GTM tools: the go-to-market stack by job, what each layer costs, and where agents fit

"GTM" here means go-to-market, not Google Tag Manager, which shares the acronym and half of the results page for this search. A go-to-market stack is the set of tools a sales, marketing and RevOps team uses to decide who to sell to, reach them, and keep a record of what happened.

Most lists of GTM tools on the first results page are written by a company that sells one and ranks it first. This one is too: Tulina runs sales and RevOps processes as AI agents across the tools below, and its section is clearly marked. The rest of the page is sorted by the job each tool does, because that is how a stack is actually built: one answer per job, and a clear idea of what moves the work from one job to the next.

What are GTM tools?

GTM tools are the software that carries a company's go-to-market motion: the data that says who might buy, the signals that say who might buy now, the tools that find a reachable person and an address, the sequencer that writes to them, the CRM that remembers every conversation, the layer that moves work between those, and the analytics that say what worked. A "GTM tool" is any one of those; a "GTM stack" is the set a team actually runs.

Two things the definition hides. Most tools do more than one job: Apollo is a database, an enrichment source and a sequencer; HubSpot is a CRM, a sequencer and an automation engine; Clay is enrichment and orchestration in one table. And the job that breaks most stacks is the one with no tool of its own: deciding, between two tools, whether a record should move at all. That is the orchestration row below, and it is where this page ends.

The GTM stack by job

Seven jobs, the tools teams pick for each, and how each one charges. Every row was read on the vendor's own pricing page on 29 October 2026, in the currency and billing period the page showed. "Quote" means the page prints no number.

The HubSpot note: HubSpot's live pricing page did not render its tier prices in text for us, and a search snippet of it showed discounted figures, so they are left out. What HubSpot's own knowledge base and pricing guide say is the part that decides a stack: sequences need Sales Hub Professional or Enterprise, and Starter's automation is described as triggering tasks and email notifications when a deal changes stage.

Three patterns run through the table. The data and signal layers sell on quote or on credits, so the cost moves with how many records you touch, not with how many people use them. The sequencing and CRM layers sell on seats. And the orchestration layer sells on runs, tasks or credits per step, which is why the same automation can cost ten times more on one tool than another: the n8n alternatives page works through that unit by unit.

Which GTM tools do companies actually use?

Salesforce and HubSpot, by a distance, then a long tail where the tools people write about are not the tools people hire for. We counted, with Tulina's TheirStack connector on 29 October 2026, how many US-headquartered companies in TheirStack's index have each tool detected in their job postings. The index held 689,569 US companies that day. A count is companies whose postings name the tool (a "Salesforce admin" opening, "experience with Outreach"), which is a proxy for use, not a customer list.

Read it as orders of magnitude, not as a ranking. Three things in it are worth knowing before you choose. The CRM is named five to ten times more often than any other layer, so the rest of the stack has to fit whichever CRM is already there. More US companies name n8n in their job postings than name Clay, which suggests the orchestration layer is built at least as often by people who write automations as by people who build tables. And the tools with the most written about them, Clay and Lemlist among them, are named by well under one percent of companies: a stack that looks standard on social media is not the standard one.

Two caveats from the source. TheirStack detects a technology from job posting text, so a company that uses a tool and never hires for it does not appear, and a posting that mentions a tool as a nice-to-have does. And the counts are per technology label: we used Apollo's apollo-io label rather than the bare apollo, which also matches other products of that name, and Clay's clay-run.

What are the top 10 GTM tools?

Of the sixteen tools we counted above, the ten named by the most US companies in their job postings on 29 October 2026 were Salesforce, HubSpot, Zapier, LinkedIn Sales Navigator, ZoomInfo, Outreach, Apollo, n8n, Salesloft and Gong. That is a list of what companies hire for, which is a public proxy for what they run.

A list of ten is the wrong unit for choosing, though. A small team needs one tool per job, and most of the ten overlap: Salesforce and HubSpot are both CRMs, Outreach, Salesloft and Apollo all sequence, and ZoomInfo, Apollo and Sales Navigator all answer "who works there". If Apollo is the one you are weighing, Apollo alternatives sorts its rivals by the job you use it for. The useful question is which job is unanswered in your stack today, and the table in the previous section is sorted that way.

What are the best AI GTM tools?

There are two kinds, and the difference matters more than the brand. The first is AI inside one tool: a research agent that fills a column of an enrichment table, AI-written steps in a sequencer, summaries of a recorded call. Each makes its own job faster and stays inside its own tool's data. The second is an agent that works across tools: it reads the CRM, calls the enrichment provider, checks the sequencer, and writes back, deciding at each step whether the record should move. Lindy (Team plan $29.99 a month with 3,000 credits) and Gumloop (Pro from $37 a month, plus an 8% "orchestration fee" on its page) are general agent builders; n8n and Zapier have added AI steps to their graphs; Tulina runs sales and RevOps processes as agents on a schedule or a webhook.

