How do I install the Demand Plan skill?

Run npx skillmds@latest add vellum-ai/demand-plan in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Which AI agents work with Demand Plan?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Demand Plan free to use?

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Who published Demand Plan?

vellum-ai (@vellum-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Demand Plan by vellum-ai — Agent Skill

Name: Demand Plan
Author: vellum-ai

Demand Plan

Build a demand-generation plan worked backward from a pipeline or revenue target through funnel math to a channel and budget allocation. Use for "build our demand plan", "how do we hit our pipeline target", "plan Q_ marketing", or budget allocation.

vellum-ai f59bbd6 3 files · 10.4 KB Updated Sep 17, 2026

File contents

Build a credible demand plan that ties a revenue/pipeline target to the funnel volume and budget required to hit it. Work backward from the number; never start from a channel list.

Step graph

Step 1: Map the funnel, then anchor the target

First establish the user's funnel — don't assume a B2B sales funnel:

B2B sales-led: lead → MQL → SQL → won, valued by ACV.
Ecommerce: visit → add-to-cart → purchase (→ repeat), valued by AOV.
Consumer/subscription: install/signup → activate → subscribe, valued by ARPU/LTV.

Then set the goal: target new revenue (or orders/subscribers) for the period and its length. Get the conversion rate between each stage and the average value per customer/order — or state assumptions explicitly. Use the user's metric names for the rest of the plan.

Step 2: Back-solve the funnel

Call funnel_math with target_revenue, the stage conversion rates, and the per-customer/order value (map your top-of-funnel metric onto its mqls/leads field — the math is stage→stage regardless of labels). It returns the top-of-funnel volume required to hit the target. This is the spine of the plan.

Step 3: Sanity-check unit economics

Call funnel_math again with spend and new_customers (and LTV inputs if available) to compute CAC, LTV:CAC, and payback. If LTV:CAC < 3 or payback is too long for the business, flag that the plan needs efficiency work before more spend. (Payback tolerance varies — months are fine for high-margin software, much tighter for low-margin ecommerce.)

Step 4: Allocate to channels

Distribute the required top-of-funnel volume across channels by expected efficiency and the business's motion (e.g. paid search/social, SEO/content, marketplace/retail, lifecycle, partnerships, sales). For each channel: expected volume, cost, and a confidence level. Note lead-time (paid is fast, SEO/content is slow).

Step 5: Assemble the plan

Output:

Target → required funnel volume (from Step 2).
Channel allocation table: channel | volume (leads/sessions/signups) | budget | CAC | confidence.
Unit-economics check (Step 3) with flags.
Risks & assumptions, and the 2–3 bets that matter most.
What you would NOT fund and why.

Quantify everything. If a number is assumed, say so.

---name: demand-plandescription: Build a demand-generation plan worked backward from a pipeline or revenue target through funnel math to a channel and budget allocation. Use for "build our demand plan", "how do we hit our pipeline target", "plan Q_ marketing", or budget allocation.---Build a credible demand plan that ties a revenue/pipeline target to the funnel volume and budget required to hit it. Work backward from the number; never start from a channel list.## Step graph### Step 1: Map the funnel, then anchor the targetFirst establish **the user's funnel** — don't assume a B2B sales funnel:- B2B sales-led: lead → MQL → SQL → won, valued by ACV.- Ecommerce: visit → add-to-cart → purchase (→ repeat), valued by AOV.- Consumer/subscription: install/signup → activate → subscribe, valued by ARPU/LTV.Then set the goal: target new revenue (or orders/subscribers) for the period and its length. Get the conversion rate between each stage and the average value per customer/order — or state assumptions explicitly. Use the user's metric names for the rest of the plan.### Step 2: Back-solve the funnelCall **`funnel_math`** with `target_revenue`, the stage conversion rates, and the per-customer/order value (map your top-of-funnel metric onto its `mqls`/leads field — the math is stage→stage regardless of labels). It returns the top-of-funnel volume required to hit the target. This is the spine of the plan.### Step 3: Sanity-check unit economicsCall **`funnel_math`** again with spend and `new_customers` (and LTV inputs if available) to compute CAC, LTV:CAC, and payback. If LTV:CAC < 3 or payback is too long for the business, flag that the plan needs efficiency work before more spend. (Payback tolerance varies — months are fine for high-margin software, much tighter for low-margin ecommerce.)### Step 4: Allocate to channelsDistribute the required top-of-funnel volume across channels by expected efficiency and the business's motion (e.g. paid search/social, SEO/content, marketplace/retail, lifecycle, partnerships, sales). For each channel: expected volume, cost, and a confidence level. Note lead-time (paid is fast, SEO/content is slow).### Step 5: Assemble the planOutput:- Target → required funnel volume (from Step 2).- Channel allocation table: channel | volume (leads/sessions/signups) | budget | CAC | confidence.- Unit-economics check (Step 3) with flags.- Risks & assumptions, and the 2–3 bets that matter most.- What you would NOT fund and why.Quantify everything. If a number is assumed, say so.

Frequently asked questions