Make Review 2026: Complete Guide for Sales Teams

What is Make?

Make (formerly Integromat) is a powerful visual automation platform that enables sales teams and businesses to build complex, multi-step workflows connecting 1000+ apps and services without writing code. Founded in 2012 in the Czech Republic and rebranded to Make in 2022, the platform has become the preferred choice for teams that need sophisticated automation beyond what simple point-and-click tools can deliver.

At its core, Make is an integration platform as a service (iPaaS) that sits between your various business tools, moving data, triggering actions, and orchestrating complex processes automatically. Unlike basic automation tools that handle simple "if this, then that" workflows, Make excels at building elaborate scenarios involving multiple apps, conditional logic, data transformation, and advanced error handling.

The platform's target audience includes RevOps teams, sales operations professionals, marketing automation specialists, and technical users who need to automate complex business processes but prefer visual workflow design over traditional coding. Make particularly resonates with teams that have outgrown simple automation tools like Zapier but aren't ready for enterprise-grade platforms like MuleSoft.

What makes Make unique is its visual, flowchart-style interface that displays workflows as interconnected nodes and paths. This visual approach makes it easier to understand complex logic, debug issues, and maintain sophisticated automations. Every workflow scenario clearly shows how data flows between systems, where transformations occur, and what happens when errors arise.

Key Features

Visual Workflow Builder

Make's visual workflow builder is the platform's signature feature. Instead of linear step-by-step automation, Make displays workflows as flowcharts where you can see all connections, branches, and logic paths simultaneously.

Each workflow scenario consists of modules (individual app actions) connected by routes (data flow paths). You can create parallel branches, merge data from multiple sources, apply conditional routing based on specific criteria, and build loops for processing arrays of data. The visual representation makes it immediately clear how data moves through your automation.

For sales teams, this means building scenarios like: "When a new lead enters the CRM, enrich their data from multiple sources simultaneously, score them based on criteria, route high-value leads to Slack for immediate attention, add others to a nurture sequence, and log everything back to the CRM" – all visible as a single flowchart.

The learning curve is moderate. Users familiar with flowcharts and basic logic will grasp the fundamentals in hours, though mastering advanced features like iterators, aggregators, and error handlers takes weeks of practice.

1000+ App Integrations

Make connects to over 1000 applications across categories including CRMs (Salesforce, HubSpot, Pipedrive), sales tools (Apollo, Outreach, Instantly), communication platforms (Slack, Teams, Gmail), databases (Airtable, PostgreSQL, MongoDB), and specialized services.

Each integration provides dedicated modules for common actions (create, update, delete, search) plus webhook support for real-time triggers. Premium apps often include advanced modules for complex operations. Make's HTTP module allows connecting to any service with an API, even if there's no native integration.

For sales operations, critical integrations include CRM platforms, data enrichment tools (Clearbit, Apollo), outreach platforms, calendar schedulers, and analytics systems. Make's extensive integration library means you can typically connect your entire sales stack without custom development.

Integration quality varies. Popular apps (Google, Salesforce, HubSpot) have well-maintained, feature-rich integrations with extensive documentation. Niche apps may have basic integrations requiring more manual configuration. The community actively contributes templates for common integration patterns.

Advanced Data Transformation

Make includes powerful built-in functions for transforming data as it flows through workflows. You can parse JSON, manipulate text, perform mathematical calculations, format dates, merge arrays, filter datasets, and apply custom formulas without external tools.

Functions are organized into categories: text operations, numeric operations, array functions, date/time manipulation, encoding, and more. You can combine multiple functions to build complex transformations. For example, extracting a domain from an email address, capitalizing names, converting time zones, or restructuring nested data objects.

For sales teams, common transformations include: cleaning imported data (removing duplicates, standardizing formats), enriching records (combining data from multiple sources), calculating lead scores, formatting personalization variables for outreach, and structuring data for CRM import.

The formula builder uses a syntax similar to spreadsheet formulas, making it accessible to users with Excel experience. Advanced users can write custom JavaScript for complex transformations that exceed built-in function capabilities.

Robust Error Handling

Unlike basic automation tools where errors break entire workflows, Make provides sophisticated error handling mechanisms that allow scenarios to recover gracefully from failures or route around problems.

