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TDWI Upside - Where Data Means Business

Harnessing the Power of Customer Data: Insights and Innovations in Data Management

Dave Stodder, TDWI’s senior director of research for business intelligence, discusses trends and topics in customer data management.

In this “Speaking of Data” podcast, TDWI’s Dave Stodder discussed the latest developments in customer data management with host Andrew Miller. Stodder is senior research director for business intelligence at TDWI. [Editor’s note: Speaker quotations have been edited for length and clarity.]

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Miller began the conversation by asking, “Within TDWI, we're seeing that customer data itself is growing in volume and variety. What are the key trends with customer data and objectives to tap into its value?

“It’s definitely a top-of-mind thing,” Stodder said. “To begin with, more companies are collecting customer data. Companies now have direct relationships with customers through their online presence and e-commerce.” That’s why, he noted, it's incumbent upon organizations to modernize their customer experiences, which starts with modernizing their customer data management. Organizations need to be thinking about how they can support next-generation customer experiences such as dynamic pricing and the applications that run 24/7 to support them.

“One of the things that a lot of organizations are trying to get to is the 360-degree view of customers. Organizations often have multiple channels to integrate, even just online, to understand how loyal their customers are personally and what’s influencing them.” Companies are marketing heavily and want to know how it’s affecting customer behavior. Is it leading to buying? According to TDWI research, just 23% of respondents are satisfied with their single view of all relevant customer data.

When asked about whether advanced analytics, including AI and machine learning, was important to managing all of this data, Stodder readily agreed.

“Definitely. That’s where a lot of analytics, AI and machine learning as well, have been used -- to understand customer behavior. In fact, it's part of the original reason for data lakes, to capture such a variety of data that are involved in interactions and experiences with customers.”

Much of companies’ analytics efforts are spent trying to improve their net promoter scores (a measure used to gauge customer loyalty, satisfaction, and enthusiasm), understand customer lifetime value, and drive personalization programs. Stodder says that 65% of TDWI research respondents report increased demand for machine learning over the past year and 47% say that modern analytics, including AI and machine learning, is the primary motivation for evolving the organization's data strategy, based on an unpublished data analytics survey from 2022.

Another analytics-dependent practice is retargeting -- the practice of reaching out to previous visitors and sending them content through email or other means to generate more activity, trying to get them back to the website to buy something. No wonder embedding analytics and machine learning in business applications in websites is critical.

To manage all this, companies are using or developing customer data platforms. All the major data management vendors, even CRM vendors, offer customer data platforms. Companies are collecting a lot of data – first-party data from direct interactions with customers plus second- and third-party data, data from various partners or data they may be acquiring from other sources. There's a lot of data to pull together about customers, instead of having it spread out over silos. This is one of the main strengths of the customer data platform. Some organizations are using data warehouses as their customer data platform, others are using a data lake. As we see organizations beginning to unify the data, Stodder explained, converging lakes and data warehouses into this unified platform called a data lakehouse, the question is, shouldn't the customer data platform be part of that as well? It’s a growing trend that TDWI is watching.

Another top-of-mind subject is governance, especially as it relates to customer data. Today, we look at governance in two parts. Part one is protecting sensitive data and complying with regulations. To begin with, it’s important to understand the regulations as they apply to you. There’s been a huge movement globally to develop standards (e.g., GDPR, CCPA, and others) for protecting consumer data. Some of these come with huge fines, some upwards of $1 billion, for violations. Another aspect, especially related to customer data platforms, are localization requirements that dictate where data can be stored, necessitating other approaches (such as data fabrics) to eliminate silos.

Part two is improving data trust. According to Stodder, part of trust is knowing that the data is accurate, validated, and complete, that users can repeatably go to the sources, and that the data is okay to use. Some other practices are to make sure you have your data governance in sync with your data access control policies and procedures, and then having security -- certainly data security procedures -- in place.

From a process and people perspective, Stodder suggests organizations assemble a center of excellence to bring the stakeholders together -- the data owners, data stewards, and others. Data stewards are becoming important in organizations, particularly for making sure everybody understands the governance regulations, as well as for addressing trust issues and letting users know they can count on the data.

As far as tips for success, Stodder offered one key piece of advice. “Organizations should never stand pat. They have competitors out there who are working very hard. They could even be small organizations that have been data-driven from the get-go and are coming in to compete with your organizations. It's important to stay on top of all the different technologies and practices that are modernizing. Think about those embedded applications that I talked about and what are your processes for delivering data products. This particular aspect of data management -- customer data management -- only is going to get tougher, between complying with evolving regulations and governing the various amounts of data coming in.”

[Editor’s note: To hear the full conversation, replay the podcast episode here.]

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