Growth Models — Flywheel, Bowtie, ABM & GTM Archetypes¶

A comprehensive reference for B2B SaaS growth models covering the mechanics of momentum-based growth, post-sale expansion patterns, account-based marketing orchestration, and how to select and combine the right growth archetype for your stage and context.

1. The Flywheel Model¶

Funnel vs. Flywheel: The Shift in Mental Model¶

The traditional marketing funnel (Attract → Convert → Close → Delight) treats growth as a linear, one-directional process. You push prospects through stages; anyone who falls out is lost. The model optimizes for throughput and has a hard ceiling: spend stops, growth stops.

HubSpot introduced the flywheel (2018) as a fundamental reconception. The insight: in a SaaS business, your existing customers are the source of your next customers. Every happy customer adds force to the wheel — through referrals, reviews, case studies, renewals, and expansions. The company that builds a reputation for delighting customers grows faster over time because growth compounds, not diminishes.

Source: HubSpot, How to Grow with a Flywheel (2018); Brian Dixon's flywheel research.

Stage Definitions: Attract, Engage, Delight¶

HubSpot's three-stage flywheel maps to the old funnel but adds a critical loop:

Attract Stage
- What it is: Drawing the right people (fits your ICP) to your business through valuable content, organic presence, and brand signals.
- Old funnel equivalent: Awareness
- Key plays: SEO content, paid social, organic social, PR, podcast appearances, speaking at events.
- Force multiplier: Your brand reputation. A well-known brand in a category gets click-throughs that no unknown company can buy.

Engage Stage
- What it is: Building relationships, demonstrating value, and earning the right to solve a problem for the prospect. The goal is to convert a stranger into a lead or trial user.
- Old funnel equivalent: Consideration + Decision
- Key plays: Lead magnets, nurture sequences, product trials, demos, chatbots, sales outreach, targeted content.
- Force multiplier: Speed to respond. Companies that respond to inbound leads within 5 minutes are 10x more likely to convert (Insidesales.com, pre-Gong data).

Delight Stage
- What it is: Exceeding expectations so the customer becomes an advocate. Support that solves problems fast, onboarding that actually gets them to value, renewal conversations framed around outcomes.
- Old funnel equivalent: Retention + Loyalty
- Key plays: Proactive customer success, in-app guidance, CSM touchpoints, customer community, feedback loops.
- Force multiplier: Advocates create the Attract loop. A referring customer brings pre-qualified prospects who already trust the recommendation.

Friction Points in the Flywheel¶

The flywheel can slow — or even reverse — if friction accumulates at any stage:

Measuring Momentum at Each Stage¶

Momentum = Velocity × Mass. In the flywheel:

• Velocity = how fast customers move through stages and return as referrals
• Mass = the number and quality of customers in each stage

Lead-to-Close Velocity (Engage stage)
- Average sales cycle length (target: shortening over time)
- Time from MQL to SQL to opportunity
- Demo-to-trial conversion rate
- Formula: (Deals closed × average deal size) / Average cycle days

Net Promoter Score (Delight stage)
- NPS > 50 = strong flywheel; NPS < 0 = drag on the wheel
- Track quarterly, segment by ACV tier and product line

Referral Rate (output of Delight feeding Attract)
- % of customers who refer at least one other customer per year
- Target: 20–30% for mid-market; 10–15% for enterprise

Flywheel Velocity Metric (HubSpot's framework)
HubSpot's formula: Flywheel Momentum = (New + Expansion − Churn) × Customer Success Score
- A simplified momentum score: (New ARR + Expansion ARR) / (Churned ARR + Contraction ARR)
- Momentum > 1.0 means the flywheel is accelerating

Source: HubSpot Flywheel Momentum Framework (HubSpot Academy); Dixon, H. The Flywheel Effect (2019).