Error handlers can be attached to any module, defining what happens when that specific step fails. Options include: retry the operation with exponential backoff, route to an alternative path, send error notifications to Slack or email, log failures to a database, or continue the workflow with default values.

For production-critical sales automations, this is essential. When an API rate limit is hit, Make can pause and retry. When a CRM field is missing, the workflow can use a fallback value. When enrichment fails, the lead can still be added to outreach with partial data rather than being lost entirely.

Advanced error handling includes commit and rollback controls for transaction-like behavior, allowing you to undo previous steps if a later step fails. This prevents partial data writes that corrupt your systems.

Scheduling and Execution Control

Make offers flexible scheduling options for workflows. Scenarios can run on interval schedules (every X minutes/hours), specific times (daily at 9 AM), webhook triggers (real-time when data arrives), or manual execution.

The interval scheduler includes intelligent execution limits. Free plans allow scenarios to run every 15 minutes, paid plans support intervals down to 1 minute for near-real-time automation. Webhook triggers execute instantly when events occur, enabling true real-time integrations.

For sales teams, scheduling enables automated daily lead list building, hourly CRM sync, real-time Slack notifications for hot leads, nightly data enrichment batches, and weekly reporting automation. The granular control means you can optimize scenarios to balance timeliness with API rate limits and operation costs.

Make also provides execution history, showing every scenario run with complete data logs. You can inspect what data entered each module, what transformations occurred, and what results were produced. This transparency is invaluable for debugging and compliance.

Scenario Templates

Make offers a template library with pre-built scenarios for common use cases. Templates cover integrations like "Sync Salesforce leads to Google Sheets," "Create HubSpot contacts from form submissions," "Send Slack notifications for CRM opportunities," and hundreds of others.

Templates provide a starting point, reducing setup time from hours to minutes. You can clone a template, customize the apps and logic for your needs, and deploy immediately. This is particularly valuable for users new to Make or implementing common patterns.

The community also shares custom templates, and Make's marketplace allows vendors to publish certified templates for their apps. For sales teams, popular templates include CRM sync, lead enrichment workflows, outreach automation, and reporting dashboards.

Multi-Step Workflows with Branching

Make excels at complex workflows requiring conditional logic and parallel execution. You can build scenarios that branch based on data conditions, process multiple paths simultaneously, merge results, and make decisions dynamically.

For example, a lead qualification workflow might: receive a webhook from a form, enrich the lead data from Clearbit, score them based on firmographic criteria, then branch three ways simultaneously (add to CRM, send to outreach if qualified, notify sales on Slack if high-value), aggregate results, and log the complete record.

This multi-path capability is where Make outshines simpler tools. Instead of creating separate automations for different scenarios, you build one comprehensive workflow that handles all cases with conditional routing. This reduces duplication, simplifies maintenance, and ensures consistency.

Pricing and Plans

Make uses an operation-based pricing model where scenarios consume "operations" each time a module executes. Understanding this model is crucial for cost management.

Free Plan

• 1,000 operations/month
• Scenarios run every 15 minutes
• 2 active scenarios
• 100 MB data transfer
• 15-minute execution limit per scenario
• Best for: Testing, personal projects, very light automation

Reality Check: 1,000 operations sounds like a lot but depletes quickly. A simple 3-step scenario (trigger + 2 actions) running every 15 minutes consumes ~8,640 operations monthly (3 operations × 4 runs/hour × 24 hours × 30 days). The free plan is genuinely useful for evaluation but insufficient for production use.

Core ($9/month, billed annually)

• 10,000 operations/month
• Scenarios run every 5 minutes
• Unlimited active scenarios
• 100 MB data transfer
• 40-minute execution limit
• Best for: Small teams, simple automations, getting started

Value Analysis: At $9/month, this represents exceptional value for straightforward automations. 10,000 operations supports approximately 5-10 active scenarios running regularly, suitable for small sales teams automating basic workflows like form-to-CRM sync or notification alerts.

Pro ($16/month, billed annually)

• 10,000 operations/month (base allocation)
• Scenarios run every 1 minute
• Full-text execution log search
• Priority app updates
• 40-minute execution limit
• Best for: Growing teams needing near-real-time automation

Note: The Pro plan includes the same 10,000 base operations as Core, but allows purchasing additional operation packs at better rates. The primary benefits are faster execution intervals and enhanced logging.

