Make: The No-Code Automation Revolution

Make (formerly Integromat) is the leading visual automation platform that enables connecting applications and automating complex business processes without needing to code. With over 1,400 native integrations and an intuitive visual approach, Make democratizes automation for teams of all sizes.

In today’s business world, where efficiency determines success, Make positions itself as the definitive tool to eliminate repetitive tasks and create intelligent workflows that work 24/7 without human intervention.

What is Make and why is it transforming businesses?

Make is a visual automation platform that uses a system of “scenarios” to connect different applications and web services. Unlike other automation tools, Make stands out for its visual “flowchart” interface that allows creating complex automations intuitively.

The evolution from Integromat to Make

In 2021, Integromat rebranded to Make, bringing years of experience in business automation and a solid base of over 300,000 active users. This change wasn’t just cosmetic; it represented an evolution toward:

More intuitive interface: Redesigned UI focused on user experience
Greater processing power: Capacity to handle more complex workflows
Expanded integrations: Growth from 800 to over 1,400 connectors
Advanced functionalities: Debugging, monitoring and optimization tools

Why choose Make over other alternatives?

1. Superior visualization

Make uses a visual nodes system that lets you see exactly how data flows between applications, facilitating understanding and debugging of complex workflows.

2. Advanced processing power

Unlimited operations: No artificial restrictions on business logic
Parallel processing: Multiple simultaneous branches
Robust error handling: Automatic retry and fallback systems

3. Data flexibility

Advanced transformation: Complex data manipulation without code
Intelligent filters: Sophisticated conditional logic
Arrays and objects: Native handling of complex data structures

Make’s architecture and fundamental concepts

🧩 Essential components

Scenarios

Scenarios are the heart of Make. Each scenario represents a complete workflow that can:

Execute automatically according to triggers
Process data in real-time
Handle multiple conditions and routes
Scale according to business needs

Modules

Modules are the individual building blocks that represent:

Triggers: Events that start the scenario
Actions: Operations that are executed
Filters: Conditions that determine the flow
Routers: Logical branching points

Operations

Operations are the units of measurement in Make:

One operation = one action executed by a module
Plans based on monthly operations
Real-time tracking of consumption

🔄 Typical execution flow

1. TRIGGER → An event starts the scenario
   ↓
2. FILTER → Conditions are evaluated
   ↓
3. ACTION → An operation is executed
   ↓
4. TRANSFORM → Data is processed
   ↓
5. OUTPUT → Final result is sent

Step-by-step tutorial: Your first workflow in Make

🚀 Initial setup

Step 1: Registration and setup

Create account: Visit make.com and register with your business email
Verification: Confirm your account via email
Onboarding: Complete the initial tour to familiarize yourself with the interface
Team configuration: Invite collaborators if you work in a team

Step 2: Explore the interface

Dashboard: Overview of active scenarios and statistics
Scenarios: List of all your workflows
Connections: Management of connections to external services
Webhooks: Custom endpoints for integrations
Data stores: Temporary data storage

🛠️ Creating your first scenario: Gmail to Slack

We’ll create a workflow that sends notifications to Slack when important emails arrive at Gmail.

Step 1: Create new scenario

1. Click on "Create a new scenario"
2. Search for "Gmail" in the apps list
3. Select "Watch emails" as trigger
4. Configure the connection with your Gmail account

Step 2: Configure Gmail trigger

Folder: Select “INBOX” to monitor the inbox
Criteria: Define filters like “from:[email protected]”
Max results: Set email limit per execution (recommended: 10)
Advanced settings: Configure polling interval according to needs

Step 3: Add conditional filter

1. Click the "+" button after the Gmail module
2. Select "Filter" from the menu
3. Configure condition: Subject contains "URGENT"
4. This ensures only urgent emails trigger Slack

Step 4: Configure Slack action

1. Search for "Slack" in the modules list
2. Select "Create a message"
3. Connect your Slack workspace
4. Configure:
   - Channel: #general (or specific channel)
   - Text: "Urgent email from {{1.From}} with subject: {{1.Subject}}"
   - Username: "Gmail Bot"

Step 5: Test and activate

Run once: Execute the scenario manually to test
Check results: Verify the message arrives correctly to Slack
Debug if necessary: Use the data inspector to identify issues
Activate: Turn on the scenario for automatic execution

📊 Monitoring and optimization

Scenario control panel

Execution history: Detailed history of each execution
Error logs: Record of failures and their resolution
Performance metrics: Execution time statistics
Operations usage: Operations consumption of the plan

