Customer Data Management

Customer Data Management refers to applications that store data and metadata about customers, members, citizens or any type of user. It encompasses a variety of applications, like subscriber data management, customer relationship management (CRM), gaming user profiles, biometrics, identity and access management (IAM), and enterprise resource planning (ERP).

Business Outcome

Traditional Customer Data Management applications help businesses keep track of their customers, provide basic customer service or support basic user access to applications. Today, however, leading organization are using MongoDB to create new solutions that drive:

  • Differentiated customer service and reduced churn, like MetLife’s 360-degree view of the customer;
  • Upsell and cross-sell opportunities, like Gilt Groupe’s carefully segmented daily digests;
  • Improved targeting and insight about customer behavior, eHarmony’s singles matching algorithm.

Customer Examples


Challenge

  • Agility. Yesterday you only knew basic information about your customers. Today you know their Twitter handles and location. While you may want to change your application to capture and act on new customer data, relational databases do not lend themselves to this type of iterative development.
  • Structured and Unstructured Data. It is hard to manage traditional structured customer data -- like names, addresses and logins -- as well as new contextual data -- like purchasing behavior and brand preferences -- in a single data store.
  • Real-Time and Historical Analysis. Analyzing customer behavior and putting it to use in real-time (e.g., via real-time offers) is no simple task.
  • Scalability. Accomplishing this for large, global user bases -- like MetLife’s 100M+ customers -- only compounds these challenges.

Why MongoDB

  • Dynamic schemas in MongoDB provide a simple way to stay agile and incorporate changes to the database as you evolve your application.
  • Documents in MongoDB lend themselves to storing structured and unstructured customer data in a single data store.
  • Rich query language, indexing and analytics enable applications to provide actionable user data in real-time.
  • Horizontal Scaling allows customers to support massive, global user bases.

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