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Version: 14.x

Create a Real-Time Data Aggregation with Fast Data Single Views

The Scenario​

A multi-brand retail company has its customer data spread across multiple, disconnected systems. This fragmentation makes it impossible to have a unified understanding of their customers' behavior and preferences.

The Challenge​

  • Data Silos:
    • Customer personal information (name, email) is in a Salesforce CRM.
    • Order history is in an e-commerce platform.
    • Product browsing history and marketing preferences are in a HubSpot marketing automation tool.
    • Development team activities and product releases are tracked in GitHub repositories.
    • Customer support tickets and issue tracking data are stored in Jira Service Management.
    • Cloud infrastructure logs and security events are scattered across AWS CloudTrail and Azure Activity Logs.
  • Inconsistent Customer Experience: When a customer calls support, the agent doesn't have a complete view of their recent orders or marketing interactions, leading to a frustrating and disjointed experience.
  • Ineffective Marketing Campaigns: The marketing team cannot create personalized campaigns because they cannot segment customers based on their combined purchase and browsing history.
  • Slow Batch Processes: The company has a nightly batch process that tries to unify this data in a data warehouse, but the information is always stale by up to 24 hours, making real-time personalization impossible.

The Solution with Mia-Platform​

The company leverages Integration Connector Agent and Fast Data Engine 2.0 to create a unified, real-time customer 360° view.

  1. External Data Ingestion: Integration Connector Agent connects to GitHub, Jira, AWS CloudTrail, and Azure Activity Logs, synchronizing development activities, support tickets, and infrastructure events directly into MongoDB collections.

  2. Real-Time Data Capture: Mongezium CDC captures changes from all data sources (CRM, e-commerce, marketing platforms, and external systems) and streams them to Kafka topics with high performance.

  3. Data Transformation and Aggregation: Farm Data combines multiple data streams into a unified customer profile, while Stream Processor enriches and transforms data using JavaScript logic.

  4. Unified Single View Creation: Kango persists the aggregated customer data to MongoDB, creating the customer_sv collection with complete 360° customer profiles that include traditional business data plus development activities, support interactions, and infrastructure insights.

  5. API Exposure: Modern REST APIs expose the unified customer single view, providing millisecond response times for applications requiring complete customer context.

The Outcome​

  • Comprehensive 360° Customer View: The company now has a single, real-time view combining traditional customer data with technical and operational insights. A document in the customer_sv collection might look like this: 
    {
      "email": "jane.doe@example.com",
      "name": "Jane Doe",
      "crm_info": { ... },
      "order_history": [ { ... }, { ... } ],
      "marketing_preferences": { ... },
      "support_tickets": [ { ... } ],
      "product_interactions": { ... }
    }
  • Personalized Customer Experience: The new customer support portal, built with Microfrontend Composer, calls the /customers-sv endpoint. When a customer calls, the support agent instantly sees their complete history, enabling personalized and efficient service.
  • Targeted and Effective Marketing: The marketing team can now run highly targeted campaigns. For example, they can create a segment of customers who have viewed a specific product category but have not made a purchase in the last 30 days.
  • Foundation for New Applications: The customer_sv becomes a valuable asset for the entire company. New applications, like a recommendation engine or a loyalty program app, can be built quickly on top of this reliable and real-time data source.

By leveraging Fast Data Single Views, the company broke down its data silos and transformed its fragmented data into a strategic asset, that is to say unified business data as a product. Single Views are easily discoverable, reusable and governed across all layers of the organization, enabling a new level of personalization and operational efficiency.