Make vs Zapier

Pricing: per-task vs credits

Zapier uses task-based billing. Make now uses credits: most non-AI module operations consume one credit, while some AI and advanced features use different rules. Compare current plan documentation with a representative run trace because bundles, retries, and AI usage change the total.

A fair comparison must model the actual scenario. Make now bills in credits, with feature-specific rules for some AI and advanced functions; Zapier uses tasks and product-specific usage rules. Count the modules, actions, retries, fan-out, and AI usage, then compare the current plans. Neither platform has a universal step-count crossover or cost multiple.

Branching, routers, iterators

Make has a criteria-specific edge for visual control flow: routers, iterators, aggregators, and error handlers are first-class canvas primitives. Validate the exact scenario because Zapier also supports paths and looping through a different authoring model.

Zapier has Paths (conditional branching) and Looping (iteration), but both feel like extensions to a fundamentally linear trigger-to-action model. For two or three branches and a loop, Paths and Looping work fine; for five or more branches, nested iterators, or recovery paths, Make is better suited and friendlier -- you see the whole logic on the canvas instead of clicking through tabs.

Debugging and AI

Both debuggers are solid but shaped differently. Zapier has a clean task history with per-step input/output and a Replay button -- enough to triage 2-3 step Zaps quickly. Make has full execution history with canvas-style visual replay, per-module bundles, and configurable error handlers; for 8-12 step branching scenarios, watching data flow through the canvas is far easier to reason about than a list view.

Zapier now centers AI by Zapier inside Zaps, combining a tool-calling reasoning step with deterministic triggers, approvals, and actions. Make combines AI modules and its evolving AI Agents surface with the existing scenario canvas, routing, logs, and error handlers. Do not infer equal maturity from the shared “agent” label; test the exact tool permissions, execution logs, failure recovery, and human-approval path each workload needs.

Lock-in and migration

Both are high lock-in in the same ways: cloud-only, no export to a portable format, manual rebuild to migrate. The realistic risk is not shutdown -- both are mature and well-funded -- but a pricing change or product-direction shift, where your only responses are stay or rebuild. If owning the runtime or portability matters, a source-available self-host tool (n8n, Activepieces, Windmill) is the better fit.

Migration has no importer either direction. Zapier to Make is usually straightforward (Paths become routers, Looping becomes iterators, Formatter steps become inline functions). Make to Zapier keeps fidelity only for simple scenarios -- deep router nesting, iterators feeding aggregators, or error-handler chains cannot map one-to-one and often become two or three Zaps where one Make scenario lived. Cutover pattern either way: rebuild, test with real data, run both versions in parallel for a risk-appropriate validation window, switch the trigger, and retain a rollback path until the replacement is proven stable.

Our take

Frame the choice by workflow shape, not by which product is better overall. Mostly linear glue across a wide SaaS stack can favor Zapier. Multi-step automation with visible routers, iterators, and conditional logic can favor Make, but cost still requires a representative scenario under current plan rules.

A growing team may use both: Zapier for connector coverage and Make for scenarios that benefit from its visual control-flow model. That split adds governance and migration overhead, so compare the combined operating model rather than assuming it reduces cost.