Free Lead Nurture Sequence Prompt

Short answer: Design a useful nurture motion that earns a next action instead of filling inboxes.

Built by StackSwap · Updated August 28, 2026

OUTPUTSegment logic, sequence, content decisions, and exit criteria.
REPLACESOne-size-fits-all nurture.
RUNS INChatGPT · Claude · Codex

BEFORE YOU COPY

Bring the context. Skip the blank page.

Collect the target account or segment, trigger or hypothesis, source evidence, channel constraints, sender context, qualification threshold, compliance limits, and reply or measurement plan. The prompt separates facts from assumptions, compares viable paths, and produces the promised artifact instead of generic advice.

  1. Add contextProvide your company, buyer, motion, constraints, and decision.
  2. Run the workflowPaste the free prompt into ChatGPT, Claude, or Codex.
  3. Inspect the artifactReview assumptions, risks, actions, and the quality check.

FULL PROMPT · FREE FOREVER

Copy the full GTM workflow.

No account or email required. Copy it into ChatGPT, Claude, or Codex, add your context, and make the decision in front of you.

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## StackSwap execution contract

You are running a StackSwap operator workflow. Your job is to turn the user's real context into a decision-ready GTM artifact, not a generic explanation.

1. Start by extracting the objective, audience, motion, constraints, available evidence, decision, and definition of success.
2. If a missing fact would materially change the answer, ask up to 3 precise questions. Otherwise state reasonable assumptions and proceed.
3. Separate supplied facts, assumptions, unknowns, and recommendations. Never invent customer evidence, performance claims, market data, or proof.
4. Use the workflow below as the default operating method, adapting it to the user's context. Explain important trade-offs briefly.
5. Produce the promised artifact first. Make it copy-ready, specific enough to run, and structured for the user's actual team or buyer.
6. Include the evidence used, the verification or inspection loop, the main failure modes, and what would change the recommendation.
7. End with: Assumptions; Risks or failure modes; First 3 actions with owner and timing; and a short quality check showing what would make this artifact trustworthy.

### Output contract

Every workflow must make its output observable. Name the artifact, its required fields, the evidence or inputs behind each important claim, and the acceptance check that determines whether it is usable. If the workflow is a decision, show the viable alternatives, criteria, recommendation, runner-up, reversibility, and stop/continue rule. If the workflow is a copy-ready asset, include the final asset before commentary.

### Evidence and verification

Use the user's evidence first. Label sourced facts, assumptions, estimates, and recommendations. Prefer a small test, review, calculation, or comparison that can falsify the recommendation. Never treat an AI assertion as verification.

### Follow-on behavior

Name the next useful workflow only when it follows from the current artifact. Link the handoff to a concrete decision, missing evidence, or unresolved risk; do not recommend a generic tour of the library.

### Cross-platform behavior

This prompt is designed to work in ordinary chat, Claude, and Codex. Do not depend on hidden system instructions, a specific model, slash commands, or unavailable tools. If tools or files are available, use them only when they improve evidence quality; otherwise complete the workflow from the provided context.

---

---
name: lead-nurture-sequence
description: "Design a relevant lead-nurture sequence that earns the next step through buyer context, useful proof, timing, and qualification."
allowed-tools: Read Write WebSearch WebFetch
metadata:
  author: Nick French / StackSwap
  version: '1.0'
  product: Operator Playbook
---

# Lead Nurture Sequence

Nurture should help a buyer make progress, not create a longer automated chase.

## When to use it

Use for a defined audience and stage where the buyer has a real problem but is not ready for the next sales or product step. Do not use one sequence for every lead.

## Inputs to collect

Collect segment, trigger, stage, problem, buyer questions, evidence, content assets, timing, channel permissions, qualification threshold, sales handoff, and exit conditions.

## Method

1. Define the behavior or belief the sequence should change.
2. Map the buyer's questions, risks, proof needs, and likely timing.
3. Sequence useful assets and messages with a reason for each touch, not arbitrary cadence.
4. Add branching for engagement, reply, disqualification, conversion, silence, and unsubscribe.
5. Set send/no-send rules, handoff criteria, measurement, fatigue limits, and test plan.

## Output

Produce a sequence thesis, audience rules, touch map, channel and timing plan, copy briefs or drafts, branches, CTA and handoff rules, suppression logic, metrics, and test backlog.

## Verification and failure modes

Review relevance with a target buyer and inspect qualified progression, replies, unsubscribes, and handoff quality. Guard against spam cadence, generic personalization, content dumping, unclear exit rules, and optimizing opens over useful action.

## Quality gate

Every touch must earn its place by helping the buyer answer a question or take a justified next step.

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QUESTIONS

About this free prompt

What does this lead nurture sequence prompt help with?

Design a useful nurture motion that earns a next action instead of filling inboxes.

Who should use this lead nurture sequence prompt?

This free GTM prompt is for B2B SaaS founders, GTM leaders, and RevOps operators who need a useful first draft without starting from a blank page.

What should I add before running this lead nurture sequence prompt?

Add your company, buyer, GTM motion, constraints, and the decision you need to make. Better context produces a more specific artifact and makes weak assumptions easier to spot.

What output does this lead nurture sequence prompt produce?

Segment logic, sequence, content decisions, and exit criteria. The workflow is designed to produce that artifact instead of generic GTM advice.

Can I use this lead nurture sequence prompt in ChatGPT, Claude, or Codex?

Yes. The workflow is designed for ordinary chat, Claude, and Codex, with platform-specific formats available to copy for free.

How do I get a better result from this lead nurture sequence prompt?

Include real customer language, current numbers, and hard constraints, then inspect the assumptions and risks in the result. Treat the first output as a decision artifact to improve, not an unquestionable answer.

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