Lindy vs Make
Last updated: April 2026 · By AI-Ready CMO Editorial Team
AI Marketing Automation
Lindy vs Make — Feature Comparison
| Feature | Lindy★ Winner | Make |
|---|---|---|
| Category | AI Marketing Automation | AI Marketing Automation |
| Pricing | Premium ($99-299/mo depending on workflow complexity and data volume) | Freemium: Free tier (1,000 ops/mo), Standard ($9.99/mo), Pro ($18.99/mo), Business ($299/mo), Enterprise (custom) |
| Overall Score | 7.6/100 | 7.6/100 |
| Strategic Fit | 8.2/10 | 8.2/10 |
| Reliability | 7.4/10 | 7.8/10 |
| Integration | 8.1/10 | 8.5/10 |
| Scalability | 7.9/10 | 7.9/10 |
| ROI | 7.8/10 | 7.3/10 |
| User Experience | 7.5/10 | 7.5/10 |
| Support | 7.2/10 | 7.1/10 |
| Best For | Mid-market B2B SaaS companies with 15+ marketing tools, Marketing operations teams without dedicated engineers, Organizations needing AI-driven workflow logic beyond simple integrations | Mid-market and enterprise marketing teams managing 10+ integrated tools, Marketing operations leaders needing complex, conditional automation workflows, Teams with high-volume lead processing or multi-channel campaign coordination |
| Top Strength | Natural language workflow builder reduces technical barriers—marketers can describe automations conversationally rather than mapping data fields manually. | Exceptional data transformation capabilities with JSON parsing, array handling, and conditional logic built directly into workflows—eliminates need for external middleware or custom code |
| Main Limitation | Pricing scales with workflow complexity, making it expensive for teams running dozens of automations; total cost of ownership can exceed $500/mo for large operations. | Steep learning curve compared to Zapier—the module-based paradigm and operation counting require training; free tier insufficient for testing complex workflows at scale |
Strategic Summary
Overview
Lindy and Make represent two fundamentally different approaches to marketing automation: Lindy is an AI-native workflow platform built from the ground up for autonomous agents, while Make is a visual integration platform that has added AI capabilities to its existing connector ecosystem. For CMOs evaluating these tools, the choice hinges on whether your team needs autonomous AI workers handling repetitive marketing tasks end-to-end, or a flexible integration hub that connects your existing martech stack with AI-assisted workflows.
Lindy positions itself as the "AI employee" for marketing operations. It excels when you need autonomous agents to handle email sequences, lead qualification, content distribution, and customer outreach without human intervention at each step. The platform is purpose-built for teams that want to delegate entire workflows to AI—set parameters, define success criteria, and let Lindy execute independently. This approach works best for mid-market and enterprise marketing teams with high-volume, repetitive tasks and the operational maturity to monitor AI performance. Lindy's strength is in reducing human touchpoints; its weakness is that it requires more upfront configuration and assumes your team is comfortable with AI autonomy.
Make (formerly Integromat) is a visual workflow automation platform that connects 1,000+ applications through a drag-and-drop interface. It's ideal for marketing teams that already have a complex martech stack and need to orchestrate data flow between tools—Salesforce to HubSpot, Slack to email, form submissions to CRM. Make's recent AI additions help with data transformation and content generation, but the platform's core strength remains integration and conditional logic. Choose Make if your bottleneck is connecting disparate systems; choose Lindy if your bottleneck is human time spent on repetitive marketing tasks.
Our Recommendation: Lindy
For pure marketing automation and AI autonomy, Lindy wins because it's purpose-built for autonomous agents handling end-to-end workflows without human intervention. However, Make wins for organizations with complex martech stacks requiring deep integrations—it's the better choice if your challenge is connecting tools, not replacing human effort.
Choose Lindy when...
Choose Lindy if your team is drowning in repetitive marketing tasks (email sequences, lead scoring, outreach follow-ups) and you have the operational maturity to define clear success metrics for AI agents. Lindy is ideal for teams with high-volume, rule-based workflows where autonomy reduces headcount pressure.
Choose Make when...
Choose Make if your marketing tech stack is fragmented across multiple platforms and you need reliable data orchestration between systems. Make is the better fit if your primary pain point is integrating Salesforce, HubSpot, Slack, and custom tools—not automating individual marketing tasks.
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Score Breakdown
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Lindy vs Make — FAQ
What marketing tasks can AI automate?
AI can automate 40-60% of marketing tasks, including email campaigns, social media posting, content creation, lead scoring, ad optimization, customer segmentation, reporting, and personalization. Most CMOs report saving 10-15 hours per week per team member using AI automation tools.
Read full answer →How to choose the right AI marketing tools?
Evaluate AI marketing tools across 5 key dimensions: your specific use case (content, analytics, personalization), integration with existing martech stack, cost vs. ROI, ease of implementation (days vs. months), and vendor stability. Start with a pilot program in one department before full rollout.
Read full answer →How much time does AI save marketers?
AI saves marketers 5-10 hours per week on average, with the largest time savings in content creation (40% of tasks), email marketing (35%), and data analysis (30%). The actual time saved depends on your tech stack, team size, and which marketing functions you automate first.
Read full answer →How to create an AI marketing workflow?
Build an AI marketing workflow in 5 steps: identify repetitive tasks, select AI tools (ChatGPT, HubSpot AI, Jasper), map your process, integrate with existing systems, and test with one campaign before scaling. Most teams see 30-40% time savings within 60 days of implementation.
Read full answer →How to integrate AI tools with your existing martech stack?
Start by auditing your current martech stack, identify 1-2 high-impact use cases (email personalization, lead scoring, content optimization), then choose AI tools with native integrations via APIs or middleware platforms like Zapier. Most integrations take 2-4 weeks and cost $500-$5,000 depending on complexity and data volume.
Read full answer →Still deciding?
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