SaaS Adaptations¶

The HubSpot flywheel was built for SMB/mid-market with an inbound motion. SaaS companies with different GTM motions adapt it:

For PLG companies:
- The Engage stage is in-product. The "flywheel" starts when a user signs up for free. Their activation → adoption → expansion loop IS the flywheel.
- Force comes from time-to-value: faster activation = faster referrals
- Attract is largely product-led (SEO, product hunt, word of mouth)
- Delight is product-experience + community

For Sales-Led Growth companies:
- The flywheel has a heavy Engage stage driven by AE capacity
- The Attract stage feeds marketing-qualified leads into a sales motion
- The flywheel can feel slower because the Engage stage is bottlenecked on headcount
- Growth lever: improving sales efficiency (more closed/won per rep) vs. adding more reps

For High-Touch Enterprise:
- Flywheel operates at the account level, not contact level
- Land (long, expensive sales) → Expand (land-and-expand within account) → Refer (executive references)
- Force multiplier: executive sponsorship and success metrics owned by champion

2. The Bowtie Model¶

The Structure: Wide–Narrow–Wide¶

The Bowtie Model, developed by Winning by Design (Jacco van der Knaap, Andrej Stoppel, and the WbD team), reconceives the customer lifecycle as a bowtie rather than a funnel or flywheel. The left wing is acquisition; the "knot" is the customer; the right wing is expansion.

[Wide Left: Acquisition]
     ↑    ↑    ↑
   Lead → MQL → SQL → Opportunity → Won → Customer
                                         ↓
[Central: Customer Lifecycle] ←——————— THIS IS THE WAIST ————————
                                         ↑
[Wide Right: Expansion]
  Upsell → Cross-sell → Renewal ←→ Referral ←→ Advocacy

The core insight: The most dangerous moment in the customer lifecycle is the waist — the transition from "prospect" to "customer." This is where momentum dies if you don't handle it well. The left bolt-on and right bolt-on (see below) surround and protect this critical transition.

How It Differs from the Funnel and Flywheel¶

The Bowtie treats acquisition and expansion as bolt-ons to the central customer lifecycle. The central bolt-on (the customer experience itself) is the most important part of the model.

The Three Bolt-Ons¶

Central Bolt-On: The Customer Experience

The knot of the bowtie — the actual customer lifecycle. This is not a stage; it's the entire relationship, measured through the SPICED framework (Winning by Design's customer success measurement model):

A customer who scores well on all six SPICED dimensions is expansion-ready. A customer scoring poorly on any dimension is at risk.

Source: Winning by Design, The SPICED Customer Success Framework (2021).

Left Bolt-On: Acquisition Motion

The left side of the bowtie handles all the ways new customers arrive. The goal is not just volume but ICP-fit at entry — customers who are more likely to succeed (perform well on SPICED) will have lower churn and higher expansion.

Key metrics for the left bolt-on:

The goal of the left bolt-on: reduce time-to-value for new customers, because time-to-value is the leading indicator of retention and expansion.

Right Bolt-On: Expansion Motion

The right side is where SaaS companies escape the trap of "land and stagnate." Expansion revenue turns a static customer base into a compounding growth engine. The right bolt-on has four primary plays:

Net Revenue Retention (NRR) is the north-star metric for the right bolt-on:

NRR = (Starting ARR + Expansion − Churn − Contraction) / Starting ARR

• World-class NRR: >130% (Zendesk, Snowflake, Slack in growth phase)
• Good NRR: 110–120%
• Healthy floor: 100% (no churn eating growth)
• Warning: <100% means you're running to stand still

The Bowtie connects NRR to the SPICED score: customers who score well on SPICED are candidates for the right bolt-on. The expansion conversation should start from a place of "we helped you achieve X; what's next?"

Where PLG Fits in the Bowtie¶

PLG companies typically compress the left bolt-on — the product itself becomes the acquisition motion. Users self-serve through the product, convert from free to paid, and the "won" stage happens in-product.