Business use cases by industry

🛒 E-commerce and Retail

Automated order management

Scenario: New order in Shopify → CRM → Email → Slack

1. Trigger: Shopify - Watch orders
2. Action: HubSpot - Create/Update contact
3. Action: Gmail - Send email (customer confirmation)
4. Action: Slack - Send message (notify team)
5. Filter: Only orders > $500 go to VIP Slack

Measurable benefits:

85% reduction in manual processing time
0% unprocessed orders
40% improvement in customer satisfaction

Inventory automation

Scenario: Low stock → Automatic replenishment → Notifications

1. Schedule: Check inventory every hour
2. Action: Shopify - Get products with stock < 10
3. Filter: Only products in "Best Sellers" category
4. Action: Send email to supplier with list
5. Action: Create task in Asana for follow-up

📱 Digital Marketing and Growth

Automated lead nurturing

Scenario: New lead → Scoring → Personalized sequence

1. Trigger: Typeform - Watch form submissions
2. Action: Calculate lead score based on responses
3. Router: Direct according to score (High, Medium, Low)
4. High Score: Assign to sales, send premium email
5. Medium Score: 5-day nurturing sequence
6. Low Score: Monthly newsletter, retargeting ads

Scenario: New blog post → Social media automatically

1. Trigger: WordPress - Watch posts
2. Action: Create image with AI (DALL-E integration)
3. Action: LinkedIn - Post with image and excerpt
4. Action: Twitter - Automatic thread with key points
5. Action: Instagram - Story with featured quote
6. Schedule: Facebook post scheduled for prime time

🏢 Human Resources and Onboarding

Automated employee onboarding

Scenario: New employee → Complete automatic setup

1. Trigger: BambooHR - Watch employees
2. Action: Google Workspace - Create email account
3. Action: Slack - Invite to workspace and relevant channels
4. Action: Asana - Assign onboarding tasks
5. Action: DocuSign - Send contracts for signature
6. Action: Calendly - Schedule welcome sessions
7. Schedule: Reminder email day before start

💰 Finance and Accounting

Automatic invoice reconciliation

Scenario: New invoice → Processing → Accounting

1. Trigger: Email with PDF invoice attachment
2. Action: OCR - Extract invoice data
3. Action: Xero - Create accounting entry
4. Filter: Invoices > $1000 require approval
5. Action: Slack - Send for manual approval
6. Action: When approved → Mark for payment

Exhaustive comparison: Make vs. competition

Make vs. Zapier: Detailed analysis

Aspect	Make	Zapier
Interface	Visual flowchart	Linear step-by-step
Workflow complexity	Unlimited	Limited in basic plan
Data handling	Native arrays, full JSON	Limited, requires formatter
Error visualization	Detailed visual inspector	Basic text logs
Price value	Better price/features ratio	More expensive for advanced use
Learning curve	Moderate	Easy start
Integrations	1,400+ connectors	5,000+ connectors
Performance	Faster execution	Standard speed

When to choose Make over Zapier?

Complex workflows with multiple branches and conditions
Advanced data processing (arrays, objects, transformations)
Optimized budget for high-volume operations
Visual debugging required for troubleshooting
Technical use cases that require maximum flexibility

When might Zapier be better?

Non-technical users who prioritize absolute simplicity
Very specific integrations that only Zapier offers
Simple linear workflows without complex ramifications
Mature ecosystem with many pre-built templates

Make vs. Microsoft Power Automate

Feature	Make	Power Automate
Ecosystem	Independent	Microsoft 365 integrated
Flexibility	Total connector freedom	Limited outside Microsoft
Price	Transparent, usage-based	Included in M365, hidden limits
Interface	Visual flowchart	Hybrid visual/list
On-premise	Cloud-first	Hybrid cloud/on-premise
Complexity	Very complex workflows	Enterprise workflows

Make vs. n8n (Open Source)

Factor	Make	n8n
Cost	SaaS with free plan	Self-hosted free
Maintenance	Zero maintenance	Requires DevOps
Scalability	Auto-scaling	Manual scaling
Support	Professional support	Community
Security	Enterprise-grade	Depends on implementation
Time-to-value	Immediate	Requires setup

Advanced functionalities and best practices

🔧 Make’s advanced tools

Data Stores: Intelligent persistence

Data Stores allow saving information between executions:

// Example: Processed emails counter
{
  "key": "email_counter",
  "value": 1247,
  "updated": "2025-10-14T10:30:00Z"
}

Practical use cases:

Rate limiting: API control with limits
Deduplication: Avoid processing duplicates
Audit trails: Activity logging for compliance
Caching: Store API responses temporarily

