sales-motion-design

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

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.

---

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.

---

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 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 Type	Target TTFV	Tolerable Max	What "Value" Means
API/Developer tool	< 5 min	15 min	First successful API call
Workflow/automation	< 15 min	30 min	First workflow runs
Analytics/BI	< 30 min	2 hours	First insight from own data
AI agent/assistant	< 1 hour	4 hours	First task completed by agent
Enterprise platform	< 1 day	1 week	First team using core feature
Infrastructure	< 1 day	3 days	First 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-pattern	Fix
Mandatory 10-field sign-up form	Email-only, progressive profiling later
Feature tour before any action	Skip tour, guide first meaningful action
Empty dashboard on first load	Pre-loaded sample data or template
"Contact sales" before trial	Give trial access, trigger sales on usage
Configuration wizard with 20 steps	3-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:

Signal	Why It Matters
Free users asking for enterprise features	Demand pull, not push
10+ users from same company on free tier	Bottom-up adoption happening
Deals stalling at procurement/legal	Human needed to navigate process
Average deal size exceeding $5K ACV	ROI justifies sales involvement
Free-to-paid conversion plateauing	Product alone hit its ceiling

Hybrid team structure

ARR Stage	Team Composition
$1-5M	1-2 AEs (PQL/inbound), 0-1 SDR (high-value outbound), 1 CS
$5-20M	3-5 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

Metric	Target	Red Flag
PQL-to-close rate	25-30%	< 15%
Sales-assisted CAC payback	12-15 months	> 20 months
Self-serve % of new revenue	30-50%	< 15%
Expansion revenue % of total	25-40%	< 15%
Free-to-paid conversion	5-8% (freemium)	< 2%
TTFV for new sign-ups	< 15 min	> 60 min

---

6. CAC Benchmarks and Efficiency

Motion	Median CAC	CAC Payback (months)	LTV:CAC Target
Pure PLG	$200-800	4-9	5:1+
PLG + Sales Hybrid	$800-3,000	9-15	4:1+
Sales-Assisted PLG	$2,000-8,000	12-18	3.5:1+
Sales-Led	$5,000-25K+	18-24	3:1+
Agent-Led Discovery	$1,000-5,000	8-14	4:1+

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:

Stage	Pricing Model
Pure PLG	Freemium or usage-based, self-serve billing
Adding Sales	Add annual contract with volume discount
Full Hybrid	Self-serve (monthly) + sales-negotiated (annual)
Moving Upmarket	Enterprise 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

Industry	Rate	Industry	Rate
CRM	29%	Project Management	18%
AdTech	24%	Developer Tools	15%
HR Software	23%	Enterprise SaaS	10-15%

---

9. Stage-Specific Playbooks

Stage	Key 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

Motion	Mistake	Impact
PLG	Free tier too generous	< 1% conversion
PLG	No activation onboarding	70%+ sign-up churn
PLG	Measuring sign-ups, not activations	Vanity metrics
Sales	Hiring AEs before demand exists	Burn rate spikes
Sales	No interactive demo on website	40% fewer qualified leads
Sales	Same process for $5K and $500K deals	Over/under-serving
Hybrid	Sales calling PQLs too early	Kills product-led trust
Hybrid	PQL definition too loose	Sales wastes time
Hybrid	Pricing gap between tiers too large	Conversion 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-serving → Cause: 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 trust → Cause: Sales touching PQLs too early. Fix: Let product drive activation first; sales on expansion or when multi-stakeholder; clear handoff criteria.
• Conversion dead zone → Cause: 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.

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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