Select a Market to see who’s leading and who’s moving. Brands are scored based on Share of Voice within a curated panel of GTM voices, across sources. This is not a measure of which product is “best.” Instead, it’s tracking which brands are generating the most buzz and who’s gaining mindshare the fastest. This alone won’t tell you what to buy, but it will help you stay informed and ahead of the GTM trends.
Traditional SaaS Going Headless
Incumbent GTM SaaS or established pre-AI. Racing to extend their platforms for agents and agent builders.
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AI-Native GTM Challengers
AI-native software and purpose-built agents for GTM tasks and jobs, built around LLMs. Racing to deliver outcomes.
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Coding Agents & Harnesses for GTM
The race for the center of the AI GTM stack. General-purpose coding agents, harnesses, and experience builders.
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Orchestrators & Agentic Workflow
Workflow that connects data, agents, and apps into GTM systems. Racing to own business logic and coordination.
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GTM Developer Tools
Tools & infrastructure used to build and run GTM agents. API, CLI, MCP first. Racing to own the new primitives.
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AEO-First Marketing Tech
Marketing platforms that believe AI search is the critical buyer discovery channel. Racing for AEO leadership.
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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:
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.
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:
| 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 2026-07-26.
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:
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:
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.
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.
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:
| Type | Definition | Examples |
|---|---|---|
| Coding Agents & Experience Builders | AI coding assistants and app builders. | Claude Code, Cursor, Lovable |
| Orchestration | The workflow layer that wires data, agents, and apps into GTM systems. | Clay, Zapier, n8n |
| Agent-Native GTM | Software where agents are core and do the work — purpose-built for GTM jobs. | 11x, Artisan, Attio |
| GTM Developer Tools | The API- and MCP-first primitives used to build and run agent-based GTM systems. | Exa, Vercel, ElevenLabs |
| Traditional SaaS for GTM | Traditional SaaS for sales and marketing, now going headless and shipping agents. | Salesforce, HubSpot, Gong |
| Creative & Content | AI generation of media assets — images, video, decks, avatars, copy. | Canva, Runway, HeyGen |
| AEO | Platforms that help brands measure & optimize visibility inside AI answers. | Profound, Scrunch AI, AthenaHQ |
| GTM Adjacent | Broad, general-purpose platforms a company runs on (comms, docs, cloud, data) — used by GTM but orthogonal to sales and marketing execution. | Slack, Notion, Snowflake |
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.
| Category | Definition | Examples |
|---|---|---|
| GTM Developer Tools | Broad dev primitives GTM teams run through agents and APIs. | Exa, Vercel, Twilio |
| Data & Intelligence | Enrichment, intent, and signal data that feeds the pipeline. | Clay, ZoomInfo, Apollo |
| Selling | Active deal execution — conversation intelligence, coaching, proposals, demos. | Gong, Salesforce, Granola |
| Marketing Execution | Campaigns, content, ABM, and marketing ops. | HubSpot, Klaviyo, Customer.io |
| Advertising | Paid-media execution and measurement — DSPs, paid social and search, attribution. | The Trade Desk, LiveRamp, Metadata |
| Creative & Content | AI generation of GTM media — video, images, decks, avatars, copy. | Canva, Runway, HeyGen |
| GTM Infrastructure | GTM-specific pipes — email deliverability, CDP and reverse-ETL, billing. | Hightouch, Metronome, Paddle |
| Website & Inbound | Websites, chat, and inbound capture that convert traffic into pipeline. | Webflow, Chili Piper, Framer |
| AEO | Visibility inside AI-generated answers. | Profound, Scrunch AI, AthenaHQ |
| Prospecting | Outbound — finding, qualifying, and reaching buyers. | Outreach, Salesloft, Nooks |
| Customer Success | Post-sale onboarding, retention, and expansion. | Intercom (Fin), Gainsight, Zendesk |
| Autonomous CRM | AI-native CRMs that run pipeline, deals, and relationships themselves. | Attio, Day.ai, Clarify |
Products can fit types and multiple categories, but there must be a strong case.
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.
Send any suggestions or issues to adam at adamgtm.com. I verify them, write the fix back to the system and publish.
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