Teams ($29/month, billed annually)

• 10,000 operations/month (base allocation)
• All Pro features
• Team management and permissions
• Shared scenario templates
• 40-minute execution limit
• Best for: Sales operations teams collaborating on automations

Enterprise (Custom pricing)

• Custom operation volumes
• Dedicated infrastructure options
• SSO and advanced security
• SLA guarantees
• Dedicated support
• Premium app integrations
• Best for: Large organizations with mission-critical automations

Understanding Operation Costs

Operations are consumed each time a module executes:

• Triggers: 1 operation per execution
• Actions (create, update, delete): 1 operation each
• Searches: 1 operation per search
• Iterators/Aggregators: 1 operation per item processed
• API calls: 1 operation per call

Example Scenario Cost: A workflow that triggers hourly, searches CRM for new leads (1 op), enriches 10 leads via API (10 ops × 2 modules = 20 ops), and creates records in outreach platform (10 ops) = 31 operations per run × 24 runs/day = 744 operations daily or ~22,320 operations monthly.

This example would require additional operation packs beyond base allocations. Make offers operation packs starting at $9 for 10,000 additional operations, scaling to $89 for 100,000 operations.

Hidden Costs to Consider:

• Processing large datasets quickly exhausts operations through iterators
• Webhook-triggered scenarios can spike unpredictably with traffic
• Error retries consume additional operations
• Testing and debugging count against your operation quota

Value Comparison: Make is generally more cost-effective than enterprise platforms (MuleSoft, Workato) but can become expensive at high volumes compared to Zapier's task-based model or n8n's self-hosted option. Teams should carefully estimate operation consumption before committing to paid plans.

Who Should Use Make?

Ideal Customer Profile

Perfect Fit:

• Sales operations and RevOps teams (5-50 employees)
• B2B companies with complex, multi-system workflows
• Teams that have outgrown Zapier's linear automation model
• Organizations needing sophisticated error handling and data transformation
• Technical sales teams comfortable with logic and data concepts
• Businesses requiring transparent, auditable automation workflows

Company Stage:

• Series A to Series C companies with established sales operations
• Growing SMBs investing in operational efficiency
• Mid-market companies automating manual processes
• Organizations with technical resources to build and maintain scenarios

Use Case Examples:

• Multi-step lead enrichment pulling data from multiple providers
• Complex CRM sync with conditional routing and transformation
• Sales alert systems with intelligent filtering and prioritization
• Automated reporting combining data from CRM, outreach, and analytics
• Lead routing workflows with territory assignment and scoring
• Data cleanup automations fixing inconsistent CRM records

When NOT to Use Make

Poor Fit:

• Non-technical users needing simple, one-step automations (consider Zapier)
• Very early-stage startups without dedicated ops resources
• Teams needing only basic trigger-action workflows without complex logic
• Organizations without time to learn the platform (2-4 week ramp-up)
• High-volume scenarios processing millions of records monthly (evaluate enterprise iPaaS or custom development)
• Teams needing complete data ownership and on-premise hosting (consider n8n)

Pros and Cons

Pros

Unmatched Visual Clarity: Make's flowchart interface provides superior understanding of complex workflows compared to linear, step-based builders. You can see all logic paths, data transformations, and error handling at a glance. This transparency dramatically reduces debugging time and makes handoffs between team members smoother.

Superior Error Handling: Make's error handler system is best-in-class for automation platforms. The ability to define specific recovery paths, implement retry logic, and route around failures means production scenarios are remarkably resilient. Sales teams can trust that critical automations won't silently fail or corrupt data.

Powerful Data Transformation: The built-in function library handles sophisticated data manipulation that would require custom code in other platforms. Sales teams can clean, enrich, format, and restructure data on the fly without external tools or developer involvement.

Cost-Effective for Complex Workflows: While simple automations might cost more on Make than Zapier (due to operation counting), complex scenarios with multiple branches and transformations often cost less because you build one comprehensive workflow instead of many separate automations.

Granular Execution Control: The combination of flexible scheduling, manual execution options, operation logging, and execution history provides unprecedented control over automation behavior. You can optimize scenarios for performance, cost, and reliability with fine-grained precision.

Active Development and Community: Make ships new features, app integrations, and improvements regularly. The platform has evolved significantly since rebranding from Integromat, with clear investment in product development. The user community is active, helpful, and shares templates and solutions freely.

