Select a Market to see who’s leading and who’s moving.

Traditional SaaS Going Headless

Incumbent GTM SaaS founded before 2021. The market is named for a move about a third of it has made.

27.2%▼0.2pp
share of voice · 30d move
128 Scored · 199 Tracked

Coding Agents for GTM

General-purpose coding agents that GTM teams point at their own stack. The most uniform roster in the index, and the one absorbing work the other five used to sell.

16.1%▼0.5pp
share of voice · 30d move
23 Scored · 28 Tracked

AI-Native GTM Startups

AI-native GTM products and the agents that do the work. Built on LLMs, and mostly not callable by one.

10.7%▼0.3pp
share of voice · 30d move
68 Scored · 112 Tracked

GTM Developer Tools

The primitives GTM engineers build on: scraping, enrichment, memory, voice, deployment. Bought by a developer, not a buying committee.

16.1%▲4.5pp
share of voice · 30d move
115 Scored · 206 Tracked

Orchestrators & Agentic Workflow

The workflow spine, where GTM teams wire signals, enrichment and agents into something that runs without them. Clay owns four times the conversation of anyone else in it.

9.1%▼0.4pp
share of voice · 30d move
24 Scored · 33 Tracked

AEO-First Martech

Vendors selling visibility inside AI answers. Seven of the fifteen scored brands are SEO-era incumbents that repositioned.

2.9%▼1.6pp
share of voice · 30d move
15 Scored · 20 Tracked

GTM Report · Methodology

Intro

Hi, I'm Adam. I'm an independent builder & industry analyst. My goal is to help GTM leaders make sharp decisions in uncertain markets.

This is my methodology for the GTM Index — the score, the rankings, and the category maps. Three principles guide this work:

  1. Mindshare matters. We can gain an edge by understanding the conversations and perceptions within our market. This goes beyond reviews or narrow expert opinions.
  2. Curation is judgement. My judgement is encoded into this research system by curating the panel and coverage. That's what makes this different from vanilla Claude queries on GTM tech.
  3. Everything must update and evolve constantly. The traditional analyst model can't keep pace; this one runs continuously.

Coverage

I cover products and companies with a central application for B2B go-to-market in the AI era. Most are sales- or marketing-focused (e.g. Gong, Clay), but I also cover broader solutions that are clearly GTM-relevant (e.g. Claude Code, Vercel, Exa).

On the edges my judgement determines what fits (and what doesn't). Like all things, this evolves as I learn and as the market changes.

SOV Score

Your share of panel conversation, normalized 0–99 against the field.

That's the whole idea. It is a share-of-voice measure, not a rating: I am not scoring whether a product is good. I'm measuring how much of the GTM conversation it holds.

Here's how it works:

  1. Curated Panel. Over 3,500 sources I've hand-picked across social media, newsletters, blogs, and podcasts. Not a broad sample — the best minds in GTM: operators, authors, builders, executives.
  2. Tracking Mentions with Context. I track every product mention — and its context — across the panel.
  3. Engagement Weighted. Each mention is weighted by engagement and relevance (the factors vary by mention type). A product's own posts don't count — the score is earned voice only.
  4. Normalized 0–99. Every product sits on one scale, indexed to the loudest product in the window — that product scores 99 and everything else is placed against it. The index follows a power curve, not a straight line.

The two windows

Window What it answers
SOV Score Last 90 days Where does this brand stand right now?
30-day move Last 30 days vs the 30 before them Which direction is it heading?

Ninety days is long enough that one viral post doesn't decide a ranking, and short enough to still be about the present. Thirty days is where movement actually shows up — a longer movement window mostly reports slow drift.

Both are recalculated every night, against the panel as it stands that night. Scores as of 2026-07-25.

What the number is not

  • It is not a percentage. A SOV Score of 40 does not mean 40% of anything. It's a position on a 0–99 curve where 99 is whoever the panel talked about most in the window.
  • It is not linear. The curve compresses the top and spreads the bottom, so the gap between 90 and 95 represents far more conversation than the gap between 20 and 25. At the very bottom the scale is steep: roughly, SOV 9–11 is one earned mention over 90 days, 14–16 is two, 19–21 is five, 24–26 is nine.
  • It is not a quality rating. A product can be excellent and quiet. That shows up here as a low score, and that is the measure working, not failing.

What counts as a voice

A voice is a source on the curated panel — a person or a publication whose GTM commentary I've chosen to track, across LinkedIn, X, newsletters, blogs and podcasts. It is a hand-picked list, not a crawl of the internet, and that curation is the product. Three rules keep it honest:

  • Earned only. A brand's own accounts, and posts by its own staff, are identified and excluded. You cannot post your way up this index.
  • Weighted by engagement. A post nobody read counts for less than one the market argued about.
  • Context-checked. Common-word brand names ("Clay", "Air", "Enrich") are run through a context gate before a mention is credited, so an ordinary English sentence doesn't score for a vendor.

