CDPs and Customer Data Unification (CDP Best Practices)
October 16, 2024Customer data unification is an important use of the customer data platform. The CDP Institute recently asked industry leaders what best practices they see to maximize value in the enterprise. Here’s the second post in a series based on their answers. Today’s topic is CDPs and Customer Data Unification.
Companies Struggle with Data Integration. Realistic expectations are important. “Companies struggle with integrating a CDP due to the complexity of unifying disparate data from multiple systems, compounded by a lack of consistent identifiers. These data hygiene issues, such as duplicated records and anonymous data, hinder the potential of a CDP,” explains Deepak Narisety, Marketing Technology Practice Leader, Acxiom.
Data Quality Includes Process Improvement. Successful integration starts with managing data quality. “Leading companies are measuring and improving data quality as a primary initial metric, knowing it will affect all their use cases and later measurements. Data quality is more than simply bringing data together – it’s understanding sources of error and having software and processes to continually manage and improve the quality, accuracy, timeliness and compliance of customer data,” notes Steve Zisk, Product Marketing Principal, Redpoint Global.
Evolve Data Governance to Support CDP. Effective data governance is vital to CDP implementation. “In our experience, technology is only part of the puzzle. Equally important is the evolution of the data operating model and governance structure to keep pace with the transformational benefits of introducing a CDP to the enterprise,” explains Projjol Banerjea, Founder & CPO, Zeotap.
Golden Customer Record Provides a Focus for Data Unification. A “golden customer record” combines the best information across all sources for each customer. “Leading companies focus on creating a golden customer record by integrating valuable data from key sources like DWH, CRM, and MarTech to ensure a unified customer view. This strategy breaks down data silos, enabling seamless access to personalization-ready data, segments, and insights across departments for better decision-making,” notes Guus Rutten, Managing Director, GX.
Modern Data Clouds Support CDPs. Data clouds such as Google Big Query, Databricks, and Snowflake often host data for a CDP. “By running a CDP on a modern data cloud, leading companies extract value in two ways. First, by maintaining control of their data they better adhere to privacy and regulatory requirements. Second, maintaining a single source of truth for customer data without data replication provides confidence that a unified profile is both accurate and consistent across every MarTech stack connection,” explains Steve Zisk, Product Marketing Principal, Redpoint Global.
Standalone CDP Supports Best of Breed Experience Platforms. A standalone CDP can make it easier for companies to avoid marketing clouds such as Salesforce or Adobe. “Enterprises that have a standalone CDP are more able to leverage best of breed experience platforms more easily than with a CDP that is provided as part of a wider marketing cloud. This enables enterprises to more rapidly bring online new types of experiences without having to wait for their marketing cloud provider’s roadmap,” notes Damian Williams, CTO, n3 Hub Ltd.
Data Warehouse as Backbone of Customer Data Strategies. Not everyone prefers a separate CDP database. “Leading companies are increasingly using their data warehouse as the backbone of their customer data strategies. Centralizing data in one place gives teams a consistent, unified source of truth that powers all of their personalization, loyalty programs, operations, and more. This creates a positive feedback loop between data/analytics teams and marketers/other end users.
“Investments in core data assets can immediately drive ROI for business users, who then advocate for more investments in their data. This centralized data store also opens the door for AI-powered marketing and decisioning. Machine learning and AI rely on complete data from disparate sources. Companies that invest in their data warehouse at the center of their marketing are better positioned to take advantage of the next wave of AI innovations to increase customer engagement,” says Tejas Manohar, co-founder and co-CEO, Hightouch.
Composability Includes Both Functions and Warehouses. “Composability” comes up often in CDP discussions, so it’s important to understand its different meanings. “Data architecture composability (accessing data where it lives, e.g., in a cloud data warehouse), and functional composability (“unbundling” unneeded capabilities of a CDP, e.g., data activation), will be critical to the CDP of tomorrow. In tandem, these will lessen the TCO for both data and martech, decrease complexity, and increase the utilization of our “messy” martech stacks,” predicts Lisa Loftis, Principal Product Marketer, Global Customer Intelligence, SAS.
We hope you got a lot of insight from the experts on CDPs and customer data unification. Also, see our other CDP Best Practices posts on these topics:
Thank you to our participants!