Free GTM Motion Selection Prompt

Short answer: Choose sales-led, PLG, hybrid, channel, or community motion against actual economics.

Built by StackSwap · Updated August 28, 2026

OUTPUTMotion decision, sequencing, and downstream org implications.
REPLACESTrend-driven GTM strategy advice.
RUNS INChatGPT · Claude · Codex

BEFORE YOU COPY

Bring the context. Skip the blank page.

Collect the current offer, buyer language, alternatives including do-nothing, proof available, market frame, and the decision this message or strategy must change. 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.

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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: gtm-motion-selection
description: "Choose the right B2B SaaS go-to-market motion, sales-led, product-led (PLG), product-led sales hybrid, channel, or community, matched to ACV, product time-to-value, how the buyer buys, and the CAC-payback math, with hybrid/sequencing and the downstream org implications. MANDATORY TRIGGERS: 'GTM motion', 'PLG vs sales-led', 'sales-led vs product-led', 'which go-to-market motion', 'should we do PLG', 'choose a GTM motion', 'go-to-market strategy', 'self-serve vs sales'. STRONG TRIGGERS: 'product-led growth', 'do we need a sales team', 'inside vs field sales', 'channel strategy', 'should we be self-serve', 'motion for our ACV'. Do NOT trigger on: WHEN to hire the first rep within a sales motion (use founder-led-sales-to-first-rep), pricing tiers (use pricing-and-packaging), or sizing the market (use tam-sam-som-sizing). DO trigger when an operator is choosing the overarching GTM motion."
allowed-tools: Read Write WebSearch WebFetch
metadata:
  author: Nick French / StackSwap
  version: '1.0'
  product: Operator Playbook
  website: stackswap.ai/playbook
---

# GTM Motion Selection

Teams pick their go-to-market motion the way they pick a fashion: PLG because a unicorn blogged about it, or "real" sales because hiring AEs feels legitimate, without checking whether the motion fits their ACV, their product, or how their buyer actually buys. The wrong motion is fatal, and slowly: PLG bolted onto a $120K enterprise deal that needs six stakeholders and an implementation, or a field-sales team carrying a $30/month self-serve product whose CAC will never pencil. Both burn cash for quarters before anyone admits the motion, not the execution, was wrong.

> **The GTM motion isn't a fashion choice, it's a function of your ACV, your buyer, and your product's time-to-value. Pick the motion the math demands, not the one the latest blog post praised. The wrong motion is a slow, expensive death.**

This skill picks the motion the math supports, gated on ACV, product self-serve fit, buyer behavior, and CAC payback, and maps the hybrid reality and the downstream org implications, because the motion choice dictates your hiring, comp, pricing, and whole playbook.

---

## When to use this skill

Trigger on:

- "PLG vs sales-led, which motion?"
- "Should we be self-serve or sales-led?"
- "Choose our GTM motion"
- "Do we need a sales team?"

Don't run for:

- *When* to hire the first rep (use `founder-led-sales-to-first-rep`)
- Pricing tiers (use `pricing-and-packaging`)
- Sizing the market (use `tam-sam-som-sizing`)

---

## The framework

### 1. The motion options

- **Sales-led**, reps drive the deal (inside or field). For considered, higher-ACV purchases.
- **Product-led (PLG)**, the product drives acquisition + conversion; self-serve. For fast-time-to-value, lower-ACV products.
- **Product-led sales (hybrid)**, self-serve land + sales-assisted expansion/enterprise. The common modern shape.
- **Channel / partner**, third parties sell/resell. For ecosystems and reach you can't build.
- **Community-led**, a community drives awareness and adoption (often a layer, not a standalone motion).

### 2. The ACV gate (the dominant factor)

ACV sets the affordable motion, because the motion's cost has to fit the deal:

- **< $5K** → self-serve / PLG (a human can't profitably touch it)
- **$5-25K** → low-touch / inside sales / PLG-with-assist
- **$25-100K** → inside or field sales
- **$100K+** → field / enterprise sales

A motion that costs more to run than the ACV supports is a structural loss, not a fixable one.

### 3. Product fit (can it deliver value without a human?)

PLG requires the product to deliver value *self-serve and fast*, sign up, reach the activation moment, see ROI, without a human. If your product needs implementation, configuration, integration, or change management to deliver value, PLG will stall and you need sales-led (or at least sales-assisted). Time-to-value is the PLG litmus test.

### 4. Buyer fit (how does your ICP buy?)

- **Bottoms-up adoption** (an individual/team can start without procurement) → PLG works
- **Top-down committee purchase** (multiple stakeholders, security review, procurement) → sales-led
- Mismatching this is fatal: PLG into a committee buy strands you with no one to navigate procurement; sales-led into a self-serve buyer adds cost the buyer didn't want.