Webhooks: Custom integrations

Make generates unique webhooks for each scenario:

https://hook.make.com/abc123def456ghi789

Advanced applications:

Custom APIs: Integrate internal applications
IoT devices: Connected sensors and devices
Third-party notifications: Services without native integration
Real-time triggers: Instant events vs. polling

Error Handling: Resilient workflows

Error handling strategies:

Break: Stop execution (default)
Continue: Ignore error and continue
Rollback: Undo previous operations
Retry: Automatically retry

Advanced configuration:

- Max retries: 3 attempts
- Retry interval: Incremental (1min, 5min, 15min)
- Fallback action: Send alert to administrator
- Custom error handling: Specific router for errors

🎯 Development best practices

Scalable scenario architecture

1. Single responsibility principle Each scenario should have a specific purpose:

❌ Bad: "Master workflow" that does everything
✅ Good: Specific scenarios that communicate via webhooks

2. Consistent nomenclature

[TRIGGER-APP] to [ACTION-APP] - [PURPOSE]
Example: "Gmail to Slack - Urgent Notifications"

3. Internal documentation Use notes modules to document:

Scenario purpose
Complex business logic
External dependencies
Responsible person contact

Performance optimization

1. Strategic filters Place filters early in the workflow:

✅ Correct: Trigger → Filter → Heavy Processing
❌ Incorrect: Trigger → Heavy Processing → Filter

2. Batch processing For high-volume data, use:

Aggregators: Process multiple items together
Schedulers: Distribute load over time
Rate limiters: Respect API limits

3. Connection pooling Reuse connections between scenarios to:

Reduce authentication latency
Optimize shared rate limits
Simplify credential management

🔒 Security and compliance

Credential management

Make uses OAuth 2.0 and encryption at rest:

Credentials never exposed in logs
Automatic token rotation
Access audit trail
SOC 2 Type II compliance

Data privacy

GDPR compliant: Right to be forgotten
Data residency: Region choice
Encryption: TLS 1.3 in transit
Access controls: Granular roles

Advanced troubleshooting and debugging

🔍 Data inspector: Your best ally

Make’s Data Inspector is the most powerful debugging tool:

Key functionalities

Input/Output tracking: See exactly what data enters and exits
Execution timeline: Detailed chronology of execution
Error highlighting: Visual identification of problems
Data transformation: Preview how data is transformed

Inspector use cases

1. Scenario fails → Open inspector
2. Identify problematic module (marked in red)
3. View input data of failed module
4. Compare with expected format
5. Adjust mapping or add transformer

⚠️ Common errors and solutions

1. Incorrect data mapping

Error: Property 'email' not found Cause: Email field doesn’t exist in data source Solution:

// Use null coalescing
{{1.email ?? 1.mail ?? "[email protected]"}}

2. Rate limiting

Error: Too many requests (429) Cause: Excess calls to external API Solution:

- Add delay between operations (Sleep module)
- Implement exponential backoff
- Use batch operations when possible

3. Timeout in long operations

Error: Execution timeout after 40 seconds Cause: Operation taking too much time Solution:

- Divide into multiple smaller scenarios
- Use webhooks for asynchronous operations
- Implement pagination for large datasets

4. JSON parsing errors

Error: Invalid JSON format Cause: String is not valid JSON Solution:

// Validate before parsing
{{if(isJSON(1.response), parseJSON(1.response), "{}")}}

🛠️ Debugging tools

1. Notes modules

Use Notes for temporary debugging:

- Log intermediate values
- Document complex logic
- Mark checkpoints in workflow
- Debug conditional branches

2. Email notifications for debugging

Subject: "DEBUG: {{scenario.name}} - {{formatDate(now; "YYYY-MM-DD HH:mm")}}"
Body: "
Input data: {{1.input}}
Processed data: {{2.output}}
Error (if any): {{error.message}}
"

Featured integrations and special cases

🤖 AI and Machine Learning

OpenAI GPT Integration

Make + ChatGPT for intelligent automations:

Use case: Automatic classification of support tickets

1. Trigger: Zendesk - New ticket
2. Action: OpenAI - Analyze ticket content
3. Prompt: "Classify this support ticket: {{1.description}}"
4. Router: Route based on AI classification
5. Path A: Technical → Assign to dev team
6. Path B: Billing → Assign to finance
7. Path C: General → Assign to general support

Computer Vision workflows

1. Trigger: Dropbox - New image uploaded
2. Action: Google Vision AI - Analyze image
3. Filter: Only images with "product" label
4. Action: Extract text via OCR
5. Action: Update inventory spreadsheet
6. Action: Send Slack notification with analysis

