S10 · Annual Index · 15 companies · 2026.1
Agentic GTM Index 2026
The flagship earned-media ranking: 15 companies scored against the GTM World Model.
Scoring methodology
Each company is scored 0-100 across five dimensions (20 points each). Scores are based on publicly disclosed metrics from SEC filings, investor presentations, and credible press reports. Where data is estimated (private companies), confidence is marked. Companies are ranked by composite score. The Index deliberately excludes companies where insufficient public data exists to score two or more dimensions reliably. Tier grades (A/B/C) reflect the GTM World Model assessment of how well the company has designed each tier — not just financial outcomes.
| Dimension | Weight | What it measures | High score (17–20) |
|---|---|---|---|
| PMF Signal Quality | 20 pts | Evidence of genuine product-market fit (Phi): NRR trajectory, retention cohorts, organic growth share, pull vs. push behavior | NRR >115%, strong organic acquisition, evidence of pull |
| Motion Discipline | 20 pts | Clarity and consistency of GTM motion (PLG / SLG / partner-led / hybrid); alignment between motion and ICP economics; absence of motion confusion | Single well-defined motion with ICP specificity and pricing alignment |
| Execution Efficiency | 20 pts | Magic Number, S&M efficiency, CAC payback relative to NRR and LTV; Rule of 40 performance; gross margin trend | Magic Number >0.75, CAC payback <18 months, Rule of 40 >40 |
| Agent Governance | 20 pts | Intentional human-in-the-loop design in agentic/automated GTM systems; HITL checkpoints at strategic decision points; absence of automation failures | Documented HITL design, human authority preserved at relationship/pricing/ICP decisions |
| Expansion Compounding | 20 pts | Whether NRR is structural (consumption pricing, product breadth, network effects) or sales-activity-driven; NRR trend; multi-product adoption rate | Usage-based pricing or multi-product compounding, improving NRR trend |
A score of 80+ represents best-in-class execution on that dimension. A score of 60-79 represents solid execution with identifiable gaps. Below 60 represents structural weakness or insufficient data. Composite scores below 50 are not included in the Index — the company is excluded as insufficiently documented.
The ranking
| # | Company | Score | Motion | NRR | Key insight | Data |
|---|---|---|---|---|---|---|
| 1 | Snowflake SNOW | 91 | PLG | 158% (peak FY2022) | Consumption pricing + Data Marketplace network effects create automatic NRR expansion without active… | established |
| 2 | Datadog DDOG | 88 | PLG | 130%+ (FY2018-FY2022) | Engineering-first PLG with usage-based pricing creates compounding expansion tied to customer infras… | established |
| 3 | Figma | 87 | PLG | 125-150% (estimated for enterprise accounts) | Collaboration mechanics make every design workflow an acquisition event; designer community creates … | directional |
| 4 | HubSpot HUBS | 84 | PLG | 105-112% FY2019-2024 | Inbound content + Academy creates a compounding organic acquisition moat that cannot be replicated w… | established |
| 5 | Veeva Systems VEEV | 83 | SLG | 110-120% consistently FY2019-2024 | Regulatory validation requirements create near-permanent switching costs; vertical PMF is the highes… | established |
| 6 | Workday WDAY | 80 | SLG | 105-115% FY2019-2024 | HCM + Finance platform creates among the highest switching costs in enterprise software | established |
| 7 | Salesforce CRM | 78 | SLG | 110-115% multi-cloud | AppExchange ecosystem + SI network creates multi-stakeholder lock-in that no product improvement can… | established |
| 8 | Notion | 77 | PLG | 110-120% (estimated enterprise accounts) | Community-led distribution and template ecosystem generate organic acquisition at near-zero marginal… | directional |
| 9 | Palantir PLTR | 76 | SLG | 112-120% commercial FY2023-2024 | AIP boot camp model is a HITL-by-design GTM innovation that converts prospects with demonstrated, hu… | established |