The bowtie for PLG:
- Left bolt-on is minimal: product-led, community-led, or virality-led acquisition
- Central bolt-on: the in-product onboarding + activation experience
- Right bolt-on: expansion through seat upgrades, usage-based tiers, and product-led cross-sell

PLG companies that succeed convert free users to paid at rates of 5–15% (consumer-propagation models like Dropbox early days) or 2–5% (B2B SaaS, lower-frequency products). The key expansion lever is usage density — the more deeply users integrate the product into their workflow, the stickier the subscription.

3. ABM Playbook¶

What ABM Is and Why It Works Now¶

Account-Based Marketing (ABM) is a strategic approach that treats individual accounts (companies) as markets in their own right. Rather than targeting broad personas and hoping enough convert, you identify a specific set of target accounts and personalize every touchpoint to that account's context, stakeholders, and buying process.

ABM's resurgence in B2B SaaS is driven by three converging forces:
1. Rising buyer expectations: Buyers expect vendors to understand their industry and specific challenges before reaching out
2. Increasing buyer-controlled journey: 70–80% of B2B buying decisions are made before a prospect talks to Sales (Gartner, 2022)
3. Data precision enabling personalization at scale: Tools like 6sense, Demandbase, and Drift allow behavioral targeting and intent-signal detection at the account level

The core premise: the cost of acquiring a large enterprise account often justifies highly personalized, multi-touch, multi-channel approach. ABM justifies the investment by targeting accounts with high ACV potential.

Source: Demandbase, ABM Platform Buyer Survey (2023); Gartner, B2B Buying Journey Report (2022).

The Three Tiers of ABM¶

ABM is typically implemented in three tiers, each with different investment levels, personalization depth, and team structures:

Tier 1: 1:1 ABM (Strategic/Enterprise)
- Target: 1–25 high-value accounts per quarter
- ACV range: Typically $250K–$2M+
- Approach: Fully personalized. Every touchpoint is tailored to the specific account — personalized landing pages, direct mail campaigns, executive outreach sequences, custom content, in-person events
- Team: Dedicated ABM specialist or strategists working with assigned AE
- Timeline: 6–18 month sales cycles
- Typical company fit: Logo accounts, strategic partnerships, tectonic market opportunities

Tier 2: 1:Few ABM (Segment/Similarity)
- Target: 25–100 accounts per quarter, grouped by shared characteristics (same vertical, same tech stack, similar company size)
- ACV range: $50K–$250K
- Approach: Cohort-level personalization. Shared messaging and content for the segment, with personalization at the account level within the cohort. Personalized content at the industry and role level; account-specific overrides for priority accounts
- Team: ABM manager supporting multiple AEs; campaigns built once, adapted per segment
- Timeline: 3–6 month sales cycles
- Typical company fit: Mid-market with defined ICP segments

Tier 3: 1:Many ABM (Programmatic/Light)
- Target: Hundreds to thousands of accounts using intent data and firmographic filters
- ACV range: $5K–$75K
- Approach: Digital-first, broad personalization. Intent-signal-triggered ads, personalized LinkedIn outreach sequences, account-specific retargeting. Light-touch personalization (name, company in subject lines) vs. full account-level customization
- Team: Demand gen team with ABM tooling support (6sense, Demandbase, Terminus)
- Timeline: 1–3 month sales cycles
- Typical company fit: SMB and lower mid-market with high-velocity motion

Source: Demandbase, The Three Tiers of ABM (2023); ITSMA, ABM Leadership Survey (2022).

Targeting Criteria¶

Firmographic Filters (what the company is)

Technographic Filters (what technology the company uses)

Tools for technographic data: Clearbit, Bombora, 6sense, Datanyze, BuiltWith.

Behavioral Filters (what the company is doing)

Intent data (providers: Bombora, G2, TrustInsights) aggregates behavioral signals across the web and scores accounts by topic or category interest. An account spiking on "CRM migration" or "customer success platform" is in active evaluation — ready for ABM activation.

Source: Bombora, The State of Intent Data (2023); 6sense, ABM Measurement Framework (2023).

