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What's going on today in MarTech in the enterprise?
This week I’m touching on building a fully composable MarTech or using a MACH approach for your MarTech stack.
Adopting a MACH Philosophy in MarTech: A Comprehensive Approach
Before I jump into solution mode, let me tell you a little bit about what I’m working on and why I believe it is important to share it.
I’m currently working with a start-up to build a platform to provide marketing and engagement solutions in the sports industry at a global scale!
This is complex, complicated, and above all, exciting. This type of solution can’t be approached using a traditional MarTech suite approach. It requires an architecture that allows for evolving requirements and flexibility only found in the micro-services world.
The world of MarTech, though advanced, is not fully MACH-ready. Most solutions are intended to work as standalone platforms, even when designed as open systems that provide connectors and APIs.
In this scenario, I’m working towards a solution to leverage the best solutions in the market that are open but also allow for flexibility and take us closer to a MACH-like architecture.
In the following sections, I’ll give you a high-level understanding of the areas I am looking at and this approach's principles and potential drawbacks.
The digital landscape is evolving unprecedentedly, and marketing technology (MarTech) is no exception. The traditional software suite-based ecosystems are increasingly being challenged by a more flexible, agile, and scalable approach: the MACH philosophy. MACH stands for Microservices, API-first, Cloud-native, and Headless. This approach offers a modular and decoupled architecture, allowing businesses to adapt more to changing requirements.
Transitioning from a suite-based MarTech ecosystem to one based on the MACH philosophy requires a systematic approach. Let me outline the adoption process, starting from data systems and moving through systems of insights, integration, record, and experience.
In today's digital age, customer experience (CX) has emerged as the primary differentiator for businesses. A CX-led architecture focuses on crafting seamless, personalized customer experiences across various touchpoints.
This necessitates an outside-in approach, where businesses design systems based on customer needs and behaviors rather than internal processes. The Engagement Fabric, a conceptual framework that stitches together all customer interactions, further emphasizes the need for a holistic view of the customer journey.
To effectively implement a CX-led architecture, an outside-in approach, and The Engagement Fabric, businesses require agility in their MarTech ecosystems. This agility, adaptability, and scalability can be effectively addressed by adopting the MACH philosophy.
1. Data Systems: The Foundation of MarTech
The first step in the transition is to re-evaluate the data systems. In a MACH architecture, data should be accessible, consistent, and real-time.
Decentralize Data Storage: Instead of a monolithic database, consider adopting microservices that handle specific data domains. This ensures that each service is scalable and maintainable independently.
API-first Approach: Ensure data can be accessed and manipulated through well-defined APIs. This not only ensures data consistency but also facilitates integration with other systems.
2. Systems of Insights: Gaining a Competitive Edge
With data systems in place, the next step is to derive actionable insights.
Real-time Analytics: MACH architecture supports real-time data processing. Tools like Apache Kafka or AWS Kinesis can be integrated to process data streams and provide real-time insights.
Machine Learning and AI: With data available through APIs, it becomes easier to feed machine learning models and derive predictive insights, enhancing personalization and customer engagement.
3. Systems of Integration: Bridging the Gaps
One of the main advantages of the MACH philosophy is the ease of integration.
Event-driven Architecture: Adopt an event-driven approach where systems communicate based on events rather than direct calls. This ensures scalability and resilience.
Standardized APIs: Ensure all internal or third-party services communicate using standardized APIs. This reduces integration complexity and ensures data consistency.
4. Systems of Record: Ensuring Data Integrity
MACH philosophy emphasizes the importance of maintaining a single source of truth.
Decoupled Architecture: By decoupling systems of record from other systems, you maintain data integrity. Any changes in one system don't directly impact others.
Immutable Data Storage: Consider adopting immutable data storage practices. This ensures that it cannot be changed once data is written, ensuring data integrity and traceability.
5. Systems of Experience: Enhancing Customer Engagement
The final step in the transition is to focus on the systems of experience.
RT DXP: Adopt an RT DXP that separates the content and presentation layers. This allows for flexibility in delivering content across multiple channels and adapts to changes across source systems to deliver digital experiences.
Individualization: With data and insights in place, focus on delivering individualized experiences to users. This can be achieved through AI-driven recommendation engines or personalized content delivery.
Potential drawbacks of MACH in MarTech
While the MACH philosophy offers numerous advantages, especially in terms of agility and scalability, there are potential drawbacks when viewed from a marketer-friendly perspective:
1. Complexity: The decoupled nature of MACH can introduce complexity, especially for marketers who are accustomed to suite-based solutions where everything is integrated. This can lead to a steeper learning curve.
2. Dependency on Developers: MACH ecosystems can be more developer-centric. Marketers might depend more on IT teams for even minor changes, potentially slowing down campaign rollouts.
3. Integration Challenges: While MACH promotes easy integrations through APIs, the reality is that integrating multiple microservices or tools can sometimes lead to unforeseen challenges, especially if they are from different vendors.
4. Cost Overruns: The flexibility to choose best-of-breed solutions for each function can sometimes lead to increased costs, as businesses might end up paying for overlapping features across different tools.
5. Potential for Silos: If not implemented correctly, the MACH approach can lead to data silos, where information is trapped within specific microservices. This can hinder a unified view of the customer, which is crucial for effective marketing.
Transitioning to a MACH philosophy in MarTech is not just about adopting new technologies; it's about embracing a new mindset. It's about understanding that flexibility, scalability, and adaptability are key in today's fast-paced digital world.
By focusing on data systems and moving through systems of insights, integration, record, and experience, businesses can ensure that they are not only keeping up with the competition but also setting themselves up for future success.
The MACH philosophy, emphasizing Microservices, API-first, Cloud-native, and Headless approaches, offers a promising pathway for businesses looking to be agile in their MarTech endeavors.
However, it's essential to balance the technical advantages with the potential challenges it might pose from a marketer's perspective. By being aware of these challenges and proactively addressing them, businesses can harness the full potential of MACH while ensuring that their marketing teams remain empowered and effective.
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