We’re trying to make a migration decision, and part of the analysis is understanding how quickly we can actually get workflows running on each platform. The thing that’s blocking us is that enterprise migration guidance is always theoretical. Everyone says “templates accelerate deployment,” but in our experience, templates are more like starting points that you customize into something completely different.
I’m wondering if templates could actually give us an apples-to-apples comparison for implementation time. Like, if we could find templates that match our common workflow patterns, use those as baselines, and measure actual time to production on Make versus Zapier, that would be concrete data.
But I’m concerned about the hidden factor—how much time do we actually spend rebuilding templates versus just using them as-is? And does that differ between platforms?
The ROI math for migration depends partly on implementation velocity. If Make templates take 20 hours to customize versus Zapier templates taking 40 hours, that’s significant cost. But if we’re rebuilding both equally, then templates don’t really save either platform any time.
Has anyone used templates from different platforms to actually benchmark implementation time? Did templates mostly work as-is, or did you end up rebuilding them regardless?
We actually did a structured test on this because the same question was hitting our team.
We took five templates from Make and the Zapier library that matched our workflow types. We had two developers independently implement each template for their respective platform, measuring time from template selection to a working, tested automation running on real data.
The honest answer is templates sped up both platforms, but not equally. Make templates required less customization on average—roughly 65% of workflows ran with minimal tweaks. Zapier templates needed more modification, more like 40% worked without significant changes.
But here’s the thing nobody talks about—template selection time is real. We spent a couple hours just finding templates that were close enough to our needs. Once we found them, implementation differed.
For our purposes, Make was faster on average by about 15 hours across the five workflows. But the quality of templates matters more than the platform. One high-quality Make template was more useful than three mediocre Zapier ones.
If you’re doing this comparison, measure template selection time and customization separately. That’s where differences emerge.
Templates provide value primarily for common workflow patterns that match your use case exactly. When we evaluated this, we found that templates accelerate time-to-production by roughly 40-50% compared to building workflows from scratch, but only if you’re using templates that closely match your requirements. The implementation time difference between platforms came down to template quality and specificity rather than the platforms themselves. What we learned was that template libraries differ significantly between platforms in terms of coverage of business process types. If your workflows align well with available templates, you see faster implementation. If you’re building workflows that don’t have good template matches, templates become less useful. For fair comparison, focus on workflow categories that have good template support on both platforms.
Template utility depends on alignment between template design and your specific workflow requirements. Conduct a structured evaluation by identifying your top-use workflow categories, locating corresponding templates on each platform, measuring time-to-production using each template as a starting point, and tracking modifications required. This provides empirical data on implementation velocity. Additionally, assess template quality—some platforms provide well-designed, production-ready templates while others require substantial customization. This testing process typically reveals 30-50% variance in implementation time based on template quality rather than platform capability. Select templates that require minimal modification for fair comparison of baseline implementation speed.
Pick 5 matching templates from each platform. Implement them. Measure time. Zapier took us 40 hours avg, Make took 25. Template quality matters more than platform.
Templates do accelerate deployment, but comparison requires testing against your actual use cases. The difference isn’t just the template—it’s how well the platform’s development environment handles your customization needs.
What we’ve observed is that ready-to-use templates combined with AI-assisted workflow generation changes the equation significantly. Instead of starting from a template and rebuilding it, you can describe what you need in plain language, get a production-ready workflow generated automatically, then use templates as reference points if needed.
The deployment velocity advantage shows up when you’re measuring time-to-production for multiple workflows. A 15-20% faster implementation time compounds across a migration project. Over 50 workflows, that’s weeks of team time saved.
For your comparison, build out your top 10 workflow types using templates and AI-assisted generation on both platforms. Track actual hours including testing and customization. That gives you concrete implementation velocity data for ROI modeling.