n8n vs Make: Which Automation Tool Is Right for Your GTM Team in 2026?

Choosing between n8n and Make is one of the most common automation decisions GTM teams face in 2026. Both platforms connect your apps, trigger actions, and eliminate manual work. But they're built for different types of teams, and picking the wrong one will cost you time or money.

This guide breaks down the real differences so you can make the right call for your stack.

The Short Answer

Choose Make if your team is non-technical or marketing-led and needs fast, visual workflow setup with minimal infrastructure overhead.

Choose n8n if you have a GTM engineer or technical founder on the team, run high-volume automations, or need native AI agent capabilities baked into your workflows.

Neither tool is objectively better. The right choice depends on your team's skills, your workflow volume, and how much you care about data ownership.

What These Tools Actually Do

Both n8n and Make are workflow automation platforms. They let you connect apps, pass data between them, and trigger actions automatically based on conditions you define.

The use cases for GTM teams are nearly identical:

• Route inbound leads from your website to your CRM
• Sync contact enrichment data from Clay into HubSpot
• Trigger Slack alerts when a high-value prospect visits your pricing page
• Push new signups into an onboarding email sequence
• Auto-generate weekly pipeline reports from CRM data

Where they differ is in philosophy, pricing model, and technical requirements.

Platform Overview

Make

Make (formerly Integromat) is a cloud-based visual automation builder. You create "scenarios" by dragging and dropping modules on a canvas. Each module represents an action. Data flows between them visually.

Make has 3,000+ native integrations. It covers virtually every mainstream GTM tool: HubSpot, Salesforce, Apollo, Instantly, Slack, Google Workspace, and more. It requires no servers, no setup, and no code. You log in and start building.

The trade-off is pricing. Make charges per operation, meaning every step in a workflow consumes a credit. A 10-step workflow running 1,000 times per month consumes 10,000 operations. Costs can escalate fast as your workflows grow complex.

Make pricing (annual billing, March 2026):

• Free: 1,000 operations/month
• Core: $9/month for 10,000 operations
• Pro: $16/month for 10,000 operations with advanced features
• Enterprise: Custom

n8n

n8n is an open-source, fair-code automation platform. It supports self-hosting, custom JavaScript and Python code execution in any node, and 70+ native AI agent nodes including native LangChain integration.

In October 2025, n8n raised $180 million in a Series C led by Accel, with NVIDIA's venture arm (NVentures) participating. The round valued the company at $2.5 billion. n8n reported 6x user growth and 10x revenue growth in 2025, and now has over 3,000 enterprise clients including Vodafone and SoftBank.

More than 80% of workflows built on n8n now embed AI agents. That number explains why technical GTM teams are adopting it at pace.

n8n charges per workflow execution, not per step. A 10-step workflow running 1,000 times costs 1,000 executions, not 10,000. For complex, high-volume automations, that difference is significant.

n8n pricing (annual billing, March 2026):

• Self-hosted: Free (pay only for infrastructure, typically $6-15/month for a VPS)
• Cloud Starter: €20/month for 2,500 executions
• Cloud Pro: €50/month for 10,000 executions
• Enterprise: Custom

Head-to-Head Comparison

Ease of Use

Make wins here. Its drag-and-drop canvas is intuitive. A marketing ops manager with no technical background can build a functional lead routing workflow in under an hour.

n8n has a steeper learning curve. It assumes some technical fluency. Expressions for transforming data require familiarity with JavaScript syntax. Non-technical users can use it, but they'll move slower and hit more friction.

Make: Low to moderate learning curve. Ready in hours. n8n: Moderate to steep. Best with a technical operator.

Integrations

Make has 3,000+ native integrations. n8n has 400+ native nodes, but the community library extends this to 1,100+.

For most GTM stacks, both tools cover what you need. HubSpot, Salesforce, Slack, Gmail, Apollo, Clay, and every major SaaS tool are available on both platforms.

Where Make has an edge is breadth. Where n8n has an edge is depth. n8n's API-level control lets you build custom integrations without waiting for a native connector.

Make: 3,000+ integrations. Better for less common SaaS tools. n8n: 400+ native, 1,100+ with community. Better for custom API connections.

AI Capabilities

This is where n8n pulls ahead decisively in 2026.

n8n has 70+ native AI nodes. It integrates natively with LangChain, OpenAI, Anthropic, Ollama, and Google Gemini. You can build multi-step AI agents that reason, call tools, loop based on output, and route decisions without writing a separate AI application. This is production-grade AI orchestration, not a bolted-on feature.

Make has added AI capabilities, including integrations with OpenAI and Anthropic. But they require external modules and don't match n8n's native depth. For teams building AI-powered GTM workflows, this gap is material.

n8n: 70+ AI nodes, LangChain native, purpose-built for AI agents. Make: OpenAI/Anthropic modules available, but limited native depth.

Pricing at Scale

At low volumes, Make is cheaper. At high volumes, n8n wins, especially self-hosted.

Here's a real-world example from RunTheNumbers (March 2026): a 10-step workflow running 1,000 times per month:

• Zapier: 10,000 tasks consumed (mid-tier plan required)
• Make: 10,000 operations consumed ($29/month tier)
• n8n: 1,000 executions consumed (€20/month Cloud Starter)
• n8n self-hosted: effectively free beyond $6-15/month VPS cost

At higher volumes, self-hosted n8n saves thousands per month versus Make or Zapier. One agency reported saving $2,400/month switching from Zapier to self-hosted n8n for the same 15 workflows.

