MarTech Architecture: A Blueprint Overview of Marketing Technology Solution

The Martech architecture is an essential framework for modern marketing, integrating various tools and technologies to enhance marketing strategies and operations. This white paper provides an overview of Martech architecture, detailing each component and the available tools for implementation. It serves as a blueprint for organizations looking to optimize their marketing technology stack.

Quick Intro:

Based on experience over the last decade, the rapid evolution of digital marketing has necessitated the development of sophisticated marketing technology (Martech) architectures. These architectures enable organizations to seamlessly integrate multiple marketing tools, automate processes, and gain insights from data analytics. This white paper aims to outline the key components of Martech architecture and provide a detailed examination of the tools available for each component, facilitating informed decisions for effective implementation.

The purpose of this white paper is to provide a structured framework for understanding Martech architecture and to identify the most suitable tools for each component. This will assist organizations in building an efficient and cohesive Martech stack.

Martech architecture typically comprises several key components but i would like to divided in to 5 pillars, each addressing a specific aspect of marketing. These pillars include:

Touch points: Touchpoints are all the places where the customer comes into contact with any company, i.e. website, online shop, apps, etc. Because the important information flows here, there is also a lot to bear in mind with regard to data protection and CCPA. Especially as concerns the central services of consent management, identity & access management and loyalty, you must be able to inform customers at any time about the data which you have saved about them, and how you use these data. In addition, customers must be able to view and change their loyalty points and data, for example, via a self-service function such as “My account” — only this will give them the feeling of an optimal customer experience

Core Systems: To allow disclosure and accounting, all this information at touch points should also be present in upstream operational systems such as Payments, PIM, Catalog, Products, pricing, promos, CRM, call centre or an ERP system. The operational systems collect individual information such as master data, transactions, orders, permissions, etc., bring them together to provide a 360° view, perform analyses and only thus create real added value for your company

Data & Analytics: All this information is ultimately used in the data & analytics section, for example, in an upstream data lake. By analyzing customer profiles, forming statistical affinities, scoring and segmentation, and with the aid of artificial intelligence or machine learning, campaigns and target groups or their segments can be created and optimized precisely. Marketing automation comprises one of the most important use cases for the described 360° view. It utilizes consolidated information consisting of master data, purchasing behavior, as well as data on clicks, permissions and responses to enrich automated campaign processes for customer-specific communication.

Decision: Decision here signifies the section in which marketing automation is used to decide which customer should be contacted with which offer via which channel with which incentive at what time of day etc. Furthermore, the workflow module or campaign designer is used to model the steps which customers are meant to go through within the campaign. Do they first receive an e-mail or push-message on their app? What would be the best time for further contacting, for example, for re-targeting after a shopping cart cancellation? How long should I wait to send a follow-up campaign to a customer? Does the customer react to personalized offers in the e-shop more readily than to push-messages in the mobile app? Such decisions are then made in the delivery & channels section.

Delivery & Communication: Sending an email or text to customers is easy, it doesn’t require an extensive MarTech architecture. But if you wish want to reap the rewards of the above work in the other sections and precisely address customers on the basis of these findings, you then find yourself in the delivery & channels section. Now a 360° view of customers also proves its worth via CDP: Click data, redemption of coupons, purchases, opening rates — all this shows you the history, preferences and behavior of your customers. Via the connected channels, you can accordingly broadcast personalized campaigns to your customers, test A/B variants and perform renewed measurements, or broadcast special product recommendations. Only a holistic view of the customer allows you to compile all knowledge and perform the correct derivations — and thus increase your campaign’s long-term monetary success.

Components includes

2.1. Data Management

Data management is the foundation of Martech architecture, involving the collection, storage, and processing of marketing data. Tools for data management include:

Data Warehouses

1. Snowflake: A cloud-based data warehousing solution known for its scalability and performance.

2. Google BigQuery: A fully-managed, serverless data warehouse that allows for super-fast SQL queries using the processing power of Google’s infrastructure.

3. Amazon Redshift: A fast, fully-managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.

Data Lakes

1. Amazon S3 (Simple Storage Service): A scalable object storage service used for storing and retrieving any amount of data at any time, from anywhere on the web.

2. Azure Data Lake: A scalable data storage and analytics service that allows developers to perform data analysis on huge volumes of data.