Orchestration Across Channels¶

ABM is not a channel; it's a strategy that requires coordinated execution across multiple channels. The orchestration sequence typically follows an account's buying journey:

Channel Stack for ABM:

Typical Orchestration Sequence (3-month cycle for Tier 2):

Month 1 — Awareness & Education
- LinkedIn awareness campaign to target account list (lookalike + account targeting)
- Display retargeting on category-relevant content
- Personalized direct mail (book relevant to their industry challenge)
- Trigger: "Welcome to the [industry] series" — personalized by account name

Month 2 — Engagement & Research
- Email sequence with value-add content (case study from same vertical)
- LinkedIn ad campaign with problem-specific content
- Sales outreach with specific reference to their context
- Trigger: If they visit pricing page, escalate to demo offer

Month 3 — Decision & Close
- Executive direct mail (differentiated point of view, not a brochure)
- Targeted LinkedIn ads to buying committee
- Demo with reference to their specific use case
- Escalation: executive meeting if engagement score > threshold

ABM Measurement: Influenced Revenue & Account Engagement Scoring

The hardest part of ABM is attribution. The standard approach:

1. Influenced Revenue
- Track all touchpoints in the buyer journey and credit ABM for any account that enters opportunity with ABM touches in the preceding 90 days
- Formula: (# of closed-won deals with ABM touch) × (average deal size) / (# of total closed-won deals)
- Target: ABM-influenced deals should represent 50–70% of pipeline at mature ABM programs

2. Account Engagement Score
A composite score tracking engagement across channels:

Accounts scoring above threshold (e.g., 50 points) are "hot" — prioritize sales follow-up.

3. Account-Based Pipeline Coverage
- Coverage ratio: # of target accounts in active ABM motion / total target account universe
- Target: 30–50% of ICP universe in active ABM motion at any given time

Source: Demandbase, ABM Measurement Playbook (2023); Terminus, ABM ROI Report (2022).

4. Growth Archetype Taxonomy¶

The Four Primary Archetypes¶

B2B SaaS companies typically follow one dominant growth archetype, though hybrid models are increasingly common. Choosing the right archetype — and knowing when to shift — is one of the most consequential decisions a GTM leader makes.

1. Product-Led Growth (PLG)

The product is the primary driver of acquisition, conversion, and expansion. Growth happens when the product itself creates value compelling enough that users bring it into their organization.

Archetypal companies: Slack, Figma, Notion, Zoom, GitHub, Dropbox, Canva

Core mechanics:
- Free tier or free trial drives top-of-funnel volume
- Viral loops (sharing, collaboration, team invites) amplify acquisition
- Product-qualified leads (PQLs) — users who've hit an activation event — convert to paid
- Expansion is usage-driven: more users → more seats → higher tier

Key metrics: Time-to-value (TTV), PQL conversion rate, viral coefficient, expansion rate, NRR

When it works: Low-to-mid ACV ($0–$25K); self-serve or low-touch purchase; product that delivers value before the sales conversation; viral/collaborative product mechanics; large ICP market

When it struggles: High ACV requiring sales; complex implementation; products that require behavior change without immediate value; enterprise security/compliance requirements

2. Sales-Led Growth (SLG)

A dedicated sales team drives acquisition. Marketing generates leads; sales converts them; CS retains them. The AE is the primary growth engine.

Archetypal companies: Salesforce (enterprise), Oracle, Workday, traditional SaaS before 2015

Core mechanics:
- Marketing generates MQLs → Sales follows up
- AE-led discovery, demo, proposal, negotiation, close
- Account Executive owns the relationship; CS owns post-sale
- Land-and-expand is possible but secondary to new logo acquisition

Key metrics: MQL-to-SQL rate, SQL-to-Opportunity rate, Opportunity-to-Close rate, ACV, sales cycle length, quota attainment, CAC payback period

When it works: High ACV ($50K+); complex sale requiring human explanation; multiple stakeholders; long sales cycles; products requiring behavior change; regulated industries

When it struggles: High CAC relative to ACV; slow sales cycles limiting growth rate; talent-intensive scaling; low ICP density (hard to find the right prospects)

3. Community-Led Growth (CLG)

Customers become advocates who recruit other customers. Growth comes from building a passionate, active community around a product, category, or mission.