Professional-Grade Capabilities: Features like webhooks, HTTP modules, custom function support, and advanced routing logic enable building automations that rival custom-coded solutions. Technical teams can implement nearly any integration pattern without hitting platform limitations.

Cons

Steeper Learning Curve: Make requires more time to master than simpler tools. New users typically need 1-2 weeks to build basic scenarios and 4-6 weeks to become proficient with advanced features. The visual interface, while powerful, introduces concepts (routers, iterators, aggregators) that aren't immediately intuitive.

Operation Counting Complexity: The operation-based pricing model is harder to predict than task-based models. Scenarios that iterate over arrays or loop through datasets can consume operations rapidly in unexpected ways. Teams must carefully monitor usage to avoid overage charges.

Overwhelming for Simple Needs: If you only need basic trigger-action automation ("when form submitted, create CRM contact"), Make's capabilities are overkill. The additional complexity doesn't provide value for straightforward workflows.

Less Intuitive for Non-Technical Users: While Make doesn't require coding, it assumes familiarity with logical concepts, data structures, and API basics. Non-technical sales users may struggle without ops or technical support to build and maintain scenarios.

Documentation Gaps for Advanced Features: While basic documentation is solid, advanced features sometimes lack comprehensive examples or detailed explanation. Users often rely on community forums and experimentation to solve complex implementation challenges.

Limited Native Apps vs Competitors: While Make supports 1000+ apps, some niche sales tools lack native integrations, requiring HTTP module workarounds. Zapier's library of 5000+ apps provides more out-of-box options for less common tools.

Make vs Alternatives

Make vs Zapier

The most frequent comparison in workflow automation:

Complexity Capability:

• Make: Designed for complex, multi-branch workflows with sophisticated logic
• Zapier: Optimized for simple, linear trigger-action automations

User Interface:

• Make: Visual flowchart showing all paths and connections
• Zapier: Step-by-step linear builder, cleaner for simple workflows

Pricing:

• Make: Operation-based, better value for complex scenarios
• Zapier: Task-based, more predictable for simple automations

Learning Curve:

• Make: 2-4 weeks to proficiency, requires logical thinking
• Zapier: 1-3 days to productivity, very user-friendly

Error Handling:

• Make: Sophisticated error handlers with custom recovery logic
• Zapier: Basic retry and error notification options

Data Transformation:

• Make: Extensive built-in function library, powerful transformations
• Zapier: Basic formatting, often requires external tools or code steps

Best For:

• Make: Teams needing complex workflows, conditional logic, advanced error handling
• Zapier: Non-technical users, simple automations, quick setup

Verdict: Choose Zapier for simplicity and speed when building straightforward automations. Choose Make when workflows require conditional branching, complex data manipulation, or sophisticated error handling. Many teams use both: Zapier for simple automations, Make for complex orchestration.

Make vs n8n

Both target technical users but with different approaches:

Deployment:

• Make: Cloud-hosted SaaS platform
• n8n: Self-hosted (open source) or cloud-hosted

Pricing:

• Make: Operation-based subscription
• n8n: Free self-hosted, cloud plans start at $20/month

Data Ownership:

• Make: Data processes through Make's infrastructure
• n8n: Self-hosted option provides complete data control

Integrations:

• Make: 1000+ native integrations, professionally maintained
• n8n: 400+ integrations, community-driven quality varies

Ease of Use:

• Make: Polished interface, better documentation, professional support
• n8n: More technical, requires infrastructure knowledge for self-hosting

Customization:

• Make: Custom functions, HTTP module for API access
• n8n: Full code node for JavaScript, deeper customization

Best For:

• Make: Teams wanting managed service, professional support, proven reliability
• n8n: Technical teams requiring data sovereignty, unlimited execution, budget constraints

Verdict: Choose n8n if you have technical resources to self-host, need complete data control, or want unlimited operations. Choose Make for professionally maintained service, superior documentation, and when you prefer managed infrastructure over self-hosting complexity.