Make: Cheaper at low volume. Costs escalate with complex, looping workflows. n8n: Cheaper at scale. Self-hosted option is dramatically more cost-effective.

Security and Compliance

Make is cloud-only. It carries SOC 2 Type II and ISO 27001 certification. Enterprise-grade security is built in. You don't manage anything.

n8n self-hosted puts data entirely on your infrastructure. That's a major advantage for GDPR-sensitive workflows, regulated industries, or teams with strict data residency requirements. The cloud version carries SOC 2 Type II certification.

The practical implication: if your GTM workflows process sensitive contact data or operate under strict compliance requirements, self-hosted n8n gives you full control. Make's cloud model may not satisfy those requirements.

Make: SOC 2, ISO 27001, fully managed. Good enterprise security baseline. n8n: Full data sovereignty via self-hosting. Cloud version SOC 2 certified.

Common GTM Workflows: Which Tool Is Better?

Lead Routing and CRM Sync

Both tools handle this well. A form submission triggers the workflow, enriches the contact via API, scores the lead, and pushes it to HubSpot or Salesforce.

Make is faster to set up. n8n gives more control over the enrichment logic, especially if you want to run conditional branching based on AI-evaluated signals.

Winner: Make for speed. n8n for complex conditional logic.

Clay Enrichment to Sequencer Push

Pulling enriched accounts from Clay and pushing them into an email sequencer (Instantly, Smartlead) is a core GTM workflow. Both platforms support this via API.

n8n's code node lets you transform and filter data in bulk without burning credits per row. In Make, iterating over 1,000 rows consumes 1,000 operations minimum.

Winner: n8n for bulk data processing.

AI-Powered Lead Qualification

This is where n8n's advantage is clearest. You can build a workflow that: receives a new lead, pulls enrichment data, sends it to an LLM for ICP scoring, branches based on the score, and routes accordingly. All natively, in one workflow.

In Make, you'd need multiple external API calls stitched together. It's possible but messier.

Winner: n8n for AI-native qualification logic.

CRM-to-Slack Alerts

Simple trigger-and-action workflows where Make excels. New deal stage in HubSpot triggers a Slack message. Fast to set up, no code needed.

Winner: Make for simple, fast setup.

Which Tool Should You Choose?

Pre-Seed and Seed Startups

Start with Make. You probably don't have a GTM engineer yet. You need automation fast without infrastructure overhead. Make's visual builder gets you to working workflows in hours. The free tier and $9/month Core plan cover most early-stage needs.

Tool of choice: Make (Core plan, $9/month)

Series A Startups

You likely have a GTM engineer or RevOps hire. Workflow volume is growing. AI-powered qualification and enrichment automation are priorities.

This is the inflection point. Evaluate whether your current Make costs are climbing. If you're processing high lead volumes or running complex looping workflows, n8n cloud or self-hosted starts making financial sense.

Tool of choice: n8n Cloud (€20-50/month) or Make Pro ($16/month) depending on volume and team skills.

Series B and Beyond

At this stage, self-hosted n8n is almost always the right call if you have technical resources. The cost savings at scale are substantial. The AI orchestration capabilities support more sophisticated GTM workflows. And full data control matters more as your compliance requirements grow.

Tool of choice: Self-hosted n8n (infrastructure cost only, $6-15/month)

The Case for Running Both

Many GTM teams run Make and n8n in parallel. Make handles simple, fast automations across a broad tool set. n8n handles complex, high-volume, and AI-driven workflows.

The overhead of managing two platforms is low. The benefit is using each tool where it genuinely excels.

This isn't a forced recommendation. But if you're at Series A with an engineering resource available, the hybrid approach often beats committing fully to either platform.

Where Miniloop Fits

Whichever automation platform you choose, the content and signal layer above it matters. Miniloop connects your GTM automations to your content engine, helping you convert inbound traffic and automate follow-up sequences based on behavioural signals.

If you're using n8n or Make to route leads and trigger outbound sequences, Miniloop gives you the content infrastructure that makes those automations land with context. Your AI SDR's outreach performs better when prospects have already consumed relevant content before the first touch.

Quick Comparison Table

TL;DR

• Make is better for non-technical teams that need fast setup and visual workflows with minimal infrastructure.
• n8n is better for technical teams, high-volume automations, AI-native workflows, and teams with data sovereignty requirements.
• At low volume, Make is often cheaper. At scale, self-hosted n8n wins on cost by a wide margin.
• n8n raised $180M at a $2.5B valuation in October 2025 and now has 70+ AI nodes, making it the leading choice for AI-powered GTM automation.
• Pre-seed: start with Make. Series A+: evaluate n8n. Series B+: self-host n8n if you have the resources.
• Many teams run both in parallel.

Related reading: GTM Automation for Small Teams | The Lean Startup AI Tool Stack | How to Automate Lead Qualification | Clay vs Apollo for B2B Prospecting | Outbound Sales Automation | Best AI SDR Tools 2026 | Signal-Based Outreach