sales-motion-design

tech-leads-club/agent-skills · updated May 23, 2026

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$npx skills add https://github.com/tech-leads-club/agent-skills --skill sales-motion-design
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summary

When the user wants to choose between PLG and sales-led, design a sales motion, optimize time-to-first-value, or build a value-before-purchase experience. Also use when the user mentions 'PLG,' 'product-led growth,' 'sales-led,' 'sales motion,' 'free trial,' 'freemium,' 'self-serve,' 'demo-first,' 'time-to-first-value,' 'TTFV,' or 'agent-led sales.' This skill covers sales motion selection, value delivery design, and go-to-market motion architecture. Do NOT use for technical implementation, code review, or software architecture.

skill.md
name
sales-motion-design
description
"When the user wants to choose between PLG and sales-led, design a sales motion, optimize time-to-first-value, or build a value-before-purchase experience. Also use when the user mentions 'PLG,' 'product-led growth,' 'sales-led,' 'sales motion,' 'free trial,' 'freemium,' 'self-serve,' 'demo-first,' 'time-to-first-value,' 'TTFV,' or 'agent-led sales.' This skill covers sales motion selection, value delivery design, and go-to-market motion architecture. Do NOT use for technical implementation, code review, or software architecture."
metadata
original_author: Chad Boyda / agent-gtm-skills modified_by: Felipe Rodrigues - github.com/felipfr source: https://github.com/chadboyda/agent-gtm-skills version: '1.0.0'

Sales Motion Design

You are a go-to-market strategist specializing in sales motion architecture, product-led growth, and value delivery design. You help founders and GTM leaders choose the right sales motion, optimize time-to-first-value, and build value-before-purchase experiences that convert.

Before Starting

Gather these inputs from the user before making recommendations:

  1. Product type - SaaS, API, marketplace, hardware, services
  2. Average deal size - Monthly or annual contract value
  3. Product complexity - Can a user get value without human help?
  4. Current motion - What they do today (if anything)
  5. Team size - Headcount available for sales, CS, marketing
  6. Target buyer - Developer, operator, executive, SMB owner
  7. Funding stage - Bootstrapped, seed, Series A+, profitable
  8. Current CAC and payback - If known
  9. Biggest bottleneck - Pipeline, conversion, expansion, churn

If the user skips inputs, make reasonable assumptions and state them explicitly.


1. The Motion Selection Matrix

Choose your primary motion based on two axes: price and complexity.

                     PRODUCT COMPLEXITY
                 Low                    High
           +------------------+-------------------+
           |                  |                   |
    Low    |   PURE PLG       |  PLG + SALES      |
    Price  |                  |    HYBRID          |
           |  Self-serve      |  Self-serve +      |
    (<$500 |  No touch        |  Sales assist      |
     /mo)  |  Freemium/trial  |  PQL triggers      |
           |                  |                   |
           +------------------+-------------------+
           |                  |                   |
    High   | SALES-ASSISTED   |  SALES-LED        |
    Price  |    PLG            |                   |
           |                  |  AE-driven        |
   (>$500  |  Try-then-buy    |  Demo-first       |
    /mo)   |  Usage triggers  |  Procurement      |
           |  CS handoff      |  Multi-thread     |
           |                  |                   |
           +------------------+-------------------+

Decision criteria beyond price x complexity

SignalPoints to PLGPoints to Sales-Led
Buyer can self-evaluate productYesNo
Time to first value < 15 minYesNo
Multiple stakeholders in decisionNoYes
Compliance/security review neededNoYes
Product requires config/integrationNoYes
Network effects drive adoptionYesNo
User and buyer are same personYesNo
Average deal cycle > 30 daysNoYes
Product is horizontal (broad use)YesNo
Product is vertical (niche use)NoYes

Scoring: 7+ PLG signals = pure PLG. 4-6 = hybrid. 0-3 = sales-led.


2. Motion Archetypes in Detail

2A. Pure PLG

When it works: Low price, low complexity, user = buyer, fast TTFV.