Which kind you need depends on where the time goes. If one tool is slow, buy the AI inside it. If the time goes into moving records between tools and deciding what to do with each, which is what most RevOps work actually is, the AI inside a single tool cannot see the other tools, and that is the case for an agent. The GTM engineering article covers the people who build that layer, and AI GTM from Claude shows each stage of the motion run from a Claude chat, and which ones have to move to a scheduled agent.

Are GTM tools the same as RevOps tools?

Mostly the same software, owned for a different job. GTM tools are named by what they help a team do to the market: find, reach, close. RevOps tools are the same CRM, sequencer and enrichment tools seen from the operations side, plus the layer that keeps them true: forecasting (Clari, for one), routing, territory and commission tools, and the data hygiene that stops two records describing one company. A RevOps team owns the stack; a go-to-market team uses it.

In practice the overlap is the CRM and the orchestration row. A RevOps lead choosing tools is choosing the same data, CRM and automation layers as this page, and then adding the reporting that says whether the pipeline is real. The job RevOps most often automates first is the clean-up: CRM hygiene and prospect job changes is that job as a process.

How do you build a GTM stack yourself?

Start from the CRM you already have and add one job at a time, each only when the previous one is producing work the next one can use. This is the order that keeps the bills small and the data clean, and it works with any of the tools above.

1. Write the ideal customer profile in one paragraph. Industry, size, the tool or event that makes a company a buyer, and the roles you sell to. Every later choice is checked against it.
2. Keep the CRM you have. Moving CRM is a quarter of work and rarely the bottleneck. Clean it first: one record per company, by domain, and every open deal with an owner.
3. Add one data source. A free plan (Apollo's, Attio's, HubSpot's free tools) is enough to learn which fields you actually use.
4. Add signals before you add volume. A list of companies that started hiring for the role you sell to, or adopted a tool you plug into, beats a list ten times longer with no reason to write now. TheirStack sells this by the company credit; Common Room and 6sense sell it by the platform.
5. Enrich only what passed the checks. Find emails and phones for the companies that fit and are not already customers or open deals. A waterfall across two or three providers finds more than one provider alone, and the Clay pricing article shows what that costs per contact.
6. Pick one sequencer and keep it paused until a person reads the first batch. Lemlist, Outreach, Salesloft and Apollo all do the job; the choice is mostly whether LinkedIn steps and the price per seat matter to you.
7. Wire the hand-offs last. Only now is it clear which moves repeat: the new signal into the list, the list into enrichment, the enriched contact into the sequencer, the reply into the CRM. Each one is a Zap, an n8n flow, a Clay table or an agent run, and each needs a rule for when the record should not move.
8. Measure one number per job. Fit rate for data, reply rate for sequencing, meetings per hundred contacts for the whole stack. A tool whose number you cannot read is the first one to cut.

How do you run work across your GTM tools with Claude or ChatGPT?

With Tulina, Claude or ChatGPT runs one job end to end across the layers above: it reads the signal source, scores each company on your profile, checks the CRM and the sequencer before anything is bought, enriches the people who are left, and adds them to a paused campaign, on a schedule or a webhook and with nobody in the chat. Every step, every tool call and its cost is in the run's trace. A person still writes the profile and the rules, and decides when the campaign sends.

Each step below is one row of the stack table: signals, judgment, CRM, data, enrichment, sequencing, and the chat channel for the recap. Once TheirStack, Apollo, Jev, HubSpot, FullEnrich, Lemlist and Slack are connected, paste this into Claude or ChatGPT:

Run one pass of my GTM stack for yesterday's signals. Send nothing:
the Lemlist campaign stays paused.

1. Signals (TheirStack): companies in [our countries] that opened a
   job posting for [the role that means they need us] or started
   using [a tool we plug into] yesterday. Keep a tool detection only
   when two postings back it.
2. Judgment (Jev): score each company on our profile, [one paragraph
   ICP], as fit yes or no with a probability. Keep above 0.8, park
   below 0.4, and list the middle band for me with the reason.
3. CRM (HubSpot): drop every company that is a customer or has an
   open deal, by domain. Post the open-deal ones to the owner in
   Slack, one line each.
4. Data (Apollo): for each company left, find up to two people with
   [our buyer titles], matched by domain.
5. Enrichment (FullEnrich): work emails only, for the people Apollo
   returned without one, as one batch.
6. Sequencing (Lemlist): skip anyone already in a campaign in our
   workspace. Add the rest to campaign [id] with a two-sentence
   opener that starts from the signal and asks one question.
7. Recap (Slack): companies read, kept, parked, dropped by the CRM,
   people added, and what each paid step cost.