Archetypal companies: WordPress (early), HubSpot (INBOUND community), Atlassian (community forums), Snowflake (Data Cloud ecosystem), Clari (revenue collective), Salesforce (AppExchange community)

Core mechanics:
- Community creates content, plugins, use cases, and word-of-mouth
- Community events (user groups, conferences, online forums) become lead gen
- Developers build on the platform (marketplace ecosystem)
- Customers evangelize in peer networks

Key metrics: Community MAUs, community-driven leads per quarter, referral rate, NPS, community NPS vs. product NPS, event attendance, user group formation rate

When it works: Developer-led or platform businesses; products with high network effects; products where customers identify with a shared identity or mission; markets where peer recommendation drives decisions

When it struggles: Products without strong community mechanics; low-touch/no-dev ecosystem; slow community formation in niche markets; requires years to build compounding community effects

4. Marketing-Led Growth (MLG)

Brand, content, and demand generation are the primary drivers. The company builds a predictable, scalable demand engine that feeds a moderate-touch sales or product motion.

Archetypal companies: HubSpot (classic era), Drift (before Zoom acquisition), Hubspot, ActiveCampaign,monday.com

Core mechanics:
- Inbound content engine (SEO + blog + podcast + video)
- Paid acquisition to accelerate
- Nurture and demo conversion
- Lower ACV with high-volume motion

Key metrics: Organic traffic growth, inbound MQL volume, content-attributed pipeline, CAC, inbound mix (inbound vs. outbound)

When it works: Strong content production capability; SEO-friendly category; clear buyer journey with information-gathering phase; mid-market ICP; products where thought leadership influences buying decisions

When it struggles: Categories with short buying windows (not enough time for content to work); highly technical products requiring sales explanation; competitive SEO markets; products with no clear content angle

Decision Framework: Choosing Your Archetype¶

No archetype is inherently superior. The right choice depends on five key variables:

The ACV Framework (simplified):
- ACV < $5K: PLG is almost always the right answer. Sales cannot scale economically.
- ACV $5K–$25K: Hybrid. PLG for acquisition, sales-assisted for conversion and expansion.
- ACV $25K–$100K: Sales-led primary, PLG elements for expansion and lower-touch upsell.
- ACV > $100K: Enterprise sales (SLG), with ABM overlay for target account prioritization.

Source: Reforge, GTM Archetypes (2022); Bessemer Venture Partners, PLG Market Map (2023); OpenView Partners, 2023 SaaS Benchmark.

Transition Points: When to Shift Archetype¶

Most companies don't stay in one archetype forever. Common transitions:

PLG → SLG (Product-Led → Sales-Led)
- Trigger: ACV is rising; enterprise accounts want to talk to sales; churn is driven by expansion failures, not acquisition failures
- What changes: Hire AEs; create sales-assisted motion; add PLG → SQL handoff process; add enterprise-tier pricing
- Risk: Over-investing in sales before product can close enterprise deals on its own; PLG culture clash with sales culture

SLG → PLG (Sales-Led → Product-Led)
- Trigger: CAC is too high relative to ACV; growth is bottlenecked by sales headcount; product has become strong enough for self-serve
- What changes: Build free tier; invest in viral loops; create product-led onboarding; reduce sales dependence for smaller deals
- Risk: Cannibalizing sales deals; sales team morale; losing enterprise control of the sale

Any → CLG (Adding Community)
- Trigger: Churn is a problem; NPS is high but referrals are low; category leadership requires an ecosystem
- What changes: Hire community lead; build community infrastructure (Slack, forums, events); create community-first content
- Risk: Community takes 2–3 years to compound; easy to underinvest; difficult to measure direct ROI

