Marketers are advancing toward personalized customer-focused strategies and experiences. A comprehensive identity resolution foundation built across first-, second-, and third-party sources are necessary to connect all relevant customer data and inform experiences. In this article, Matt Austin, vice president, identity management, Merkle, examines the core identity principles necessary for marketers to connect their data across a range of sources.
For nearly a year, organizations have been scrambling to adjust to the headwinds brought on by the global pandemic. These foreboding conditions have forced many businesses to rethink their technology and data platforms to enable business agility. Optimization and modernization of technology and data assets are now front and center to business success.
In parallel, many marketers are also trying to solve for the rapidly changing data and identity landscape. Third-party cookies are evaporating, privacy legislation is on the rise, and organizations are pivoting their focus toward their own customer data management capabilities. These changes are modernizing yesterday’s platforms into agile, cloud-based, scalable, and accessible platforms for all users.
Connecting all the data into a singular asset is critical to enabling and optimizing the modern data platform. Connecting the data allows technical integration while promoting the organizational growth and application of owned first-party data. Identity resolution provides the means to connect first-, second-, and third-party data into a unified organizational asset known as the private identity graph. The private identity graph is plugged into orchestration and activation platforms to provide the insights and connections in the data necessary to deliver personalized customer experiences.
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This article will examine four key principles to consider when connecting customer data in today’s modern data platform.
1. Assess the Data
Connecting the data properly into a well-organized data asset requires planning and strategy — both technical and business-focused. Organizations need to invest in a thorough assessment of all available data across first-, second-, and third-party sources. Data characteristics such as volume, velocity, attributes, privacy/compliance requirements, and other business rules need to be captured and synthesized into concise requirements. These requirements support technical engineering and integration design, maintenance, and accessibility. Additionally, business users will need to strategize on optimally applying the connected data asset to deliver personalized experiences and value to the customer.
2. Apply Identity Resolution
Properly connecting the data at the customer level requires an identity resolution process. Consider an identity solution that can provide data quality capabilities to cleanse, correct, and enhance your customer’s personally identifiable information (PII). Identity resolution solutions need to resolve data to a person- and household-level to provide a basis for customer data integration, aggregation and insights, and activation. Identity solutions underpinned with a high-quality, person-based truth set will enhance identity accuracy and sustainability. The identity resolution solution should manage both offline and online identity signals in a privacy-compliant manner. Many identity solutions also provide portability into third-party data capabilities and person-based channel and media activation capabilities. A careful evaluation of identity resolution options will help select the right tool for your business. Be sure to consider the breadth of capabilities, time to market, and overall investment as key inputs into the decision.
3. Establish the Private Identity Graph
The identity resolution outcome connects the data to support both business and technical use cases. Companies are making identity resolution outcomes accessible to their users by creating of their own private identity graphs. The private identity graph organizes the data into a master data asset accessible across the organization to identify and connect customer data. The private identity graph enables organizations to take control of their owned customer data, enhance it with relevant second- and third-party data, and apply the intelligence to fuel customer experiences. The private identity graph is built upon a foundation of stable, person-level data at the core. Identity key associations are then created for all signals, including PII (e.g., emails, phones, addresses), digital identifiers, native platform identifiers, and relevant connections to partner systems. The private identity graph also ensures privacy and compliance across the core and various identity associations. Ultimately, the private identity graph is the hub for which all consumer data is connected, reconciled, and applied to deliver personalized customer experiences.
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4. Inform the Technology
Once the data is connected, it needs to be available for consumption across data management, orchestration and activation, and analytic platforms. Data management components will apply the connected data from the private identity graph to associate consumer identity to all applicable data sets. Orchestration and activation platforms apply the connected data from the private identity graph to inform interactions and experiences. Analytics platforms apply the connected data from the private identity graph for modeling and insights based on the interactions and associated results.
Figure 1 provides a high-level illustration of how data from across the organization is connected through identity resolution into the private identity graph. The private identity graph then informs data management, orchestration and activation, and analytics.
Figure 1.
Today’s modern platform needs to connect all data to create a single data asset that links all relevant sources. Identity resolution provides the foundational technology necessary to connect customer data across first-, second-, and third-party sources. The private identity graph organizes the identity resolution results into a single enterprise asset used to inform technical and business processes. Connecting all the data through the private identity graph promotes the ongoing curation of customer data while supporting the delivery of personalized customer experiences.