Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last year, I spent three weeks building a custom integration between a client's SaaS platform and their CRM system. The integration worked beautifully—for exactly two months. Then the CRM updated their API, everything broke, and I found myself maintaining digital infrastructure instead of growing their business.
That's when I realized the uncomfortable truth: most startups are building custom integrations when they should be treating platforms like Lego blocks. We're so focused on having "perfect control" that we're creating maintenance nightmares that drain time and resources from what actually matters—serving customers.
After working with dozens of SaaS companies and e-commerce brands, I've learned that the best SaaS growth strategies aren't about building everything from scratch. They're about smart platform orchestration that scales without breaking your team.
Here's what you'll learn from my platform integration experiments:
Why "best practices" for custom integrations often create more problems than they solve
The platform-first approach that saved my clients hundreds of hours in maintenance
How to choose between Zapier, Make, and N8N based on your actual needs (not the hype)
The framework I use to evaluate when custom builds are actually worth it
Real examples of platform orchestration that drove measurable business results
Industry Reality
What every startup thinks they need
Walk into any startup accelerator and you'll hear the same advice: "Build your integrations in-house for maximum control." The conventional wisdom goes something like this:
The Standard Integration Playbook:
Custom API Development: Build direct API connections between your systems for "better performance"
In-House Maintenance: Keep everything under your control to avoid vendor lock-in
Real-Time Everything: Prioritize instant data sync over practical business outcomes
Perfect Documentation: Maintain comprehensive integration docs (that nobody reads)
Future-Proof Architecture: Build for theoretical scale rather than current needs
This advice exists because it feels logical. Custom integrations give you complete control, perfect optimization, and the satisfaction of building exactly what you want. It's engineering porn—beautiful to look at, impressive to discuss, and completely divorced from business reality.
The problem? Most startups don't have Google's engineering resources. When your integration breaks at 2 AM (and it will), you're not calling a 24/7 infrastructure team. You're debugging API calls while your sales team can't access customer data and your e-commerce orders aren't syncing to fulfillment.
What the industry doesn't tell you is that platform-based integrations have evolved dramatically. Modern integration platforms handle error handling, retry logic, data transformation, and monitoring better than most custom solutions. But admitting this means admitting that maybe you don't need to build everything yourself.
The real question isn't "Can we build this integration?" It's "Should we be spending our limited time and resources on integration maintenance instead of product development?"
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The wake-up call came during a project with a B2B startup that had built their entire system on custom integrations. Their CRM talked to their email platform, which connected to their analytics tool, which fed data to their billing system. Everything was custom-coded, perfectly optimized, and completely brittle.
When I started working with them, they were spending 40% of their development cycles just maintaining integrations. Not building new features, not improving user experience—just keeping the digital plumbing from exploding. Their head of engineering looked exhausted every time we talked about adding a new tool to their stack.
The breaking point came when Salesforce updated their API (again), and suddenly their entire customer onboarding workflow stopped working. Deals were stuck in limbo, customer success couldn't access account data, and the team spent three days rebuilding what should have been a simple data sync.
That's when I proposed something that made the founders uncomfortable: "What if we stopped building integrations and started orchestrating platforms instead?"
The resistance was immediate. "But what about performance?" "What about customization?" "What about vendor lock-in?" All valid concerns that completely missed the bigger picture—they were optimizing for theoretical problems while ignoring the very real problem of integration maintenance consuming their roadmap.
I convinced them to run an experiment. Instead of rebuilding their broken Salesforce integration, we'd use an automation platform to handle the connection. If it worked for their most critical workflow, we'd consider platformizing other integrations.
The team was skeptical, but desperate enough to try. That experiment became the foundation for everything I now recommend about cross-platform integrations. Sometimes the best engineering decision is to stop engineering and start orchestrating.
Here's my playbook
What I ended up doing and the results.
The experiment started with their most broken integration: syncing new deals from Salesforce to their onboarding system. Instead of rebuilding the custom API connection, I set up the entire workflow using Make.com (formerly Integromat).
The Platform-First Integration Approach:
Step 1: Audit Current Integration Pain Points
First, I mapped every integration they had and tracked how much development time each one consumed monthly. The results were shocking—they were spending more time on integration maintenance than on core product features.
