→How to Migrate from Make (Integromat) to Rows (Step-by-Step)
Last updated: April 2026
Migrating from Make (Integromat) to Rows makes sense when you want to move from complex workflow automation to AI-enhanced spreadsheet automation with live data connections. Rows offers familiar spreadsheet interfaces with powerful automation capabilities, making it ideal for teams that prefer working with data in tabular formats rather than visual workflows. This guide covers inventory assessment, data migration, workflow recreation, testing strategies, and team training. You'll learn how to translate Make's visual automations into Rows' spreadsheet-based automations while maintaining data integrity and functionality.
Estimated Timeline
solo user
2-5 days depending on scenario complexity
small team
1-2 weeks including testing and training
enterprise
3-6 weeks with phased migration approach
Migration Steps
Inventory and Assessment
mediumData Export and Backup
easySet Up Rows Environment
easyRecreate Core Automations
hardImport Historical Data
mediumParallel Testing Phase
mediumTeam Training and Documentation
mediumFinal Cutover and Optimization
hardFeature Mapping
| Make (Integromat) | Rows Equivalent | Notes |
|---|---|---|
| Visual workflow builder | Spreadsheet formulas + AI automation | Rows uses spreadsheet logic instead of visual flows; AI helps translate complex workflows |
| App integrations modules | Live data connectors | Rows provides direct spreadsheet connections to services instead of visual integration blocks |
| Data routing and filtering | Spreadsheet filters + query functions | Use Rows' FILTER(), QUERY(), and SORT() functions instead of visual routers |
| Error handling routes | IFERROR() + data validation | Implement error handling through spreadsheet formulas and data validation rules |
| Webhooks and HTTP modules | Rows API endpoints + webhook cells | Rows allows creating API endpoints directly from spreadsheets for webhook reception |
| Data transformation tools | AI data transformation + formulas | Use Rows' AI features for smart data cleaning and transformation |
| Schedule triggers | Automation schedules | Rows offers similar scheduling but within spreadsheet automation settings |
| Team collaboration features | Real-time collaboration + comments | Rows provides enhanced spreadsheet collaboration with live editing and commenting |
Data Transfer Guide
Export data from Make by accessing each scenario's data history and using the export functionality. For structured data, export to CSV format. For complex nested data, use JSON exports. In Make's dashboard, navigate to each scenario's operations history and select export options. For Rows import, use the 'Import Data' feature from the File menu. Drag and drop your CSV/JSON files or connect directly to cloud storage. Rows will automatically detect data types and create appropriate columns. For ongoing data syncs, replace Make's data collection modules with Rows' live connectors to services like Google Sheets, databases, or APIs. Test imports with small datasets first to verify formatting before migrating full datasets.