
- Review plan
The procedure, step by step
Read this before you run it, so you can check the AI actually followed the method.
Choose launch tier (major, medium, minor) and justify.
Define goals and success metrics.
Build a T-minus timeline with owners.
List assets: announcement, email, social, landing page, sales enablement, PR.
Write a launch-day runbook and post-launch review plan.
Quality checks built into the prompt
- • Every task has an owner and a date.
- • Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].
Evidence to use with this method
Methods tell the AI how to think. Evidence gives it sourced numbers to think with. Download a context file and attach it with the prompt.
E-Commerce Share of US Retail
Online sales as a share of total US retail, and the growth gap that keeps pushing that share up.
UPI vs Visa & Mastercard: India’s Payments Rewiring
Ten years of UPI measured against the US card networks, against cash, and against the merchant-discount-rate question reopened by the Taxation and Other Laws (Amendment) Bill, 2026.
Six-Economy Macro Baseline
A common-country, common-period baseline for real growth, inflation, modeled unemployment and trade exposure across the United States, China, India, Germany, the United Kingdom and Japan.
Run next
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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.