This skill provides a systematic workflow for designing and executing market entry, launch, and growth strategies. It helps users select appropriate go-to-market motions, define ideal customer profiles, and plan product launches. Developers should use it when automating market entry execution, channel selection, or aligning revenue operations for new or scaling products.
Startup Go-to-Market
Systematic workflow for designing and executing market entry, launch, and growth.
Modern Best Practices (Jan 2026): Start from ICP + positioning, pick 1-2 channels to sequence, instrument the funnel end-to-end, use AI for execution (not strategy), align RevOps across sales/marketing/CS.
When to Use
- Designing go-to-market strategy for new product
- Choosing between PLG and sales-led motion
- Planning product launches (soft, beta, ProductHunt, full)
- Defining ICP and channel strategy
- Implementing AI-powered GTM automation
When NOT to Use
Quick Start (Inputs)
Ask for the smallest set of inputs that makes decisions meaningful:
- Stage: pre-PMF, early PMF, growth, scale
- Product and category: what it is, who uses it, and what "first value" looks like
- ICP and buyer: firmographics, pains, procurement constraints, economic buyer vs champion
- Pricing and economics: current/target ACV/ARPA, COGS drivers (include variable compute), payback constraints
- Motion constraints: self-serve possible, sales cycle expectations, implementation/onboarding complexity
- Channel constraints: budget, time, audience access (communities, lists, partnerships), geo, compliance limits
- Baseline metrics: traffic, signup/demo rate, activation, retention, win rate, sales cycle length, pipeline
- Team and tooling: who executes (founder/marketing/sales/CS), CRM + analytics stack
If numbers are missing, proceed with ranges + explicit assumptions and list what to measure next.
Workflow
- Define ICP and the buying path
- Primary/secondary ICP, anti-ICP, trigger events, and an "activation" definition.
- Use
assets/icp-definition.md to draft.
- Align on positioning and proof
- Choose the motion (PLG / sales-led / hybrid)
- Use the decision tree below for a fast cut.
- For details:
references/plg-implementation.md and references/sales-motion-design.md.
- Pick 1-2 channels to sequence (not parallelize)
- Use a bullseye-style test plan: quick tests, measure, double down.
- For execution details:
references/channel-playbooks.md.
- Define measurement and RevOps alignment
- Define shared lifecycle stages and the "one source of truth" for metrics (product + CRM).
- Ensure handoffs are measurable (e.g., PQL -> SQL routing rules and SLAs for hybrid).
- Produce deliverables + operating cadence
- Draft GTM plan (
assets/gtm-strategy.md) and launch plan (assets/launch-playbook.md).
- Run a weekly GTM review: 30 minutes on pipeline + funnel, 30 minutes on experiments, 30 minutes on decisions.
Decision Tree
GTM QUESTION
|-- "How do I reach customers?" -> Channel Strategy
|-- "PLG or Sales-led?" -> Motion Selection
|-- "How do I launch?" -> Launch Planning
|-- "Who is my ICP?" -> Segmentation
`-- "How do I scale?" -> Growth Loops
GTM Motion Types
| Motion |
Description |
Best For |
Examples |
| PLG |
Product drives acquisition, conversion, expansion |
SMB, developers |
Slack, Figma |
| Hybrid (PLG + Sales-Assist) |
Product drives acquisition; sales assists conversion/expansion |
Mid-market, higher ACV PLG |
Atlassian, Notion |
| Sales-Led |
Reps drive deals through outbound/inbound |
Enterprise, complex sales |
Salesforce |
| Community-Led |
Community drives awareness and adoption |
Developer tools, OSS |
MongoDB |
| Partner-Led |
Partners drive distribution |
Enterprise, geographic expansion |
Microsoft |
Motion Selection Framework
ACV < $5K and self-serve possible?
- yes: PLG (add sales-assist for expansion)
- no: is buyer technical?
- yes: developer/community-led (bottom-up)
- no: sales-led
ICP Components
| Component |
Questions |
Example |
| Firmographics |
Size, industry, geography |
50-500 employees, B2B SaaS, US |
| Technographics |
Tech stack, tools |
Uses Salesforce, modern data stack |
| Pain indicators |
Symptoms of problem |
Growing support tickets |
| Success indicators |
Signs of good fit |
Strong product-market alignment |
ICP Scoring
| Factor |
Weight |
| Budget available |
20% |
| Problem severity |
25% |
| Technical fit |
15% |
| Decision timeline |
15% |
| Champion identified |
15% |
| Expansion potential |
10% |
Channel Strategy
| Category |
Channels |
Best For |
| Organic |
SEO, content, social, community |
Long-term |
| Paid |
SEM, paid social, display |
Fast, scalable |
| Outbound |
Email, cold calls, LinkedIn |
Enterprise, high ACV |
| Product |
Viral, freemium, PLG |
Self-serve |
Channel Sequencing by Stage
| Stage |
Primary Channels |
| Pre-PMF |
Founder sales, communities |
| Early |
Content, outbound, founder network |
| Growth |
Paid, SEO, partnerships |
| Scale |
All channels optimized |
Measurement (Minimum Viable GTM Analytics)
- Prefer lifecycle + cohorts over vanity metrics. Always break down by ICP/segment + channel.
- Define a single funnel per motion (PLG vs sales-led) with clear stage definitions and owners.
- Track leading indicators (activation/retention, PQL, win rate) before "scale" decisions.
PQL (Product Qualified Lead) Score:
PQL = (Engagement * 0.4) + (Fit * 0.3) + (Intent * 0.3)
Product-Led Sales (Sales-Assist) Basics
Use when PLG brings users in, but conversion/expansion benefits from a human touch.
PQL -> SQL routing checklist:
Launch Types
| Type |
Goal |
Timeline |
| Soft launch |
Test, iterate |
2-4 weeks |
| Beta launch |
Build waitlist, feedback |
4-8 weeks |
| ProductHunt |
Awareness, early adopters |
1 day + prep |
| Full launch |
Maximum awareness |
1-2 weeks |
Growth Loops
| Loop |
Mechanism |
Example |
| Viral |
User invites users |
Dropbox referrals |
| Content |
Content -> SEO -> Users |
HubSpot |
| UGC |
Users create content |
YouTube |
| Paid |
Revenue -> Ads -> Users |
Performance marketing |
| Sales |
Pipeline -> close -> revenue -> hiring -> more pipeline |
Sales-led SaaS |
| Partner |
Enable partners -> referrals -> deals -> partner revenue -> more partners |
Cloud marketplaces |
Do / Avoid
Do
- Define activation as concrete "first value moment"
- Track leading indicators (activation, PQL, retention)
- Use AI for execution while humans own strategy
- Tier ICP based on fit + intent signals
Avoid
- Content spam without measurement
- "Do all channels" in parallel
- Vanity metrics without retention context
- Over-automating without human oversight
- Scaling paid before activation/retention is stable
- Treating benchmarks as targets without segmenting by ICP/channel
Resources
Templates
Data
Related Skills
What Good Looks Like
- One primary ICP with clear anti-ICP and measurable triggers (signals) for targeting.
- A motion decision with explicit economics (ACV, payback, touch model) and defined handoffs.
- One primary channel with a test plan, success metrics, and stop/pivot triggers.
- Instrumented funnel from source -> activation/value -> revenue/expansion (by segment + channel).
- A weekly operating cadence with a backlog of experiments and a written decision log.