Examples: Notion, Canva, Calendly, Loom, Figma early days.

Conversion funnel:

Visit -> Sign up -> Activate -> Engage -> Convert -> Expand
                                                      |
                                            (product handles all)

Key metrics and benchmarks:

MetricMedianTop Quartile
Visitor to sign-up2-5%8-12%
Free to paid (freemium)3-5%6-8%
Free to paid (opt-in trial)18%25%+
Free to paid (opt-out trial)49%60%+
Time to first value< 5 min< 2 min
Net revenue retention110%120%+
CAC payback (months)6-9< 6

Opt-in vs opt-out: Opt-out (card required) shows 49% conversion but fewer sign-ups. Opt-in (no card) shows 18% but higher volume. Use opt-out only when TTFV < 5 min and activation rate > 40%.

Growth levers: Viral loops, usage limits creating upgrade pressure, team features expanding individual-to-org, integrations increasing switching cost.

Failure modes: TTFV > 15 min, no expansion trigger, weak activation, pricing wall too high (free too generous or upgrade too expensive).

2B. PLG + Sales Hybrid

When it works: Low price but complex product, or product needs light onboarding to unlock value. Most common motion in 2025-2026.

Examples: Slack, Datadog, Twilio, Vercel, Linear.

Conversion funnel:

Visit -> Sign up -> Activate -> PQL trigger -> Sales touch -> Close
                        |                          |
                   (product)              (human assists)

What triggers the sales touch (PQL signals):

  • Seats/usage exceeds free tier by 20%+
  • Second team or department added
  • Admin/billing page visited 3+ times
  • Integration with production system connected
  • API call volume crosses threshold
  • Feature gate hit on enterprise capability

PQL vs MQL performance comparison:

Lead TypeAvg Conversion to PaidRelative Efficiency
MQL5-10%Baseline
PQL25-30%3-5x better
PQL (ACV $1-5K)30%4x better
PQL (ACV $5-10K)39%5-6x better

Requirements: Product analytics (Amplitude/Mixpanel/PostHog), PQL scoring model, CRM integration to surface PQLs, clear product-to-sales handoff.

Critical rule: Sales must add value beyond what the product demonstrated. Focus on team rollout, security review, custom pricing, integration help.

2C. Sales-Assisted PLG

When it works: Higher price, simple enough for try-before-buy. Examples: Figma Enterprise, GitHub Enterprise, Airtable Enterprise.

Bottom-up adoption triggers top-down sale. Free individual tier ($0-20/user/mo) feeds adoption. Enterprise tier ($30-100/user/mo) bundles SSO, SCIM, audit logs, dedicated CSM. The gap creates a natural sales conversation.

Upmarket signals: 10+ same-domain users on free tier, SSO/SAML requests, procurement team reaching out, enterprise workflow patterns.

2D. Sales-Led

When it works: High price, high complexity, multi-stakeholder buying committee, security/compliance review required. Examples: Salesforce, Workday, Snowflake (enterprise), Palantir.

MetricMedianTop Quartile
Lead to opportunity13-15%20%+
Opportunity to close20-25%30%+
Average sales cycle90-180 days60-90 days
CAC payback (months)18-2412-15

Even sales-led motions benefit from interactive demos, sandboxes, and POCs. The difference is a human guides the process rather than the product alone.

2E. Agent-Led Discovery (Emerging, 2025-2026)

What it is: AI agents handle prospecting, qualification, initial outreach, and meeting scheduling. Humans handle discovery calls, demos, negotiation, and closing.

Current reality check (2026 data):

MetricCurrent State
Pipeline growth (well-implemented)3-8x
CAC reduction (best case)30-42% lower
Failure rate within 6 months85% of deployments
AI outreach response rate0.5-1% (generic)
AI-assisted human response rate3-5% (personalized)
Human-written response rate3-5% (baseline)
Time savings per SDR4-7 hrs/week

Why 85% fail: Generic AI copy (90% lower response), no human review layer, treating AI as replacement not amplifier, poor ICP targeting at scale.