Make vs Tray.io

Both target the same market but at different scales:

Target Market:

• Make: SMBs to mid-market companies
• Tray.io: Mid-market to enterprise

Pricing:

• Make: Accessible starting at $9/month
• Tray.io: Enterprise pricing starting at $15,000+ annually

Complexity:

• Make: Handles sophisticated workflows, visual builder
• Tray.io: Enterprise-grade orchestration, professional services

Governance:

• Make: Basic team permissions, activity logging
• Tray.io: Advanced governance, compliance certifications, audit trails

Support:

• Make: Community, email, knowledge base
• Tray.io: Dedicated customer success, professional services, SLAs

Best For:

• Make: Growing companies, sales operations teams, $100-5000/month automation budget
• Tray.io: Large enterprises, mission-critical integrations, complex compliance requirements

Verdict: Make and Tray.io rarely compete directly due to price point differences. Choose Make for accessible, powerful automation at SMB/mid-market scale. Consider Tray.io when enterprise governance, compliance, and dedicated support justify the premium pricing.

Getting Started Guide

Week 1: Foundation and First Scenario

Day 1-2: Account Setup and Exploration

1. Create Make account (start with free plan)
2. Complete the interactive tutorial scenarios
3. Explore the template library relevant to your use case
4. Connect your primary apps (CRM, email, Slack)
5. Review Make Academy training videos for fundamentals

Day 3-4: Build Your First Scenario

1. Start with a simple two-app integration (e.g., form to CRM)
2. Add a trigger module (webhook or scheduled)
3. Add an action module (create CRM contact)
4. Map data fields between apps
5. Test with sample data
6. Deploy and monitor first execution

Day 5-7: Add Complexity

1. Add a search module to check for duplicates
2. Implement a router with conditional paths
3. Add error handler to one module
4. Include data transformation (text formatting, date conversion)
5. Test multiple scenarios (success, duplicate, error cases)
6. Review execution history to understand data flow

Week 2: Intermediate Features

Filters and Routers:

1. Add filters to control when paths execute
2. Build a router with 2-3 conditional branches
3. Implement fallback logic for when conditions aren't met
4. Test all routing paths with varied data

Iterators and Aggregators:

1. Process an array of items using an iterator
2. Perform actions on each item in a loop
3. Use aggregator to combine results
4. Understand operation consumption in loops

Error Handling:

1. Attach error handlers to critical modules
2. Configure retry logic with backoff
3. Set up error notifications (Slack, email)
4. Create alternative paths when primary fails

Week 3-4: Production Deployment

Optimization:

1. Review operation consumption per scenario
2. Optimize scenarios to reduce operation count
3. Adjust scheduling to balance timeliness and cost
4. Implement execution filters to skip unnecessary runs

Monitoring and Maintenance:

1. Set up regular scenario health checks
2. Create alerts for error spikes or execution failures
3. Document scenarios for team knowledge sharing
4. Build a library of reusable scenario components

Best Practices for Sales Teams

Start with High-Impact, Low-Complexity: Your first production scenario should solve a painful manual process (like CRM data entry) while being simple enough to build confidently. Success builds momentum and organizational buy-in.

Monitor Operations Closely: Set calendar reminders to review operation consumption weekly for the first month. Understanding actual usage patterns prevents billing surprises and helps right-size your plan.

Build with Failure in Mind: Always add error handlers to critical scenarios. Assume APIs will fail, data will be malformed, and rate limits will be hit. Graceful failure handling is what separates hobby automations from production-grade workflows.

Document Your Scenarios: Add descriptive names to all modules and notes explaining complex logic. Your future self (or team members) will appreciate understanding what a scenario does without reverse-engineering it.

Version Control Your Workflows: Before making significant changes to working scenarios, clone them. Keep the original as a rollback option until the new version is proven stable.

Test with Edge Cases: Don't just test happy path data. Test with missing fields, unexpected formats, duplicate records, and null values. Production data is messy, and your scenarios must handle it.

FAQ

Make vs Zapier: Which is better for sales teams?

The answer depends on your automation complexity and technical comfort level. Choose Make if you need complex workflows with multiple conditional branches, sophisticated error handling, or extensive data transformation. Sales operations teams building scenarios like "enrich leads from multiple sources, score them, route based on criteria, update CRM, and alert sales selectively" will find Make's visual flowchart approach and advanced features invaluable. Choose Zapier if your needs are simpler: "when lead form submitted, create CRM contact and send Slack notification." Zapier's linear interface and faster learning curve make it better for straightforward trigger-action workflows. Many sales teams use both: Zapier for simple integrations, Make for complex orchestration. Cost-wise, Make often provides better value for complex scenarios (one comprehensive workflow vs multiple Zapier Zaps), while Zapier may be more economical for simple, high-volume automations.