🌐 Advanced API Management

Custom API wrapper

Create wrapper for APIs without native integration:

// HTTP module configuration
URL: https://api.custom-service.com/v1/{{endpoint}}
Method: {{method}}
Headers: {
  "Authorization": "Bearer {{connection.token}}",
  "Content-Type": "application/json"
}
Body: {{data}}

API response caching

1. Check Data Store for cached response
2. If cache miss → Call external API
3. Store response in Data Store with TTL
4. Return cached or fresh data
5. Benefits: Faster response, API cost reduction

📊 Analytics and reporting

Automated reporting dashboard

1. Schedule: Daily at 9 AM
2. Action: Gather data from multiple sources
   - Google Analytics: Website traffic
   - Shopify: Sales data
   - Facebook Ads: Campaign performance
   - Gmail: Email campaign metrics
3. Action: Compile into comprehensive report
4. Action: Generate charts with Google Sheets
5. Action: Send executive summary via email
6. Action: Post summary to Slack #executives

Future of Make and automation trends

🚀 Make’s roadmap

Features in development

AI-powered workflow suggestions: AI that suggests optimizations
Natural language scenario building: Create workflows with text
Advanced analytics dashboard: Deep business metrics
Complete mobile app: Full management from mobile devices

Emerging integrations

Blockchain platforms: DeFi and NFT marketplaces
IoT ecosystems: Smart home and industrial IoT
AR/VR platforms: Metaverse and augmented reality
Edge computing: Distributed processing

🌍 Industry trends

1. Hyperautomation

Definition: Automation of all possible processes
Components: RPA + AI + Low-code + Analytics
Impact: Complete digital transformation

2. Citizen automation

Democratization: Non-technical users creating workflows
Self-service: Departments creating their own solutions
Governance: Frameworks to control proliferation

3. Intelligent automation

AI-driven decisions: Automation that learns and adapts
Predictive workflows: Anticipate needs and act
Context-aware: Automation that understands situations

Additional resources and next steps

📚 Learning resources

Official documentation

Make Academy: Free structured courses
Help Center: Complete knowledge base
API Documentation: For custom integrations
Community Forum: Community support

Recommended YouTube channels

Make Official: Official tutorials and updates
Automation Consultants: Advanced use cases
No-Code Community: Trends and best practices

Templates and blueprints

Template Gallery: 500+ pre-built scenarios
Industry-specific: Templates by industry
Community Templates: Shared by users
Custom Blueprint Service: Custom development

🎯 Recommended implementation plan

Week 1-2: Fundamentals

Create account and familiarize with interface
Complete basic Make Academy
Create 3-5 simple test scenarios
Identify candidate processes for automation

Week 3-4: Initial implementation

Select 2-3 high-impact processes
Design complete workflows
Implement with robust error handling
Document and train the team

Month 2: Expansion and optimization

Analyze metrics of active scenarios
Optimize operations and performance
Implement more complex use cases
Establish governance and best practices

Month 3+: Scaling

Expand to other departments
Implement interdepartmental workflows
Explore advanced integrations (AI, ML)
Develop internal center of excellence

🤝 Community and support

Official support channels

Help Desk: Direct tickets to Make team
Live Chat: Real-time support (Pro+ plan)
Phone Support: Telephone support (Enterprise)
Success Manager: Dedicated manager (Enterprise)

Active communities

Reddit r/make: Technical discussions and troubleshooting
Facebook Groups: Use cases and inspiration
LinkedIn Communities: Professional networking
Discord Servers: Real-time chat with experts

Conclusion: Transforming work with intelligent automation

Make represents more than an automation tool; it’s a digital transformation catalyst that allows organizations to reimagine how they operate and create value.

The transformational impact

Automation with Make doesn’t just eliminate repetitive tasks; it frees human potential to focus on higher-value activities:

Creativity and innovation instead of manual processes
Strategic analysis instead of data collection
Customer relationships instead of internal administration
Business growth instead of operational maintenance

Preparing for the future

Organizations that adopt Make today don’t just optimize their current operations; they strategically position themselves to:

Adapt quickly to market changes
Scale operations without linearly increasing costs
Integrate new technologies (AI, IoT, blockchain) without friction
Maintain competitive advantage through operational excellence

Your next step

Automation isn’t the future; it’s the present. Every day without automation is a day of lost advantage against competitors who are already optimizing their operations.

Make democratizes the power of business automation, putting it within reach of any organization willing to evolve. The question isn’t whether your company needs automation, but how quickly you can implement it.

Ready to transform your company with intelligent automation? Explore our specialized guides on complementary tools and digital transformation strategies to maximize the impact of your automated workflows.