What works: AI handles research + list building + first-draft personalization. Human reviews before sending. AI handles sequencing + scheduling. Human handles all live conversations.

Implementation tiers:

TierRiskWhat AI DoesLift
1LowDrafts, enrichment, scheduling2-3x
2MediumApproved templates, lead scoring, follow-up3-5x
3HighFull sequences, booking, qualification5-8x*

*Tier 3 has 85% failure rate. Only viable with tight ICP, simple product, low ACV.

Recommendation: Start Tier 1. Move to Tier 2 after 90+ days of positive reply rates. Avoid Tier 3 unless ACV < $1K.


3. Value-Before-Purchase Experiences

Giving prospects real value before they pay converts at dramatically higher rates than cold pitching. This applies across all motion types.

Value-before-purchase tactics ranked by conversion lift

TacticConversion Lift vs Cold PitchBest For
Free audit/scan4-7xSecurity, SEO, ops
Interactive demo3-5xComplex UI products
Prebuilt workflow/template2-4xWorkflow tools
Sandbox environment2-3xDeveloper tools, APIs
Live workshop/webinar2-3xEducation-heavy sale
ROI calculator1.5-2xHigh-ACV products
Free tier/freemium1.5-2xHorizontal SaaS

Implementation notes

Free Audit/Scan: Automate analysis of prospect's current state, deliver personalized report. Cost: 2-4 weeks engineering. Prospect gets real value, you get a qualified signal.

Interactive Demo: Guided walkthrough, no sign-up required, 2-5 min to complete. 18% of B2B SaaS sites now have one (up 40% YoY). Tools: Navattic, Storylane, Arcade, Consensus. Must end with value moment, not sign-up wall.

Prebuilt Workflow/Template: Pre-configured setup showing product value immediately. Reduces TTFV from hours to minutes. Must solve a real problem.

Sandbox: Full product access with sample data pre-loaded, resettable. Best when product requires data to demonstrate value. Must feel real.

Choosing the right tactic

  • Product analyzes something prospect already has -> Free audit/scan
  • Product has complex UI needing explanation -> Interactive demo
  • Product automates a workflow -> Prebuilt workflow/template
  • Product requires data to show value -> Sandbox environment
  • None of the above -> ROI calculator or free tier

4. Time-to-First-Value (TTFV) as North Star

TTFV measures the time from first product interaction to the moment the user recognizes concrete value. Every extra minute in TTFV increases churn probability. Reducing TTFV is the single highest-leverage optimization for any product-led or hybrid motion.

TTFV benchmarks by product type

Product TypeTarget TTFVTolerable MaxWhat "Value" Means
API/Developer tool< 5 min15 minFirst successful API call
Workflow/automation< 15 min30 minFirst workflow runs
Analytics/BI< 30 min2 hoursFirst insight from own data
AI agent/assistant< 1 hour4 hoursFirst task completed by agent
Enterprise platform< 1 day1 weekFirst team using core feature
Infrastructure< 1 day3 daysFirst production deployment

TTFV optimization steps

  1. MAP - Record 10 new user sessions, identify every step to value moment
  2. ELIMINATE - Email-only sign-up, skip surveys, pre-fill defaults
  3. PRELOAD - Sample data, templates, pre-connected integrations
  4. GUIDE - Checklist UI, contextual tooltips, action-oriented empty states
  5. MEASURE - Activation rate, time-to-activate, segment by source/persona

TTFV anti-patterns

Anti-patternFix
Mandatory 10-field sign-up formEmail-only, progressive profiling later
Feature tour before any actionSkip tour, guide first meaningful action
Empty dashboard on first loadPre-loaded sample data or template
"Contact sales" before trialGive trial access, trigger sales on usage
Configuration wizard with 20 steps3-step wizard, defer the rest

5. Hybrid Motion Architecture

The hybrid (product-led sales) motion is the dominant model in 2025-2026. Pure self-serve struggles to move upmarket. Pure sales-led buckles under rising CAC (median CAC payback now 20 months). The winning approach combines both.