The process behind that prompt, with every step and the tools it uses:

The process in Tulina

Outbound from buying signals

Trigger · Schedule

Daily schedule

Each morning the run opens on the signals of the day before, so a company that adopted the tool you plug into on Tuesday is in sequence on Wednesday.

Claude runs the rest autonomously

1. 1

   AI builds the universe on stack and hiring.

   TheirStack

   TheirStack

   Companies that started running the tools you plug into, backed by more than one posting, and companies hiring for the pain you solve come back as one list with the detections behind it.

   Apollo.io

   Apollo.io

2. 2

   AI scores on your rubric.

   Jev

   Jev

   Every company is scored on your profile written as closed questions, with a probability next to each answer, and the middle band goes to a person instead of a label.

3. 3

   AI drops what the CRM or a sequence holds.

   HubSpot

   HubSpot

   A customer, an open deal, another rep's claim, a company inside the cool-off or a person already in any sequence leaves the list with its reason, before anything is bought.

   Lemlist

   Lemlist

4. 4

   AI reads why now, matches the buyer.

   TheirStack

   TheirStack

   Each company's postings and news come back as signals with the exact sentence behind them, and the signal names which of your buyer roles to write to.

   Serper

   Serper

5. 5

   AI finds the buyers, enriches their emails.

   Apollo.io

   Apollo.io

   Two people per company come back with a verified work email, false affiliations purged, and anyone already in a sequence stopped.

   FullEnrich

   FullEnrich

6. 6

   AI picks the play, writes each opener.

   Your outbound playbook decides how many people to write to and in what order, and one opener per person is written from the signal, with only citable figures.

7. 7

   AI fills the campaign, updates the CRM.

   Lemlist

   Lemlist

   Everyone with an email joins the paused campaign with their opener, each company gets one note with its signal and score, and the team gets the recap with every company that stopped and why.

   HubSpot

   HubSpot

   Slack

   Slack

See the full process

The order is the point. In a stack wired with one Zap per hand-off, the CRM check is a separate automation someone has to remember to build, and enrichment usually runs before it, so the team pays to enrich its own customers. In the run above, the CRM is step 3 and the first paid lookup is step 4: a company the CRM already knows costs nothing further. For the outbound loop in full, including the claims table that stops two reps writing to the same account, see Outbound from buying signals.

What a GTM stack can't fix

• A vague customer profile. Every tool above sorts by the fields you give it. A stack built before the profile is written finds more of the wrong companies faster.
• Data the vendors do not have. Coverage differs by country and by company size; a database strong on US software companies can be thin on European manufacturers. Test on fifty of your own accounts before you sign for a year.
• Two systems of record. When the CRM, the sequencer and a Clay table each hold their own copy of a contact, they disagree within a month. Pick the CRM as the record and make every other tool write back to it.
• Sending rules. Email and LinkedIn limits apply to the sender, whatever the tool. The LinkedIn automation tools page covers pacing; for email, deliverability is a domain and volume question no sequencer removes.
• The price you will actually pay. Half the vendors in the table print no number, and the rest bill per credit, per action or per seat. Price a stack by the month you expect to run, with the records and the steps counted, not by the entry plan.

How many GTM tools does a small team need?

Four to start: a CRM, one data source, one sequencer, and one way to move work between them. Signals and dedicated enrichment come next, when the list is the bottleneck rather than the writing. Analytics and conversation intelligence come when there are enough calls and deals for patterns to exist. Several tools on the table cover two jobs, so a five-person team can run the whole loop on three subscriptions: for example a CRM with a free tier, Apollo for data and sequencing, and an orchestration layer for the hand-offs.

Are there free GTM tools?

Yes, for every job except signals at volume. The free plans we read on 29 October 2026: Apollo's Starter plan, which "stays free with no time limit"; Salesforce's Free Suite and Attio's free plan for up to three seats; Clay's free plan with 500 actions a month and 200 rows a table; Zapier's free plan for 100 tasks a month; Make's free plan with 1,000 credits a month; n8n's self-hosted Community Edition; and Granola's free plan for call notes. Free plans are enough to learn which fields and steps you use. They are rarely enough to run a team on, and the step that runs out first is usually enrichment credits.

For what to automate in the sales process once the stack exists, and which tools do it with rules alone, see sales automation tools.