Single → Hybrid (Adding Mixed Model)
- Trigger: One archetype hits a ceiling; ICP is diverse (some segments fit PLG, others need sales)
- What changes: Segment-based motion (PLG for SMB, SLG for enterprise); unified data layer; separate but coordinated teams

5. Integrated Motion: Combining Growth Models¶

The Case for Combining Models¶

Most high-growth B2B SaaS companies operate with multiple growth models simultaneously. The single-archetype approach is a simplification that works best in the early days. As companies scale, they encounter:

• ACV expansion — As ACV grows, you need a sales motion to close large deals while PLG handles SMB
• Segment diversity — Different market segments have different buying preferences
• NRR pressure — Expansion revenue requires customer success and product expansion plays that go beyond the primary archetype
• Channel saturation — One channel hits diminishing returns and you need new vectors

The Three Canonical Combinations¶

1. PLG + SLG (Product-Led + Sales-Led)

The most common hybrid. Product drives top-of-funnel for SMB and developer segments; sales engages for conversion at mid-market and expansion into enterprise.

How it works in practice:
- PLG: Free tier → PQL → self-serve conversion
- SLG: Inbound demo requests (from PLG funnel) → AE-assisted close for MM; targeted outbound for EL
- Expansion: CS-led for PLG customers; AE-led for SLG customers
- Data: Shared CRM and product analytics; PQL score triggers sales alert

Key metrics to unify:
- PQL conversion rate (PLG metric)
- Sales-assisted close rate (SLG metric)
- ACV comparison: PLG-sourced vs. SLG-sourced
- Time-to-first-expansion for each motion

Source: OpenView Partners, The PLG + SLG Playbook (2023).

2. SLG + ABM (Sales-Led + Account-Based Marketing)

High-ACV companies use ABM to prime the pump for the sales team. ABM identifies and engages target accounts before Sales reaches out, resulting in warmer pipelines and shorter sales cycles.

How it works in practice:
- ABM: Tier 1 target accounts (1:1 ABM) → marketing creates personalized content → multiple touchpoints before sales outreach
- SLG: Sales executes outreach with context from ABM (referencing account's research journey)
- Alignment: Sales and marketing agree on target account list quarterly; joint account planning for top 20 accounts

Key metrics:
- ABM-influenced pipeline (target: 50%+ of total pipeline)
- Account engagement score before first contact (target: >30 before outreach)
- Sales cycle length for ABM-targeted accounts vs. non-ABM (target: 20–30% shorter)

3. PLG + CLG (Product-Led + Community-Led)

Developer platforms and collaboration tools often combine PLG (product virality) with CLG (community advocacy). The product drives adoption; the community drives retention and referrals.

How it works in practice:
- PLG: Viral invites (invite teammates, share files); free tier for developers
- CLG: Community forums, developer events, marketplace (Atlassian/Slack model)
- Expansion: Community-driven adoption within account (team → org → enterprise)
- Retention: Community reduces churn by building switching costs and shared identity

Mixed Model Playbook: A Growth-Stage Guide¶

Stage 1 — Product-Market Fit (PMF)
- Primary archetype: PLG or early community
- Secondary: None yet
- Focus: Find the product-led growth loop; get users to value fast; measure viral coefficient
- Risk: Premature sales motion burns capital on deals that don't close

Stage 2 — Scaling PLG (PMF found; ready to accelerate)
- Primary archetype: PLG
- Secondary: Begin community (CLG) if product has network effects
- Focus: Optimize activation; build viral loops; start community to deepen engagement
- Risk: PLG ceiling (CAC rises as organic pool saturates)

Stage 3 — Sales-Assisted (Growth slowing from PLG ceiling; ACV rising)
- Primary archetype: PLG + Sales-Assisted (SLG)
- Secondary: ABM for top-tier accounts
- Focus: Hire first AEs; build PQL → sales handoff process; add enterprise tier
- Risk: Sales-motivated team de-optimizes PLG; culture clash