What is the learning curve for Make?

Expect to invest 1-2 weeks to build basic scenarios competently: connecting apps, mapping data fields, adding simple filters, and deploying automations. Intermediate proficiency with routers, iterators, error handlers, and data transformation functions typically develops over 4-6 weeks of regular use. Advanced mastery—building complex multi-branch scenarios, optimizing operations, using HTTP modules for custom APIs, and implementing sophisticated error recovery—can take 2-3 months. Users with technical backgrounds or prior experience with workflow tools learn faster, while non-technical sales users may need ops support initially. Make provides excellent documentation, video tutorials, and an active community forum that significantly accelerate learning. The key insight: Make requires more upfront investment than Zapier but rewards that investment with capabilities that simpler tools can't match.

Are there execution limits or restrictions?

Yes, Make imposes several important limits that impact scenario design. Free plans restrict scenarios to run every 15 minutes minimum, paid plans enable intervals down to 1 minute. Each scenario has a maximum execution time (15 minutes for free, 40 minutes for paid plans), after which it's automatically terminated. Data transfer limits apply: free plans allow 100 MB per month, paid plans range from 100 MB to 1 TB depending on tier. Individual modules may have restrictions from the connected app (API rate limits, data volume caps). Most critically, scenarios consume operations based on module execution—processing arrays or looping through datasets can quickly exhaust your monthly allocation. There's also a 1 MB limit per operation for data transfer. For sales teams, these limits mean carefully architecting scenarios to batch process data efficiently, schedule appropriately, and monitor consumption. High-volume needs (processing thousands of records daily) may require higher-tier plans or alternative architectural approaches.

How does Make help with sales automation specifically?

Make excels at automating complex sales operations workflows that simple tools can't handle efficiently. Common sales use cases include: multi-source lead enrichment workflows that check Apollo, Clearbit, and LinkedIn Sales Navigator in sequence until data is found; intelligent lead routing that evaluates firmographic criteria, territory rules, and rep capacity before assigning; automated CRM hygiene that identifies duplicates, standardizes formats, and updates stale records; sales alert systems that filter for truly important events (high-value leads, competitor mentions, buying signals) rather than noisy notifications; and cross-platform reporting that aggregates data from CRM, outreach tools, and calendars into dashboards. Make's conditional routing means you can build one comprehensive workflow that handles all lead types (inbound, outbound, partner, event) with different processing paths rather than separate automations. The visual interface helps sales operations teams troubleshoot issues quickly and explain automation logic to stakeholders. Error handling ensures critical workflows don't silently fail and lose leads. Data transformation capabilities enable cleaning and formatting data to match CRM requirements without manual spreadsheet work.

Verdict

Make has established itself as the go-to visual automation platform for teams that need sophisticated workflow capabilities beyond simple trigger-action tools but aren't ready for enterprise-grade iPaaS platforms. The combination of visual flowchart design, robust error handling, powerful data transformation, and extensive app integrations makes Make particularly valuable for sales operations and RevOps teams orchestrating complex processes.

Choose Make if:

• You need complex workflows with conditional branching and multi-path logic
• Error handling and automation resilience are critical requirements
• Your team has technical resources comfortable with logical thinking
• You're willing to invest time learning in exchange for powerful capabilities
• Cost efficiency for complex scenarios is a priority
• Visual workflow understanding and debugging matter to your team

Look elsewhere if:

• You only need simple, linear trigger-action automations (consider Zapier)
• Non-technical users without ops support will build automations
• You require complete data sovereignty and on-premise hosting (consider n8n)
• You need enterprise governance and compliance (consider Tray.io)
• Your scenarios will process millions of operations monthly (evaluate enterprise platforms)

Make continues to innovate rapidly, expanding integrations, improving the builder interface, and adding features like better team collaboration and enhanced monitoring. For sales teams building their automation capabilities, Make offers the rare combination of power, flexibility, and accessibility. It's not the simplest tool, but for teams ready to invest in learning, it delivers automation capabilities that meaningfully improve sales operations efficiency and data accuracy.