Becoming Customer-Centric Through the Power of MDM and Customer Intelligence
Master Data Management (MDM) is making a big impact in delivering real business value and allowing companies to unleash the power of their data across the enterprise. Because MDM solutions help business users to trust data across all systems in use, they can be applied to many data domains including customer intelligence (individual or organization), supplier, product, location, asset, and more. Master data typically consists of structured attributes that define an entity. For customer domains, this may include name, address, date of birth, contact information, account information, or other unique, industry-specific attributes.
The master data residing in different systems may have varying degrees of completeness, timeliness, and correctness. For example, a customer may be represented by first and last name in one system and have a middle initial in another, or one system may have email as primary contact, and another may have a phone number. In order to create a golden record of the customer, data stewards make decisions to match, merge, or update individual attributes of customer records. That golden record can then update source systems to create a trusted and consistent view that’s accessible and shared across all of a company’s systems, applications, and analytics.
Since no single approach to matching can anticipate all variations of data, a hybrid of matching algorithms that mimic an expert human user can be applied. These matching algorithms may be deterministic, heuristic, and / or probabilistic, and may be combined with other matching, evaluation, and search techniques to arrive at the most trusted view.
The ability to search for, evaluate, match and merge records is fundamental to the success and efficiency of operational processes such as demand planning, customer on-boarding, territory assignment, regulatory compliance. Marketing activities such as cross-sell/up-sell and campaign management in support of enterprise-level initiatives such as customer experience also benefit from having a single version of truth across different departments, brands, and systems.
Today, with big data and the increasing prevalence of unstructured sources of data, a complementary technology—one focused on customer insight and intelligence—has emerged. Customer intelligence systems (alternatively referred to customer intelligence platforms or customer data platforms) are intended to connect “things with customers.” Customer intelligence helps business users understand the context of customer behavior and intent through data. These systems are designed to enrich customer profiles with insights from master data as well as from non-master data (which includes unstructured data).
With customer intelligence systems, customer interaction data, along with behavior and intent insights, are contextually matched and synthesized with customer profiles, and multiple perspectives (n-perspectives) the customer profile are made available to meet the needs of the consumer of data. Perspectives are determined based on confidence thresholds set during matching, in accordance with how confident is the system that a piece of known or inferred information belongs to a specific customer. Customer intelligence systems power both operational and analytical use cases such as marketing transformation, personalized campaigns, omni-channel journey, and deep analytics such as next best action/offer/intention, churn risk, and others.
MDM and customer intelligence systems are complementary and, when combined, can propel forward an organization’s overall digital transformation to become customer-centric. To learn more about the Informatica end-to-end MDM portfolio, watch this on-demand discussion of how AI-powered customer 360 solutions can synthesize data, identify relationships, and deliver business insights intelligently and at scale.
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