Markets, membership, and the ranking cutline

Brands sit inside Markets — the arenas they actually compete in. A Market is a curated call, not an algorithm.

Two different things can be true of a brand at once, and it matters which:

  • Membership is permanent. Once a brand belongs to a Market it keeps that Market, whatever its score does. Membership is about what the company is.
  • Ranking is dynamic. A brand is ranked once its SOV Score clears its Market's floor — currently SOV 15. Below that it keeps its Market and stays visible on the page, marked unranked.

One case sits outside both: a brand the panel didn't mention at all in the window has no score, so it isn't below the floor — there's nothing to be below. It keeps its Market and it's in the Index, but a Market page only shows brands the panel actually talked about. It reappears the moment it's mentioned again.

That split is deliberate. It means a quiet quarter doesn't erase a company from the Index, and a loud one doesn't require anybody to be manually let in. Entry and exit are just the score crossing a line.

The floor is set low on purpose, and it will move. Fifteen is roughly two earned mentions across 90 days — deliberately permissive, so I can look at the bottom of every Market and raise it with evidence rather than guess at it up front. It may end up different per Market: a specialist arena and a market with hundreds of players don't need the same bar. When it changes, it changes here first.

Separately, some products are scored but never ranked — see GTM Adjacent below. Those are broad platforms GTM teams run on rather than GTM tools competing for the same buyer; scoring them is useful for comparison ("Clay now out-mentions X"), ranking them is not.

Category Definitions

GTM Tech Types

My highest level organizing framework has a strong bend toward AI. I believe the traditional categorization is breaking down quickly. This is how I see the space at a high level:

TypeDefinitionExamples
Coding Agents & Experience BuildersAI coding assistants and app builders.Claude Code, Cursor, Lovable
OrchestrationThe workflow layer that wires data, agents, and apps into GTM systems.Clay, Zapier, n8n
Agent-Native GTMSoftware where agents are core and do the work — purpose-built for GTM jobs.11x, Artisan, Attio
GTM Developer ToolsThe API- and MCP-first primitives used to build and run agent-based GTM systems.Exa, Vercel, ElevenLabs
Traditional SaaS for GTMTraditional SaaS for sales and marketing, now going headless and shipping agents.Salesforce, HubSpot, Gong
Creative & ContentAI generation of media assets — images, video, decks, avatars, copy.Canva, Runway, HeyGen
AEOPlatforms that help brands measure & optimize visibility inside AI answers.Profound, Scrunch AI, AthenaHQ
GTM AdjacentBroad, general-purpose platforms a company runs on (comms, docs, cloud, data) — used by GTM but orthogonal to sales and marketing execution.Slack, Notion, Snowflake

GTM Tech Categories

Categories are generally organized around use cases, go-to-market motions, or the intersection of the two. That said, there is a balance of many factors in this framework and it ultimately comes down to my judgement.

CategoryDefinitionExamples
GTM Developer ToolsBroad dev primitives GTM teams run through agents and APIs.Exa, Vercel, Twilio
Data & IntelligenceEnrichment, intent, and signal data that feeds the pipeline.Clay, ZoomInfo, Apollo
SellingActive deal execution — conversation intelligence, coaching, proposals, demos.Gong, Salesforce, Granola
Marketing ExecutionCampaigns, content, ABM, and marketing ops.HubSpot, Klaviyo, Customer.io
AdvertisingPaid-media execution and measurement — DSPs, paid social and search, attribution.The Trade Desk, LiveRamp, Metadata
Creative & ContentAI generation of GTM media — video, images, decks, avatars, copy.Canva, Runway, HeyGen
GTM InfrastructureGTM-specific pipes — email deliverability, CDP and reverse-ETL, billing.Hightouch, Metronome, Paddle
Website & InboundWebsites, chat, and inbound capture that convert traffic into pipeline.Webflow, Chili Piper, Framer
AEOVisibility inside AI-generated answers.Profound, Scrunch AI, AthenaHQ
ProspectingOutbound — finding, qualifying, and reaching buyers.Outreach, Salesloft, Nooks
Customer SuccessPost-sale onboarding, retention, and expansion.Intercom (Fin), Gainsight, Zendesk
Autonomous CRMAI-native CRMs that run pipeline, deals, and relationships themselves.Attio, Day.ai, Clarify

Rules & Guidelines

Products can fit types and multiple categories, but there must be a strong case.

Agent Readiness Score

I score Agent Readiness as a secondary factor, but it matters: in an agent era, whether your systems can actually build on a product matters more than its UI. It's an analyst-judged 0–99 score (with an A–F grade) across four surfaces — API, MCP server, SDK, and CLI — plus the quality of the docs behind them. Multiple agents, each with a different persona, assess those surfaces and docs; the Surfaces column shows exactly which a product ships.

Feedback & Corrections

Send any suggestions or issues to adam at adamgtm.com. I verify them, write the fix back to the system and publish.

If you're building something interesting in this space, but it's not covered yet, please suggest a product here.

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