Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Let me tell you about the day my client's entire automation system crashed, leaving them unable to process new deals for 6 hours. This wasn't some technical disaster or server outage—it was a single Make.com scenario hitting an error and taking down their entire lead-to-customer workflow.
This B2B startup had built their entire operation around what looked like a simple automation: when a deal closes in HubSpot, automatically create a Slack group for the project. On paper, Make.com seemed perfect for this. The pricing was budget-friendly, the interface looked powerful, and the tutorials made it seem bulletproof.
But here's what those tutorials don't tell you: when Make hits an error in execution, it doesn't just skip that task—it stops everything. For a growing startup processing dozens of deals per month, that's not just inconvenient; it's business-breaking.
After testing the same workflow across Make.com, N8N, and Zapier for real client projects, I learned the hard truth about automation platform limits. The choice isn't just about features or pricing—it's about understanding the hidden constraints that can kill your business processes when you least expect it.
Here's what you'll discover from my hands-on testing:
Why Make's error handling can break entire workflows (and how to work around it)
The hidden execution limits that aren't mentioned in the pricing pages
When Make's "unlimited" operations actually hit walls
Real scenarios where I had to migrate clients away from Make
My framework for choosing the right automation platform based on your actual constraints
Platform Limits
What Make.com promises vs what you actually get
Every automation platform markets itself as the solution to all your workflow problems. Make.com is no exception. Their marketing emphasizes unlimited scenarios, powerful integrations, and enterprise-grade reliability. The sales pitch sounds compelling:
The Standard Make.com Promise:
"Unlimited" scenarios for complex automation
Visual flow builder that anyone can use
Robust error handling and retry mechanisms
Cost-effective alternative to Zapier
Enterprise-ready scalability
This conventional wisdom exists because Make genuinely offers powerful features at attractive price points. For simple, linear workflows, it often delivers exactly what it promises. The visual interface is intuitive, and the integration library is comprehensive.
But here's where the industry advice falls short: most guides focus on what Make can do, not what happens when things go wrong. They showcase successful scenarios without addressing the failure modes that can paralyze your business operations.
The reality is that every automation platform has constraints—hidden limits that only surface when you're running mission-critical workflows at scale. Make's limitations aren't necessarily worse than competitors, but they manifest in specific ways that can be particularly problematic for growing businesses that depend on reliable automation.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When I started working with this B2B startup, the brief seemed straightforward: revamp their website and streamline their operations. But as I dove deeper into their workflow, I discovered a critical bottleneck that most businesses overlook.
Every time they closed a deal, someone had to manually create a Slack group for the project. It sounds like a small task, but when you're processing dozens of deals per month, those manual touchpoints add up to hours of repetitive work. More importantly, delays in project setup meant slower client onboarding and frustrated team members.
I initially chose Make.com for one simple reason: pricing. At $9/month for their Core plan versus Zapier's $19.99, the math seemed obvious for a budget-conscious startup. The automation itself was straightforward—monitor HubSpot for closed deals, extract the relevant data, and automatically create a properly named Slack group with the right team members.
The initial setup worked beautifully. The visual flow builder made it easy to map the data flow, and the testing environment showed everything functioning perfectly. We launched the automation, and for the first few weeks, it ran flawlessly.
Then came the crash.
On a busy Tuesday morning, the automation encountered an error—something as simple as a missing field in a HubSpot deal record. Instead of skipping that specific execution and continuing with other tasks, Make.com stopped the entire scenario. New deals were closing, but no Slack groups were being created. The team didn't notice immediately because they expected the automation to "just work."
By the time we realized what happened, six hours had passed. Three new client projects were delayed, team members were confused about project assignments, and the client was questioning whether automation was actually helping or hurting their efficiency.
Here's my playbook
What I ended up doing and the results.
This failure forced me to completely rethink my approach to automation platform selection. I couldn't just migrate to another platform and hope for the best—I needed to systematically test how each platform handled real-world failure scenarios.
Phase 1: The Make.com Deep Dive
First, I documented exactly how Make.com's error handling worked in practice. When a scenario encounters an error, it stops executing entirely until the error is manually resolved. There's no built-in way to skip problematic records and continue processing others. For linear workflows, this "fail-safe" approach might seem logical, but for business-critical processes, it's devastating.