Step 2: Choose the Right Platform for Each Use Case
After testing multiple automation platforms with their workflows, I developed a decision framework:
Zapier: Perfect for simple, linear workflows where ease of use matters more than complex logic. Their team could actually use it without calling me every time something needed tweaking.
Make.com: Ideal for complex workflows with conditional logic and data transformation. More powerful than Zapier, still manageable for non-developers.
N8N: Self-hosted option for sensitive data or complex custom logic, but requires more technical knowledge to maintain.
Step 3: Build Integration Templates, Not One-Off Solutions
Instead of creating unique integrations for every use case, I built reusable workflow templates that could handle variations in data structure and business logic. This meant less maintenance and faster deployment of new integrations.
Step 4: Implement Proper Error Handling and Monitoring
One advantage of platform-based integrations? Built-in monitoring and error handling that's actually better than what most custom solutions provide. No more 2 AM debugging sessions when an API endpoint changes.
Step 5: Document the Business Logic, Not the Code
Instead of maintaining technical documentation that gets outdated, I focused on documenting the business processes these integrations supported. When someone needed to understand why data flowed a certain way, they could reference business logic rather than trying to decode custom API calls.
The key insight was treating integrations like business processes rather than technical challenges. When you think about connecting your CRM to your email platform, you're not just moving data—you're automating a business workflow that has specific requirements, edge cases, and success criteria.
Template Library
Built reusable workflow templates instead of one-off custom integrations, reducing deployment time from weeks to hours
Error Handling
Platform-based solutions provided better monitoring and automatic retry logic than our custom implementations
Team Independence
Marketing and ops teams could modify workflows without engineering support, removing development bottlenecks
Cost Analysis
Platform subscription costs were 70% less than the engineering time spent maintaining custom integrations
The results completely changed how this startup approached integrations:
Development Velocity: Engineering team went from spending 40% of their time on integration maintenance to less than 5%. They could finally focus on core product development instead of digital plumbing.
Reliability: Platform-based integrations had built-in retry logic and error handling that proved more robust than their custom solutions. Fewer midnight emergency calls about broken data syncs.
Team Autonomy: Marketing and operations teams could modify workflows themselves using visual interfaces. No more engineering tickets for simple automation changes.
Faster Integration Deployment: New integrations went from taking 2-3 weeks of development time to being deployed in a few hours using existing templates.
Better Documentation: Visual workflows were self-documenting in a way that custom code never was. New team members could understand data flows without digging through technical specifications.
Six months later, they'd migrated 80% of their integrations to platform-based solutions and hadn't looked back. The head of engineering actually thanked me for giving him his weekends back.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
The biggest lesson? Integration complexity should match business complexity, not technical capability.
Key insights from this platform integration experiment:
Maintenance costs compound: Every custom integration becomes technical debt that grows over time. Platform solutions transfer that maintenance burden to companies whose core business is integration reliability.
Perfect is the enemy of functional: Custom integrations optimized for theoretical performance often fail at basic reliability. Platform solutions prioritize uptime over millisecond improvements.
Team velocity matters more than technical purity: When non-technical teams can modify workflows themselves, the entire company moves faster. Code-based integrations create bottlenecks.
Error handling is harder than it looks: Platform-based solutions have already solved edge cases you haven't encountered yet. Their retry logic and monitoring capabilities are better than most custom implementations.
Scale when you need to, not when you think you might: Build for your current problems, not theoretical future ones. Platform solutions can handle significant scale before becoming limiting factors.
Documentation lives in the workflow: Visual automation tools are self-documenting in ways that API code never is. This matters more as teams grow and change.
Integration platforms are infrastructure: Treat automation tools like you treat AWS—as foundational infrastructure that enables your business rather than vendor lock-in to avoid.
The uncomfortable truth: most custom integrations are built to satisfy engineering preferences, not business needs. Platform-first integration strategies let you focus on what actually differentiates your product.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups, platform integrations mean:
Faster time-to-market for new feature integrations
Non-technical teams can manage customer onboarding automation
Built-in compliance and security features for enterprise customers
For your Ecommerce store
For e-commerce stores, this approach enables:
Automatic inventory sync across multiple sales channels
Customer data orchestration between CRM, email, and fulfillment systems
Seasonal workflow modifications without developer involvement