Make (formerly Integromat) is the automation platform we use most frequently at AIExecution. It's more powerful than Zapier for complex workflows, more accessible than n8n for non-technical teams, and dramatically more cost-effective at the volume that growing businesses typically run. If you're evaluating automation platforms, Make deserves serious consideration.
This guide covers everything a business owner needs to know: what Make actually is, how scenarios work, the pricing structure, the best use cases, the real limitations, and how to get started without wasting time.
What Make Actually Is
Make is a visual workflow automation platform. You build "scenarios" — sequences of connected modules, each representing an action inside a specific app or service. A trigger module watches for an event. Action modules do things in response. Router modules split the flow into branches. Filter modules determine which records proceed. Aggregator modules combine data from multiple records.
The visual editor shows you every module in your scenario laid out as a flowchart — you can see the entire logic at a glance, unlike Zapier's linear list view that gets unwieldy for complex workflows. This visual clarity is one of Make's biggest practical advantages when building and debugging.
Make connects to 1,500+ apps via pre-built integrations, and to any app with an HTTP API via its generic HTTP module. In practice, if a tool has an API, Make can talk to it.
How Make Scenarios Work
Every Make scenario has the same basic structure:
Trigger: The event that starts the scenario. Could be a webhook (fired instantly when something happens), a scheduled poll (Make checks a data source every X minutes), or an instant trigger (some apps push events to Make in real time). Webhooks are the fastest and most reliable — if your app supports them, use them.
Modules: Each module performs one action: read data from an app, create or update a record, send a message, transform data, make an HTTP request. Modules pass data to the next module in the chain — each module's output becomes available as input for everything downstream.
Routers and filters: Routers split the scenario into parallel paths. Filters determine whether a record meets a condition before proceeding. Together, they enable complex branching logic: if lead score is over 80, go to path A; if under 80, go to path B; if score is missing, go to path C (manual review).
Error handling: Make has proper error-handling routes — you can specify what happens when a module fails. Set up an error route that sends a Slack notification with the failed record details. Your team gets alerted to exceptions immediately without the whole scenario breaking.
Make Pricing: What You Actually Pay
Make charges per "operation" — each module execution counts as one operation. A 10-module scenario running 500 times per month = 5,000 operations.
- Free: 1,000 operations/month, 2 active scenarios. Good for testing, not production.
- Core ($9/month): 10,000 operations, unlimited scenarios, 5-minute minimum schedule interval. Covers simple workflows for small businesses.
- Pro ($16/month): 10,000 operations, 1-minute intervals, full-text execution log, custom variables. Best value for most SMBs.
- Teams ($29/month): 10,000 operations, team collaboration features, multiple users. Right for teams managing shared automation infrastructure.
- Enterprise (custom pricing): High operation volumes, priority support, SLAs.
Note: you can purchase additional operation bundles at any tier. The base plans are a starting point — most active businesses end up on Pro with 40,000–80,000 additional operations added monthly.
Best Use Cases for Make in a Growing Business
Lead intake automation. Typeform/Facebook Lead Ads → enrichment API call → HubSpot/GHL contact creation → lead scoring → Slack notification → email follow-up. Make handles all 8+ modules of this sequence cleanly, with error handling if enrichment fails.
Client onboarding. PandaDoc webhook (contract signed) → extract client data → create Asana project from template → send personalized email → create HubSpot deal → Slack notification to account team. The parallel paths (Asana + HubSpot + email simultaneously) are where Make shines vs. Zapier's linear structure.
Automated reporting. Scheduled scenario runs Monday 7:45am → pulls data from Shopify, Google Ads, Facebook APIs → writes to Google Sheets → generates summary via OpenAI API call → sends email with summary + dashboard link. This is a 15+ module scenario that Make handles comfortably.
Invoice and payment workflows. Stripe payment received → update HubSpot deal stage → create receipt PDF via PandaDoc → send to client → create accounting entry → notify bookkeeper. Clean and reliable — exactly the kind of well-defined, multi-step process Make was built for.
Real Limitations of Make
App library gaps. With 1,500+ integrations, Make covers most major tools — but Zapier's 6,000+ library is noticeably broader for niche tools. If you're running legacy or specialty software, check Make's app list first. The HTTP module can bridge most gaps, but requires more setup.
Learning curve for complex logic. Simple scenarios are intuitive. Scenarios with iterators, aggregators, and nested routers require real investment in understanding how Make processes data. Non-technical founders can get far on their own, but complex builds typically benefit from someone who has built Make scenarios before.
Not suitable for truly high-volume processing. At enterprise scale — millions of operations per month — Make's pricing and architecture may not be optimal. n8n self-hosted is the better choice at that volume.
If you want Make scenarios built for your specific business workflows — designed, built, tested, and documented — that's exactly what AIExecution delivers. Start with a free breakdown call to map which workflows we'd automate first.