Why Companies Are Rebuilding Their Tech Stacks From Scratch
The real story behind the shift to modular technology and what it means for customer experience
Companies are scrapping their expensive, all-in-one software platforms and rebuilding everything with smaller, specialized tools.
It sounds backwards, but it's actually solving a problem that's been plaguing businesses for years: how to deliver personalized experiences without violating customer privacy.
The Monolith Problem
Most companies built their digital infrastructure around massive, integrated platforms. Think Salesforce for everything customer-related, or Adobe for all marketing needs. These systems promised to do everything in one place.
The reality was different. When you needed to add new capabilities, you had to wait for the vendor to build them. When regulations changed, you were stuck with whatever privacy controls the platform provided. When customer expectations evolved, you moved at the speed of the slowest component.
Meanwhile, customer data lived in these vendor-controlled environments, making it difficult to ensure compliance with privacy laws or create truly personalized experiences.
Enter MACH Architecture
MACH stands for Microservices, API-first, Cloud-native, and Headless. It's a way of building technology systems using small, specialized components that work together through standardized connections.
Instead of one giant platform handling everything, companies use best-of-breed tools for specific functions. A specialized personalization engine connects to a separate content management system, which connects to a dedicated email platform, all coordinated through APIs.
This modular approach solves several problems at once. Companies can swap out components without rebuilding everything. They can ensure data stays where they want it. They can respond quickly to new privacy requirements or customer needs.
The Personalization Privacy Balance
Here's where things get interesting. Privacy laws like GDPR and CCPA require companies to give customers control over their data. At the same time, customers expect personalized experiences based on that data.
Traditional platforms handle this poorly. Data processing happens inside vendor systems, making it difficult to provide transparency or granular control. Customers can't easily see how their information is being used or choose specific types of personalization.
MACH architecture changes this dynamic. Companies can build privacy controls directly into their data layer, giving customers precise control over how their information is used. A customer might allow purchase history to inform product recommendations but prevent that same data from being used for email marketing.
Real-World Applications
E-commerce companies are using MACH to create shopping experiences that adapt in real-time while giving customers clear choices about data usage. Instead of generic product pages, they can show different content based on browsing history, but only with explicit consent for each use case.
Media companies are building personalized content feeds that comply with privacy laws in multiple countries. The modular architecture makes it easy to apply different privacy rules based on where the customer is located, without rebuilding the entire system.
Financial services firms are creating custom digital banking experiences that meet strict regulatory requirements while still providing personalized financial advice and product recommendations.
Why 60% Will Make the Switch
Industry analysts predict that 60% of new commerce solutions will adopt composable (MACH-based) technology by 2027. Several factors are driving this shift:
Regulatory Pressure: Privacy laws are getting stricter, and enforcement is ramping up. Companies need technology that can adapt quickly to new requirements.
Customer Expectations: People want personalized experiences, but they also want control over their data. MACH architecture makes it possible to deliver both.
Competitive Pressure: Companies using monolithic platforms can't move fast enough to keep up with more agile competitors.
Cost Efficiency: While MACH systems require more upfront planning, they often cost less over time because companies only pay for the components they actually use.
The Technical Reality
Building MACH systems isn't trivial. Companies need strong technical teams capable of integrating multiple systems and managing API connections. They need clear data governance policies and robust security practices.
However, the ecosystem is maturing rapidly. Specialized vendors are emerging to handle specific components of MACH architectures. Integration platforms are making it easier to connect different systems. Cloud providers are offering tools specifically designed for composable architectures.
Data Sovereignty Benefits
One of the biggest advantages of MACH architecture is data sovereignty—the ability to control where data lives and how it's processed. This matters for several reasons:
Regulatory Compliance: Companies can ensure data processing happens in specific geographic regions to comply with local laws.
Customer Trust: When customers can see exactly how their data is being used and have granular control over permissions, trust increases.
Business Flexibility: Companies aren't locked into vendor-specific data formats or processing rules, making it easier to adapt to changing business needs.
Implementation Challenges
The shift to MACH isn't without challenges. Companies need to rethink their technology teams, often requiring new skills in API management and microservices architecture. Integration complexity increases, at least initially.
Many organizations are taking a gradual approach, replacing components of their monolithic systems piece by piece rather than attempting a complete overhaul. This allows teams to build expertise while minimizing disruption.
The Vendor Ecosystem Response
Traditional platform vendors are responding to the MACH trend by offering more modular versions of their products. Some are embracing the shift, while others are fighting it by emphasizing the convenience of integrated platforms.
New vendors are emerging specifically to serve the MACH ecosystem. These companies focus on single functions—personalization, content management, or customer data platforms—but design their products to integrate seamlessly with other tools.
Measuring Success
Companies adopting MACH architecture typically measure success differently than those using monolithic platforms. Instead of focusing on feature adoption within a single platform, they look at:
Time to Market: How quickly can new capabilities be added or modified?
Privacy Compliance: How effectively can the system respond to privacy requests and regulatory changes?
Customer Satisfaction: Are customers getting more relevant experiences while feeling confident about data privacy?
System Performance: Do the individual components perform better than the all-in-one alternative?
Looking Ahead
The trend toward MACH architecture represents more than just a technology shift. It reflects changing expectations about data privacy, customer control, and business agility.
Companies that master this approach will have significant advantages. They can respond quickly to regulatory changes, experiment with new customer experiences, and adapt to evolving privacy expectations. Those that stick with monolithic platforms may find themselves increasingly constrained.
The 60% adoption prediction for 2027 might actually be conservative. As privacy regulations tighten and customer expectations continue to evolve, the flexibility provided by MACH architecture is becoming less of a nice-to-have and more of a business necessity.
The question isn't whether this shift will happen—it's already underway. The question is whether companies will lead the transition or be forced into it by competitive pressure.
Sources: Industry research from Gartner, Forrester, and composable commerce technology vendors.