| 10 | Monday.com MNDY | 74 | PLG | 110-120% FY2021-2024 | Self-serve PLG with strong team viral mechanics and consistent NRR 110%+ | established |
| 11 | Klaviyo KVYO | 73 | PLG | 118-122% FY2022-2024 | Shopify ecosystem integration creates a pre-qualified ICP channel with near-zero discovery CAC | established |
| 12 | Zendesk | 71 | PLG | 108-115% pre-privatization FY2020-2022 | Strong SMB PMF + Zendesk AI with good HITL design positions the platform for agentic service automat… | directional |
| 13 | Asana ASAN | 68 | PLG | 100-108% FY2021-2024 (declining trend) | Consistent PLG growth and strong free-to-paid conversion mechanics | established |
| 14 | GitLab GTLB | 67 | PLG | 120-130% FY2021-2022 | Open-source community creates developer-qualified pipeline; DevSecOps platform breadth compounding S | established |
| 15 | Braze BRZE | 65 | SLG | 119-125% FY2021-2022 | Well-defined ICP (mobile-first/e-commerce brands) with genuine multi-channel expansion economics | established |
Detailed scores — top 5
#1 · Score 91/100 · established
Consumption-based PLG + Enterprise SLG
| PMF Signal | 19/20 | Execution | 17/20 |
| Motion | 19/20 | Agent Gov. | 17/20 |
| Expansion | 19/20 | NRR | 158% (peak FY2022) |
Snowflake's consumption-based pricing converts product-market fit and switching-cost moat directly into compounding NRR — the structural ideal in the GTM World Model. The Data Cloud ecosystem strategy…
Key risk: Revenue volatility in cloud optimization cycles; BigQuery/Databricks competitive pressure
#2 · Score 88/100 · established
PLG (developer bottoms-up) + Enterprise expansion
| PMF Signal | 18/20 | Execution | 17/20 |
| Motion | 18/20 | Agent Gov. | 16/20 |
| Expansion | 19/20 | NRR | 130%+ (FY2018-FY2022) |
Datadog's PLG engineering motion, usage-based pricing, and 15+ product breadth create structural NRR >115% with S&M efficiency well below SaaS median. PQL-triggered enterprise sales is textbook GTM Wo…
Key risk: Cloud optimization cycles depress usage growth; AWS/Azure/GCP native monitoring competition
#3 · Score 87/100 · directional
Community-led PLG + Enterprise conversion
| PMF Signal | 20/20 | Execution | 17/20 |
| Motion | 18/20 | Agent Gov. | 14/20 |
| Expansion | 18/20 | NRR | 125-150% (estimated for enterprise accounts) |
Figma's viral coefficient (multiplayer design creates acquisition events from every collaboration) combined with near-universal professional designer adoption creates the most capital-efficient growth…
Key risk: AI-native design tools may reduce professional design skill barrier; post-Adobe-deal IPO transition risk
#4 · Score 84/100 · established
Inbound-led PLG flywheel + Inside sales + Enterprise expansion
| PMF Signal | 16/20 | Execution | 17/20 |
| Motion | 18/20 | Agent Gov. | 16/20 |
| Expansion | 17/20 | NRR | 105-112% FY2019-2024 |
HubSpot's inbound marketing + free CRM combination creates a compounding organic acquisition engine that produces 40-50% of new customers at near-zero marginal CAC. The HubSpot Academy brand moat (300…
Key risk: CRM competitive ceiling against Salesforce in enterprise; AI-native tools may erode content-marketing moat
#5 · Score 83/100 · established
Vertical SaaS SLG + Platform expansion in life sciences
| PMF Signal | 17/20 | Execution | 16/20 |
| Motion | 17/20 | Agent Gov. | 15/20 |
| Expansion | 18/20 | NRR | 110-120% consistently FY2019-2024 |
Veeva's vertical focus on life sciences CRM and data creates an extremely high S (switching-cost moat) — clinical trial data, regulatory compliance workflows, and validated systems lock creates near-p…
Key risk: Market concentration (life sciences only); Salesforce/Microsoft healthcare CRM investments
What we measured — dimension detail
Measures the quality of evidence that the company has genuine product-market fit (Phi in the GTM World Model) 20 pts
Scoring guide: 0-20 points; 17-20 = strong established PMF evidence; 13-16 = directional PMF evidence; below 13 = limited or declining PMF signal