3. Apache Hadoop: An open-source software framework used for distributed storage and processing of large data sets using the MapReduce programming model.

ETL Tools (Extract, Transform, Load)

1. Talend: An open-source data integration platform that provides tools for data integration, data management, data preparation, and more.

2. Apache Nifi: An easy-to-use, powerful, and reliable system to process and distribute data.

3. AWS Glue: A fully managed ETL service that makes it easy to move data between data stores.

4. Apache Airflow: An open-source tool to programmatically author, schedule, and monitor workflows.

5. Pentaho Data Integration (PDI): An open-source ETL tool that enables the transformation of data.

Data Processing Engines

1. Apache Spark: An open-source unified analytics engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning, and graph processing.

2. AWS EMR (Elastic MapReduce): A cloud-native big data platform that allows for running large-scale distributed data processing jobs, such as those using Apache Spark, Apache Hadoop, and other frameworks.

3. Apache Flink: An open-source stream processing framework for distributed, high-performing, always-available, and accurate data streaming applications.

Data Orchestration

1. Kubernetes: An open-source system for automating deployment, scaling, and management of containerized applications.

2. AWS Step Functions: A serverless orchestration service that makes it easy to coordinate multiple AWS services into serverless workflows.

Data Governance and Quality

1. Apache Atlas: An open-source metadata management and data governance platform.

2. AWS Lake Formation: A service that makes it easy to set up a secure data lake in days.

3. Apache Ranger: An open-source project that provides data security across the Hadoop ecosystem.

2.2. Customer Relationship Management (CRM)

CRM systems are essential for managing interactions with current and potential customers. They provide a centralized platform for sales and customer service teams. Key CRM tools include:

• Salesforce

• HubSpot

• Microsoft Dynamics 365

2.3. Content Management Systems (CMS)

CMS platforms are used to create, manage, and optimize digital content. They are crucial for content marketing strategies. Prominent CMS tools include:

• Adobe Experience manager

• Drupal

2.4. Marketing Automation

Marketing automation tools streamline marketing tasks and workflows, enhancing efficiency and personalization. Leading tools in this category are:

• Marketo

• Pardot

• Adobe campaign Standard/Classic

• Mail chimp

2.5. Analytics and Business Intelligence (BI)

Analytics and BI tools provide insights into marketing performance and customer behavior, driving data-driven decision-making. Essential tools include:

• Google Analytics

• Adobe analytics

• Tableau

• Power BI

2.6. Customer Data Platforms (CDP)

CDPs collect and unify customer data from various sources, enabling personalized marketing at scale. Key CDP solutions are:

• Segment

• Adobe Experience platform

• Treasure Data

• ActionIQ

• Tealium

2.7. Social Media Management

Social media management tools facilitate the planning, scheduling, and analysis of social media activities. Popular tools include:

• Hootsuite

• Buffer

• Sprout Social

2.8. Advertising Technology (AdTech)

AdTech tools manage and optimize digital advertising campaigns across multiple channels. Prominent AdTech solutions are:

• Google Ads

• Adobe audience manager

• Facebook Ads Manager

• The Trade Desk

Let say if we want to build a MarTech infrastructure for any company, I would recommend that you plan and design it precisely in order to be successful. The most important consideration here: Which architecture matches your company’s maturity? Because especially at the beginning, you might not need all functions, and can prioritize and scale as desired.

One should therefore begin with a realistic analysis of campaigns, processes and existing systems. Ask yourself: What are the strategic objectives? Can existent systems and data be used? Is there already a data lake or a customer-centric data mart in the company? Does the marketing automation solution currently in use meet my future requirements? If not, which future solution will suit me? Which channels do I currently use, and which ones will I have to add later?

This initial effort is worth it — don’t shy away from it, and obtain support for this phase. Because once your MarTech architecture is in place, you are ideally equipped to enhance your customers’ experience at the touch points noticeably, and to utilize their buying and clicking behavior to optimize your marketing — demonstrating that your customers are not mere data points, but visitors and interested parties with specific needs.

Author: Tharun Mittapalli

Enterprise architect and engineering leader. Expert in building scalable applications in most of domains like Retail, pharmacy, Ecommerce, Banking, Finance.