I tested various workarounds within Make:
Error handlers: These could catch some errors but added significant complexity to simple workflows
Conditional logic: Helped prevent some errors but couldn't account for unexpected data variations
Multiple scenarios: Breaking the workflow into smaller pieces reduced impact but increased maintenance overhead
Phase 2: The N8N Experiment
Next, I migrated the entire workflow to N8N, attracted by its open-source nature and robust error handling. N8N offered much more granular control over error scenarios and could be configured to continue processing even when individual executions failed.
The setup required more technical knowledge—N8N definitely isn't as beginner-friendly as Make's visual interface. But once configured, it handled errors much more gracefully. When a problematic record appeared, N8N would log the error, skip that execution, and continue processing subsequent triggers.
However, a new problem emerged: every small tweak the client wanted required my intervention. While N8N offered superior technical capabilities, the interface wasn't intuitive enough for non-technical team members to make simple modifications.
Phase 3: The Zapier Reality Check
Finally, we migrated everything to Zapier. Yes, it was more expensive—nearly double the cost of Make.com. But this migration revealed something crucial that most comparison articles miss: the total cost of ownership extends far beyond subscription fees.
Zapier's error handling struck the perfect balance. When individual executions failed, the platform would retry automatically, log the failure, and continue processing other triggers. More importantly, the client's team could actually use the interface. They could navigate through each Zap, understand the logic, and make simple edits without calling me.
The real test came a month later when they wanted to modify the Slack group naming convention. In Make.com, this would have required me to update the scenario and troubleshoot any issues. In N8N, it would have definitely needed my technical intervention. In Zapier, their operations manager made the change herself in five minutes.
Error Recovery
Make stops everything when one execution fails, while other platforms handle errors more gracefully
Cost Reality
The cheapest subscription often has the highest total cost when you factor in maintenance and downtime
Team Autonomy
Your automation platform should empower your team to make changes, not create dependencies on technical experts
Business Continuity
Mission-critical workflows need platforms that prioritize continuous operation over perfect execution
The comparison wasn't just about technical capabilities—it was about business impact. Here's what the numbers revealed:
Downtime Impact: During the six-hour Make.com outage, the startup missed processing three new client projects, causing an estimated 2-day delay in project kickoffs. The operational cost far exceeded the savings from the cheaper subscription.
Maintenance Overhead: With Make.com, I was called in for troubleshooting an average of twice per month. N8N required intervention for almost every modification request. Zapier? The client team handled 90% of changes independently.
Reliability Metrics: Over a six-month period, Zapier maintained 99.8% uptime for this specific workflow. Make.com experienced four significant interruptions requiring manual intervention. N8N was technically reliable but required constant developer support.
The startup is still using Zapier today, and the hours saved on manual project setup have more than justified the higher subscription cost. More importantly, they've expanded their automation to other processes, confident that the platform won't become a single point of failure.
Unexpected Discovery: The most valuable insight wasn't about any single platform's limitations—it was realizing that platform selection should be driven by your constraint hierarchy. For this client, reliability and team autonomy mattered more than cost optimization.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After implementing automation across all three platforms for the same use case, here are my key takeaways:
1. Error handling philosophy matters more than features. Make's "stop everything" approach might work for non-critical workflows, but business-essential processes need platforms that prioritize continuity over perfection.
2. Team accessibility is a hidden cost factor. The cheapest platform becomes expensive when every change requires consultant intervention. Factor in the true cost of maintenance and modifications.
3. Complexity scales differently across platforms. Simple workflows perform similarly everywhere. Complex, mission-critical automations reveal the true differences in platform architecture and design philosophy.
4. Failure modes are more important than success features. Every platform works great when everything goes right. The differentiator is how gracefully they handle the inevitable failures and edge cases.
5. One size doesn't fit all scenarios. I now use different platforms for different client needs: Make.com for simple, non-critical workflows; N8N for complex, technical requirements; Zapier for business-critical processes requiring team accessibility.
6. Test failure scenarios before going live. Don't just test the happy path. Deliberately introduce errors and malformed data to understand how your chosen platform responds under stress.
7. Plan for operational handoffs from day one. If your team can't maintain the automation without external help, you've created a new dependency rather than solving a problem.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing automation:
Prioritize reliability over cost savings for customer-facing workflows
Ensure your customer success team can modify automations independently
Test error handling with real data variations before going live
Build alerts for automation failures into your monitoring stack
For your Ecommerce store
For ecommerce stores considering automation:
Order processing workflows need bulletproof error handling—avoid single points of failure
Inventory syncing automations should gracefully handle API rate limits and timeouts
Customer service workflows benefit from platforms your support team can modify
Test peak traffic scenarios to ensure automations don't become bottlenecks