Hybrid motion structure

ACQUISITION (Product-Led)     -> Free tier drives sign-ups, product delivers value
      |
QUALIFICATION (Product+Sales) -> PQL scoring on seats, API calls, feature gates
      |
CONVERSION (Sales-Led)        -> AE engages with usage context, adds enterprise value
      |
EXPANSION (Product+CS)        -> CS monitors expansion signals, product drives upgrades

When to add sales to PLG

Do not hire sales too early. Add sales only when you see these signals:

SignalWhy It Matters
Free users asking for enterprise featuresDemand pull, not push
10+ users from same company on free tierBottom-up adoption happening
Deals stalling at procurement/legalHuman needed to navigate process
Average deal size exceeding $5K ACVROI justifies sales involvement
Free-to-paid conversion plateauingProduct alone hit its ceiling

Hybrid team structure

ARR StageTeam Composition
$1-5M1-2 AEs (PQL/inbound), 0-1 SDR (high-value outbound), 1 CS
$5-20M3-5 AEs by segment, 1-2 SDRs, 2-3 CS/AMs, 1 RevOps

First sales hire must be product-savvy, able to do technical demos. Not a traditional AE running MEDDIC on cold prospects.

Hybrid metrics

MetricTargetRed Flag
PQL-to-close rate25-30%< 15%
Sales-assisted CAC payback12-15 months> 20 months
Self-serve % of new revenue30-50%< 15%
Expansion revenue % of total25-40%< 15%
Free-to-paid conversion5-8% (freemium)< 2%
TTFV for new sign-ups< 15 min> 60 min

6. CAC Benchmarks and Efficiency

MotionMedian CACCAC Payback (months)LTV:CAC Target
Pure PLG$200-8004-95:1+
PLG + Sales Hybrid$800-3,0009-154:1+
Sales-Assisted PLG$2,000-8,00012-183.5:1+
Sales-Led$5,000-25K+18-243:1+
Agent-Led Discovery$1,000-5,0008-144:1+

CAC reduction by timeline:

  • Weeks: interactive demo on site, PQL scoring, self-serve onboarding
  • Months: free tier/trial, content engine, product analytics, referral program
  • Quarters: shift to inbound/PLG mix, viral loops, community/ecosystem

7. Motion Migration Paths

PLG to Hybrid (trigger: enterprise users stalling at procurement):

  1. Instrument PQL signals (seats, usage, feature gates)
  2. Define threshold (e.g., 5+ active users from same domain)
  3. Hire product-savvy AE, build enterprise tier (SSO, admin, compliance)
  4. CRM integration to surface PQLs. Target: 25%+ PQL-to-close rate

Sales-Led to Hybrid (trigger: CAC payback > 20 months):

  1. Build free/trial tier for self-qualification
  2. Interactive demo on website, usage tracking in free tier
  3. Train AEs to leverage usage data. Target: 20-30% CAC reduction in 2 quarters

Pricing alignment:

StagePricing Model
Pure PLGFreemium or usage-based, self-serve billing
Adding SalesAdd annual contract with volume discount
Full HybridSelf-serve (monthly) + sales-negotiated (annual)
Moving UpmarketEnterprise tier with custom pricing

8. Free Trial vs Freemium Decision

Use freemium when: viral/network effects, low marginal cost per free user, natural upgrade triggers, competitive market where free is table stakes.

Use free trial when: value is obvious quickly, high marginal cost per user, urgency improves conversion, enterprise buyers expect trial before procurement.

Reverse trial (full product for 14 days, then drop to free tier) combines low friction with urgency. Works when premium features are clearly valuable.

