Automation is no longer a “nice to have” but a necessity for small and medium-sized enterprises (SMEs) trying to scale efficiently. With repetitive tasks eating into valuable time, choosing the right automation platform can make a real difference.
Two of the top contenders in this space are Make (formerly Integromat) and Zapier. Each has its strengths and trade-offs, depending on workflow complexity, budget, team skills, and data needs. This post compares Make vs Zapier from an SME perspective: features, usability, cost, limitations, and how adding a platform like Peliqan can help you build stronger, more maintainable automation pipelines.
What Are Make & Zapier?
Make offers a visual, scenario-based environment. You build workflows (“scenarios”) by dragging modules onto a canvas, connecting them, and defining logic. It supports branching, loops, iterators, and detailed data operations, making it powerful for complex multi-step workflows.
Zapier provides a simpler, linear approach. You define a trigger and a series of actions that follow. It’s designed for quick setup, with a guided UI and templates. Zapier is ideal for standard automations like “new customer → send email” or “new sale → notify team.”
Feature-by-Feature Comparison
| Feature | Make | Zapier |
|---|---|---|
| Visual Builder & Logic | Canvas-based scenarios, routers, iterators, extensive data transformations | Step-by-step linear flows, limited branching, basic data tools |
| Integrations | ~2,000+ connectors, strong HTTP/webhook module for custom APIs | ~7,000+ integrations, one-click setup, very broad coverage |
| Data Handling | Advanced parsing, iterators over arrays, powerful mapping | Limited transformation tools, relies on pre-formatted data |
| Templates | Good library but fewer than Zapier | Large template ecosystem for fast adoption |
| User Experience | Powerful but steeper learning curve | Beginner-friendly, streamlined setup |
| Team Features | Shared scenarios, version history on higher plans | Strong collaboration tools, audit trails, enterprise controls |
| Reliability | Detailed logs, strong error handling, can be slower for very large workflows | Polished monitoring, reliable for simpler tasks |
| Scalability | Per-operation billing, cost-effective for high-volume automation | Task-based billing, costs grow faster at scale |
Pricing & Plans
| Plan | Make | Zapier |
|---|---|---|
| Free | 1,000 operations/month, multi-step scenarios | 100 tasks/month, single-step Zaps |
| Entry | $9 for 10,000 operations | $29.99 for 750 tasks |
| Mid | $29 for ~40,000 operations | $73.50 for 2,000 tasks |
| High Usage | $99 for 150,000 operations | $448.50 for 50,000 tasks |
Make’s per-operation billing is attractive for multi-step, data-heavy workflows. Zapier’s pricing is predictable for lighter, simpler automation.
Real-World Use Cases
Both platforms power thousands of automations, but they shine in different situations depending on complexity and scale.
1. Marketing & Lead Management
Zapier: Ideal for quick, “plug-and-play” connections like sending new Facebook Lead Ads directly to a HubSpot or Salesforce CRM, or auto-posting new blog articles to social channels. Small teams appreciate the pre-built templates that make these flows live within minutes.
Make: Favored when marketing data needs deeper conditioning—such as merging multiple ad-platform feeds, cleaning the data, and then pushing enriched leads into a data warehouse or custom dashboard. Its routers and iterators handle complex branching with ease.
2. E-Commerce Operations
Zapier: Perfect for simple store tasks: when an order is created in Shopify, automatically add the buyer to a Mailchimp list or send an SMS confirmation.
Make: Better for large catalogs or multi-store networks. Retailers use Make to sync product inventory across different platforms, transform CSV price lists, and run multi-step order-fulfillment pipelines with conditional logic.
3. IT & Internal Workflows
Zapier: Great for lightweight IT automations—like creating a Slack alert when a new Jira issue is logged.
Make: Fits enterprise IT scenarios, for example monitoring infrastructure events from multiple APIs, transforming the data, and feeding it into custom monitoring dashboards or internal ticketing systems.
4. Data & Analytics Integrations
Both platforms can trigger analytics updates, but Make is often chosen when companies need to blend and reshape data from many SaaS tools before pushing it into a warehouse or BI tool.
Community experiences echo these patterns. For instance, Reddit NoCode discussions show small teams praising Zapier’s simplicity, while larger operations lean on Make for advanced routing and cost efficiency.
Learning Curve and Documentation
Zapier is built for ease of use, with a step-by-step interface and thousands of ready-made templates. Most users can create their first automation in minutes without prior technical knowledge. Its knowledge base includes interactive tutorials, clear setup guides, and a large community forum where beginners quickly find answers.
Make’s documentation is thorough and offers deep technical examples, but it assumes some comfort with concepts like JSON, arrays, and API calls. Building advanced scenarios – such as handling nested data or conditional branching – can take time to master. For teams willing to invest that learning effort, the payoff is powerful, highly customized workflows.
For real-world feedback on the learning curve and support quality, see independent user ratings on G2 – Make reviews and Zapier reviews.
Trade-Offs
While both tools are reliable, each has limitations worth noting. Zapier’s simple pricing can become expensive when you need high-volume, multi-step workflows, and it offers limited options for complex logic or heavy data manipulation.
Make provides much deeper control – such as iterators, routers, and advanced data mapping—but that flexibility comes with a steeper learning curve and occasional performance tuning for very large scenarios. Community discussions often highlight these contrasts.
Users on Reddit’s NoCode forum frequently point out that Zapier is perfect for quick wins and small teams, whereas Make shines when you need intricate automations or cost efficiency at scale.
The Peliqan Advantage
As your automation needs grow, challenges like scattered data, repeated API calls, and limited analytics emerge. Peliqan complements Make or Zapier by providing a robust data layer. It consolidates data from SaaS tools, APIs, and databases into a single source of truth.
With built-in Python and SQL transformations, Peliqan reduces redundant API usage, enforces schema consistency, and supports advanced analytics. This combination allows SMEs to automate workflows with Make or Zapier while ensuring clean, analytics-ready data for dashboards, reporting, and AI initiatives.
| Challenge | Make/Zapier Alone | With Peliqan |
|---|---|---|
| Data consolidation | Multiple sources and formats | Centralized warehouse |
| Complex transformations | Limited in-app options | Full Python/SQL processing |
| High API costs | Repeated calls in every workflow | Cached data reduces calls |
| Governance | Limited schema control | Versioning and data lineage |
Summary
If you need speed and simplicity, Zapier is the fastest path to live automations; if you need advanced branching, data mapping and better economics at scale, Make is the stronger choice. But both platforms can create data sprawl, repeated API costs, and governance headaches as you grow — which is where Peliqan adds real value.
Peliqan centralizes SaaS and API data, provides Python/SQL transformations, caching, versioning and lineage so workflows built in Zapier or Make run faster, cheaper, and produce clean, analytics-ready datasets. Start with the tool that fits your team’s immediate needs, then use Peliqan to scale those automations into a reliable data infrastructure.
