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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'

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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.

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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

| Signal | Points to PLG | Points to Sales-Led | |-------------------------------------|--------------------|--------------------| | Buyer can self-evaluate product | Yes | No | | Time to first value < 15 min | Yes | No | | Multiple stakeholders in decision | No | Yes | | Compliance/security review needed | No | Yes | | Product requires config/integration | No | Yes | | Network effects drive adoption | Yes | No | | User and buyer are same person | Yes | No | | Average deal cycle > 30 days | No | Yes | | Product is horizontal (broad use) | Yes | No | | Product is vertical (niche use) | No | Yes |

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

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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: | Metric | Median | Top Quartile | |-------------------------------|----------------|----------------| | Visitor to sign-up | 2-5% | 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 retention | 110% | 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 Type | Avg Conversion to Paid | Relative Efficiency | |-----------|----------------------|---------------------| | MQL | 5-10% | Baseline | | PQL | 25-30% | 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.

| Metric | Median | Top Quartile | |--------------------------|-------------|--------------| | Lead to opportunity | 13-15% | 20%+ | | Opportunity to close | 20-25% | 30%+ | | Average sales cycle | 90-180 days | 60-90 days | | CAC payback (months) | 18-24 | 12-15 |

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): | Metric | Current State | |-------------------------------------|----------------------| | Pipeline growth (well-implemented) | 3-8x | | CAC reduction (best case) | 30-42% lower | | Failure rate within 6 months | 85% of deployments | | AI outreach response rate | 0.5-1% (generic) | | AI-assisted human response rate | 3-5% (personalized) | | Human-written response rate | 3-5% (baseline) | | Time savings per SDR | 4-7 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:

| Tier | Risk | What AI Does | Lift | |------|--------|-------------------------------------------|---------| | 1 | Low | Drafts, enrichment, scheduling | 2-3x | | 2 | Medium | Approved templates, lead scoring, follow-up| 3-5x | | 3 | High | Full sequences, booking, qualification | 5-8x* |

*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.

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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

| Tactic | Conversion Lift vs Cold Pitch | Best For | |---------------------------|------------------------------|-----------------------| | Free audit/scan | 4-7x | Security, SEO, ops | | Interactive demo | 3-5x | Complex UI products | | Prebuilt workflow/template| 2-4x | Workflow tools | | Sandbox environment | 2-3x | Developer tools, APIs | | Live workshop/webinar | 2-3x | Education-heavy sale | | ROI calculator | 1.5-2x | High-ACV products | | Free tier/freemium | 1.5-2x | Horizontal 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 requ