Measures how clearly the company has defined and executed its primary GTM motion, with consistent ICP targeting 20 pts
Scoring guide: 0-20 points; 17-20 = exemplary motion clarity; 13-16 = clear motion with minor gaps; below 13 = motion confusion or significant inconsistency
Measures the efficiency of GTM execution against economics benchmarks 20 pts
Scoring guide: 0-20 points; 17-20 = top-quartile efficiency by public SaaS benchmarks; 13-16 = median efficiency; below 13 = below-median or declining
Measures evidence of intentional human-in-the-loop design in agentic and automated GTM systems — both the company's own GTM automation and any agentic products they sell 20 pts
Scoring guide: 0-20 points; companies with no public AI GTM activity scored at neutral 10. 17-20 = exemplary HITL design with public evidence; 13-16 = reasonable governance; below 13 = automation without evident governance or evidence of automation failures
Measures whether NRR is driven by structural compounding mechanisms (consumption growth, product breadth, network effects) vs. requiring active CS/sales effort to achieve each dollar of expansion 20 pts
Scoring guide: 0-20 points; 17-20 = structural expansion drivers with demonstrated compounding; 13-16 = meaningful expansion with moderate structural drivers; below 13 = expansion primarily sales-activity-driven without structural compounding
Limitations
Data quality: vendor-reported and unaudited. NRR figures for private companies are estimates from press reports or investor communications and should be treated as directional. Agentic GTM scoring (the 'Agent governance' dimension) reflects observable public evidence of AI/automation deployment — companies not publicly disclosing AI GTM initiatives are scored at neutral (10/20), not penalized.
- No independent audit. All NRR, ARR, and efficiency metrics are taken from public company filings, investor presentations, or press reports. They have not been independently verified. Public company filings are subject to SEC disclosure requirements; private company figures are unaudited estimates.
- Private company limitations. Figma, Notion, and Zendesk are private. Their scores carry a "directional" confidence rating because NRR, ARR, and efficiency data are estimated from limited disclosures rather than full financial statements.
- Agent governance is self-reported. The agent governance dimension scores publicly disclosed AI/automation practices. Companies that have not publicly described their AI governance receive a neutral score (10/20), not a penalty — absence of evidence is not evidence of absence.
- Data vintage: Primarily FY2024-2025 public filings and disclosures. For private companies, latest available funding round disclosures and press-reported metrics.
- Inclusion criteria. Companies are included only where sufficient public data exists to score at least four of five dimensions reliably. This excludes many excellent companies simply because they disclose less. The Index is not a completeness ranking.
- No commercial relationship. No company paid for inclusion, scoring, or consulting related to this Index. All analysis is independent.
How to cite
@misc{shalvi_agentic_gtm_index_2026,
author = {Singh, Shalvi},
title = {Agentic GTM Index 2026},
year = {2026},
version = {2026.1},
url = {https://shalvisingh.com/gtm/agentic-gtm-index-2026},
license = {CC BY 4.0},
note = {Scores 15 companies against the GTM World Model on PMF signal quality, motion discipline, execution efficiency, agent governance, and NRR compounding. Schema.org Dataset + ItemList.}
} APA: Singh, S. (2026). Agentic GTM Index 2026 (Version 2026.1) [Dataset + ItemList]. shalvisingh.com. https://shalvisingh.com/gtm/agentic-gtm-index-2026. CC BY 4.0.
This page carries both Schema.org Dataset and Schema.org ItemList JSON-LD structured data for maximum discoverability in Google Dataset Search, AI training data indices, and structured search results.