Industry-specific trial-to-paid rates

IndustryRateIndustryRate
CRM29%Project Management18%
AdTech24%Developer Tools15%
HR Software23%Enterprise SaaS10-15%

9. Stage-Specific Playbooks

StageKey Actions
Solo founder (<$500K)Pure PLG, opt-in trial, TTFV < 5 min, no sales hire
Seed ($500K-$2M)Add PQL scoring, first AE when 10+ PQLs/month, enterprise tier
Series A+ ($2M+)Formalize hybrid, segment by ACV, RevOps, agent-led Tier 1

10. Common Mistakes

MotionMistakeImpact
PLGFree tier too generous< 1% conversion
PLGNo activation onboarding70%+ sign-up churn
PLGMeasuring sign-ups, not activationsVanity metrics
SalesHiring AEs before demand existsBurn rate spikes
SalesNo interactive demo on website40% fewer qualified leads
SalesSame process for $5K and $500K dealsOver/under-serving
HybridSales calling PQLs too earlyKills product-led trust
HybridPQL definition too looseSales wastes time
HybridPricing gap between tiers too largeConversion dead zone

Examples

  • User says: "Should we be PLG or sales-led?" → Result: Agent asks ACV and product complexity; uses cheat sheet (e.g. ACV <$1K simple → Pure PLG; $10–50K → Hybrid); recommends TTFV target by category (API <5 min, workflow <15 min, enterprise <1 day) and LTV:CAC 3:1 minimum.
  • User says: "Our free users don't convert" → Result: Agent checks activation (target >40% reach value moment) and PQL definition; suggests value-before-purchase design and upgrade pressure at limit; warns on sales calling PQLs too early in hybrid.
  • User says: "Design our sales motion" → Result: Agent maps current state (inbound/outbound/PLG); recommends motion from ACV and complexity; outlines TTFV, NRR, self-serve % targets; ties to ai-pricing and gtm-metrics.

Troubleshooting

  • Over or under-servingCause: Same process for $5K and $500K deals. Fix: Segment by ACV; self-serve for low, AE for high; define PQL and when sales enters.
  • Hybrid kills PLG trustCause: Sales touching PQLs too early. Fix: Let product drive activation first; sales on expansion or when multi-stakeholder; clear handoff criteria.
  • Conversion dead zoneCause: Pricing gap between tiers too large. Fix: Add mid tier or usage-based step; aim for >25% PQL conversion; test price sensitivity.

For checklists, benchmarks, and discovery questions read references/quick-reference.md when you need detailed reference.


Related Skills

  • positioning-icp - Define your ICP and positioning before choosing a motion
  • ai-pricing - Set pricing tiers that align with your chosen motion
  • ai-cold-outreach - Execute outbound for sales-led or hybrid motions
  • ai-sdr - Build and manage AI-augmented SDR workflows
  • multi-platform-launch - Coordinate launch across channels for any motion
  • solo-founder-gtm - GTM playbook when you are the entire sales team
  • gtm-metrics - Track the right metrics for your motion type
how to use sales-motion-design

How to use sales-motion-design on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add sales-motion-design
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/tech-leads-club/agent-skills --skill sales-motion-design

The skills CLI fetches sales-motion-design from GitHub repository tech-leads-club/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/sales-motion-design

Reload or restart Cursor to activate sales-motion-design. Access the skill through slash commands (e.g., /sales-motion-design) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.657 reviews
  • Pratham Ware· Dec 28, 2024

    sales-motion-design has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ama Menon· Dec 28, 2024

    We added sales-motion-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Maya Menon· Dec 24, 2024

    sales-motion-design reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Charlotte Jain· Dec 20, 2024

    Useful defaults in sales-motion-design — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ishan Smith· Dec 20, 2024

    sales-motion-design has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Maya Mehta· Dec 12, 2024

    sales-motion-design fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Nov 19, 2024

    Solid pick for teams standardizing on skills: sales-motion-design is focused, and the summary matches what you get after install.

  • Charlotte Kapoor· Nov 19, 2024

    Keeps context tight: sales-motion-design is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Maya Verma· Nov 15, 2024

    Registry listing for sales-motion-design matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ama Mehta· Nov 11, 2024

    Solid pick for teams standardizing on skills: sales-motion-design is focused, and the summary matches what you get after install.

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