Stage 4 — Enterprise / Full GTM (Multi-segment, multi-archetype)
- Primary archetype: Hybrid (segment-based)
- Secondary: ABM for Tier 1 accounts; CLG for ecosystem
- Focus: Separate motions for segments; unified data platform; clear handoff rules between motions
- Risk: Organizational complexity; misaligned incentives across motions

Stage 5 — Expansion-Focused (NRR is the growth lever)
- Primary archetype: Customer-success-led expansion
- Secondary: Upsell/cross-sell motion; referral program; community advocacy
- Focus: Expansion plays at every bolt-on of the bowtie; NRR as the primary north-star
- Risk: Neglecting new customer acquisition while focusing on expansion

The Unified Data Layer¶

Combining growth models requires a shared data infrastructure. Without it, each team operates in a silo:

The go-to-market tech stack must support all active motions:
- CRM: HubSpot, Salesforce (account-level data for all motions)
- Product analytics: Amplitude, Mixpanel (product usage data for PQLs)
- ABM platform: 6sense, Demandbase, Terminus (account-level intent signals)
- Community platform: Slack, Circle, Higher Logic (community engagement data)
- Revenue intelligence: Gong, Chorus (sales conversation data feeds back to product and marketing)

Transition Indicators: When to Shift Motion¶

Key Frameworks Quick Reference¶

Flywheel Momentum Score¶

Momentum = (New ARR + Expansion ARR) / (Churned ARR + Contraction ARR)
Momentum > 1.0 = Accelerating flywheel

Bowtie SPICED Score¶

Six dimensions of customer success: Success, Progress, Integration, Climate, Economy, Discovery. All six firing → expansion-ready.

Net Revenue Retention¶

NRR = (Starting ARR + Expansion − Churn − Contraction) / Starting ARR
World-class: >130% | Good: 110–120% | Floor: 100%

ABM Account Engagement Score¶

Score = Email Opens (×1) + Email Clicks (×3) + Website Visits (×5) 
      + Content Downloads (×10) + LinkedIn Engagement (×3) 
      + Demo Booked (×25) + Executive Meeting (×50)
Score > 50 = Hot account, prioritize sales follow-up

ACV Archetype Decision¶

ACV < $5K     → PLG
ACV $5K–$25K → PLG + Sales-Assisted  
ACV $25K–$100K → SLG Primary + PLG Elements
ACV > $100K  → Enterprise SLG + ABM Overlay

Growth Stage Archetype Map¶

PMF → PLG/early CLG
Scaling → PLG + early CLG
Sales-Assisted → PLG + Sales-Assisted + ABM
Enterprise → Segment-based hybrid + ABM + CLG
Expansion-Focused → CS-led + upsell/cross-sell + referral

Sources Referenced¶

• HubSpot, The Flywheel (2018) — hubspot.com/flywheel
• Brian Dixon, The Flywheel Effect (2019)
• Winning by Design, The Bowtie Model & SPICED Framework (2021) — winningbydesign.com
• Reforge, GTM Archetypes (2022) — reforge.com
• Demandbase, ABM Playbook & Measurement Framework (2023) — demandbase.com
• ITSMA, ABM Leadership Survey (2022) — itsma.com
• Gartner, B2B Buying Journey Report (2022) — gartner.com
• Bombora, The State of Intent Data (2023) — bombora.com
• OpenView Partners, The PLG + SLG Playbook (2023) — openviewpartners.com
• Bessemer Venture Partners, PLG Market Map (2023) — bvp.com
• 6sense, ABM Measurement Framework (2023) — 6sense.com
• InsideSales.com, Lead Response Rate Study (pre-2020)
• SaaStr, Annual SaaS Research (2022–2024) — saastr.com

Last updated: 2026-06-24 | Author: carson | Type: source

Concepts¶

Extracted from this source: growth-flywheel · bowtie-model · account-based-marketing

Related concepts: net-revenue-retention · product-led-growth · gtm-archetype