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Apr 2, 2024

Superior Data Quality and the Role of a Customer Data Platform

According to research from McKinsey, personalization drives up to a 25 percent revenue lift depending on an organization’s ability to execute. The more skillful a company becomes in applying data to grow customer knowledge and intimacy, the greater the returns. In every industry with a customer-brand dynamic, companies are competing with one another on the experience they deliver to customers, patients, members, donors – anyone who interacts with the brand. As the McKinsey article notes, the competition is fueled by data – the line between winning and losing comes down to the skillful application of data to develop a deep understanding of the customer and orchestrating the perfect experience based on those insights, anywhere, anytime. The challenge for organizations is that the actualization of benefits largely comes down to successfully harnessing people, processes and company culture to truly become data driven. When an organization’s goal is to make data-driven decisions, data quality becomes paramount. Companies must trust that their customer data is accurate, updated and ready for business use. This is where a customer data platform (CDP) comes into play in helping organizations deliver an omnichannel customer experience. There is a common misconception among companies that a CDP is a magic bullet that will miraculously bring about a hyper-personalized customer experience. The problem with this line of thinking, however, is that data quality is not given its due as a key element of the equation. If we think about a CDP’s purpose to enable marketers to access the data they need to create segmentation models and ultimately to create campaigns based on insights, what’s missing from the majority of CDPs in the market is the correct approach to data quality.

Just Say No to Reference Files

Asked about how they handle data quality, many CDP vendors will talk about identity resolution, touting basic matching techniques that anyone can do. But really what they mean is that they’re relying on someone else’s data quality; they’re outsourcing data quality by bouncing customer data against a reference file – gathered by a third-party organization and enhanced in some way. The problem? Any organization intent on delivering a hyper-relevant omnichannel customer experience does not have the luxury to wait for a quarterly update of a reference file where keys change with every iteration. We know customers expect brands to precisely match the cadence of their unique customer journey. In a 2021 Harris Poll sponsored by Redpoint, 82 percent of customers surveyed said that loyalty to a brand is dependent on the brand’s ability to demonstrate a thorough understanding of them as a unique customer. A thorough understanding, from the customer’s perspective, means the brand knows them as the same customer across every channel and offers consistent relevance because the brand knows their individual behaviors and preferences. The approach to data quality is what differentiates the Redpoint CDP from also-rans who rely almost exclusively on reference files. What makes Redpoint stand out from the crowd is that our platform is the technology with which to build reference files. Redpoint’s advanced identity resolution capabilities do not rely on a third-party organization’s customer data, but rather use probabilistic and deterministic matching to enhance a company’s own first-party data.

Democratization of Data

Redpoint solves other common problems as well, namely the data discovery challenge. For an understanding of the problem, consider the Alation State of Data Culture Report where 34 percent of data leaders listed data discovery (do not know what data exists or who has what data) as a top challenge for using data to drive business value. Furthermore, 36 percent said data democratization was a top challenge, where not everyone can access data on their own, with 35 percent citing organizational siloes as a barrier for using data to drive business value. Redpoint solves these problems by managing data governance at the point of data use (which the report said is indicative of top-tier, data-driven companies). This task used to be a central IT function, but is more often now moving to the point of use where data is applied at the business level. Pushing governance, curation, and the perfection of data out to the business unit breaks down the siloes that too often lead to inefficiencies in driving business value from data. Redpoint solves for traditional wide-scale inefficiency by ingesting raw data and taking care of all data hygiene and data transformation tasks at the point of entry. All data harmonization – unlike many vendors – means that even if two strands of data are identically labeled, the platform will make sure they mean the same thing. From ingesting to creating an industry best Golden Record, Redpoint covers the entire spectrum – from the edge to the business unit, or even in central IT if that is what a client prefers. Importantly, all standardization and data management tasks are completed in the same application, greatly reducing process inefficiencies born of having a multitude of solutions in differentiated states.

Foster a New Data-Driven Culture

Lastly, let’s talk a little bit about data culture. We’ve covered the Redpoint difference as far as being a through-line linking data, insight, and action. On the culture side, it’s important to remember that there is a difference between having quality data and knowing that you have quality data. That, in a nutshell, describes the Redpoint approach toward changing the deep-seated mindset that it’s too hard to adopt a data-driven strategy. With Redpoint, business users don’t just have democratized access to data, they see it and have the tools to answer any question they might have about it. With a dashboard that reveals all dimensions and metrics behind data quality, Redpoint makes it possible to correlate good data with good business outcomes. The business users who interact with the data drive the improvement of data quality, becoming part of the curation process at the business unit level. This involvement establishes a line of sight between the use of data and outcomes, a key factor in developing and fine-tuning a data-driven culture. With consistent visibility of data quality throughout the platform, marketers and business users no longer have to fly blind as they try to drive business outcomes. Importantly, as my previous blog notes, Redpoint is a rules-based platform. Trust in the quality of data is fortified because marketers and business users know that, as a rules-based system, data reflects every change – however recent. This is an important concept for delivering an omnichannel customer experience. By building audiences using rules instead of lists, marketers and business users are able to package different versions into content assets, building once and using an audience or asset across every channel and in every context. Lists are static and subject to decay, rules are dynamic and re-evaluate at every inflection point, guaranteeing precision with every customer interaction. Ubiquity. Connectivity. Process efficiency. Supporting perfected data and a new data-driven culture around the curation of perfected data. This is the Redpoint difference, and it is why ambitious business leaders are turning to Redpoint to rapidly transform customer experience and drive tangible ROI. For more on how the Redpoint CDP handles data quality, click here to join Redpoint VP of Product Management Beth Scagnoli and Redpoint VP of Engineering Kris Tomes in the Redpoint “CDP Back to Basics” webinar series.