### 5. The CAC-payback math (does it pencil?)

The motion has to be economically viable: PLG's low ACV demands very efficient (often product/marketing-driven) acquisition; sales-led's high cost demands an ACV that pays it back inside ~12-18 months. Run the math (ties to `saas-metrics-and-unit-economics`), a motion that doesn't clear CAC payback is a motion you can't afford, however trendy.

### 6. Hybrid + sequencing

Few real motions are pure. Common hybrids: PLG land + sales-led expansion; a sales-led core with a self-serve trial as a top-of-funnel. And motions *evolve*, a PLG company moving up-market adds sales; an enterprise company moving down adds self-serve. Choose the motion for *now* and plan the evolution, don't dogmatically pick one pure motion forever.

### 7. The downstream implications

Choosing the motion is choosing the org. It dictates: who you hire (`gtm-hiring-scorecards`, `quota-and-capacity-planning`), how you comp them (`comp-plan-designer`), how you price (`pricing-and-packaging`, PLG needs a self-serve tier; sales-led needs room to negotiate), and the entire playbook. Don't pick a motion without acknowledging the org you're committing to build.

---

## The process when triggered

### Step 1: Establish ACV
The dominant gate (§2).

### Step 2: Assess product self-serve fit
Time-to-value without a human (§3).

### Step 3: Assess buyer behavior
Bottoms-up vs top-down (§4).

### Step 4: Run the CAC-payback check
Does the motion pencil (§5)?

### Step 5: Resolve to a motion (+ hybrid/sequence)
The motion for now; the evolution (§6).

### Step 6: Map the implications
Hiring, comp, pricing, playbook (§7).

---

## The artifact (template)

```markdown
# GTM Motion Decision, [Company], [Date]

## Inputs
- ACV: $___ | Product time-to-value (self-serve?): ___ | Buyer: bottoms-up / top-down

## Gates
- ACV gate → suggests: [motion]
- Product fit → PLG viable? Y/N (why)
- Buyer fit → [bottoms-up→PLG / top-down→sales-led]
- CAC payback → penciled? Y/N

## Decision
**Primary motion: [sales-led / PLG / hybrid / channel]**
- Rationale: [ACV + product + buyer + math]
- Hybrid/assist: ___
- Evolution: [how it changes up/down-market]

## Downstream implications
- Hiring: ___ | Comp: ___ | Pricing: ___ | Playbook: ___
```

---

## Common mistakes

- **Copying the trendy motion.** PLG because a unicorn did it isn't a reason. Match it to your math.
- **PLG on complex/high-ACV products.** If value needs a human to unlock, PLG stalls. Sales-led.
- **Sales-led on low-ACV self-serve.** The CAC never pencils. Self-serve it.
- **Ignoring time-to-value.** PLG dies if the product can't deliver value fast and alone.
- **Mismatching buyer behavior.** PLG into a committee buy, or sales into a bottoms-up buyer, both fail.
- **A motion that doesn't pencil.** If CAC payback doesn't clear, you can't afford the motion.
- **Pure-motion dogma.** Most real motions are hybrid and evolve. Plan the sequence.

---

## How to use the artifact downstream

1. **Grounded by the market**, `tam-sam-som-sizing` and `icp-builder` describe the buyer and size the motion serves.
2. **Gated by economics**, the CAC-payback check uses `saas-metrics-and-unit-economics`.
3. **Dictates the org**, the motion sets `gtm-hiring-scorecards`, `quota-and-capacity-planning`, `comp-plan-designer`, and `pricing-and-packaging`.
4. **Feeds the first-rep call**, a sales-led motion leads into `founder-led-sales-to-first-rep`.

---

**The GTM motion is the most expensive decision to get wrong, because it's structural, the wrong motion loses money for quarters before anyone admits it. Gate on ACV, demand real self-serve time-to-value before betting on PLG, match the motion to how your buyer actually buys, and prove it pencils on CAC payback. Teams pick the motion that's in fashion. Operators pick the motion the math demands, and build the org it requires.**

---

_Part of the StackSwap Operator Playbook. → stackswap.ai/playbook_

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QUESTIONS

About this free prompt

What does this gtm motion selection prompt help with?

Choose sales-led, PLG, hybrid, channel, or community motion against actual economics.

Who should use this gtm motion selection 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 gtm motion selection 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 gtm motion selection prompt produce?

Motion decision, sequencing, and downstream org implications. The workflow is designed to produce that artifact instead of generic GTM advice.

Can I use this gtm motion selection 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 gtm motion selection 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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