CMOs, Take the Reins: Why Data Quality Elevates to the C-Level

Henry Ford is often attributed with saying that if he had asked people what they wanted, they would have said a faster horse. The quote speaks to innovation being a lonely pursuit. Many are able to describe a problem, but few are able to find the right solution.

The saying aptly captures why driving a customer experience strategy around data quality should be a C-level initiative. Operational marketers focused on incremental process improvements are after the faster horse; responsible for a channel, they narrowly focus on step changes that may offer nominal improvements for the metrics they care about.

The problems with this approach are two-fold. First, process improvement does not stanch the flow of poor data quality across departments and functions. Nothing is gained when a slow process using inferior data becomes a fast process using inferior data. Second, even a ten-fold improvement – open rates in an email campaign, clicks on a product image – do not factor how a customer’s behavior on one channel influences the totality of a customer journey.

With a top-down focus on data quality to drive a CX strategy, a chief marketing officer solves for both problems. Marketers presented with perfected data, that is a robust single customer view available and accessible to anywhere and anytime, can then shift their focus from a process to where it belongs – on the customer. And then from an alignment standpoint, making data quality a C-level initiative underscores the importance of the consistent use of data across channels.

Stop Bad Data in its Tracks

Gartner research reveals the extent of the problem with inferior data and why it has reached the C level. Estimating that poor data quality costs organizations an average of $12.9 million each year, Gartner predicts that 70 percent of organizations will rigorously track data quality levels via metrics, with the result that data quality will improve by 60 percent, significantly reducing operational risks and costs.

From a customer experience standpoint, poor data quality translates to irrelevant, untimely experiences that introduce friction into a customer journey. Organizations lose revenue when they fail to demonstrate a deep understanding of a customer at a personal level. Consider a 2021 Harris Poll commissioned by Redpoint in which 39 percent of customers surveyed said they will not do business with any company that does not offer a personalized experience.

Making data quality a top-down, enterprise initiative supports the delivery of a consistent experience across touchpoints, lessening a focus on a team’s contributions to a single channel or process. The through line that enables the shift is a single view of the customer, or golden customer record. A golden record integrates data from every conceivable source and includes a long-tail transactional record along with a unique identifier encompassing all devices, names, addresses, social, etc. When it is updated in real time and made accessible across the enterprise, every part of  the customer experience – call center agents, email content, web pages,  etc. – works with the same unified customer profile.

Enterprise use of a golden record empowers a CMO to rethink bonus and pay structures. Satisfaction surveys, open rates, time on page, and other channel-centric metrics give way to those that instead key in on a team’s contribution to the overall customer experience – lifetime value, retention, acquisition, conversions, revenue etc.

Perfected Data and a Deep Understanding

Supporting a consistent experience across all channels with perfected data that is accessible enterprise-wide has become an imperative in large part because dynamic customer journeys consist of multiple channels. In a joint survey between Dynata and Redpoint that explored consumer behaviors, 29 percent of consumers said they regularly conduct online research prior to in-store purchases. And 60 percent said they plan to use a buy online, pick-up in-store service.

The survey also makes clear that no matter how often consumers move at will between channels, the expectation remains that brands will maintain a deep understanding and be able to move with them through a customer journey. Consider that 78 percent of customers said they find it frustrating when a brand’s communications and marketing messages are inconsistent depending on the channel they visit (in-store, online, social, call center, app).

To meet this expectation, a golden record not only must be made accessible to a business user in the last mile to the consumer, but also accessible in the customer’s cadence to a brand’s operational systems. A call center agent or front desk clerk, for example, with a real-time view into a customer journey is then not only empowered to provide a relevant experience and move a customer journey forward, but they are also making real-time updates to the golden record during the interaction.

With data quality pushed out to the edge and customer service reps and other front-line business users empowered to correct mistakes, having strong data governance systems and policies in place becomes important. To maintain a golden record’s integrity, controls must be in place to ensure accurate changes and record-keeping.

Dynamically updated across functions and departments, a golden record never becomes stale, outdated, or inaccurate. The recognition that one function impacts another – such as a poor sales experience becoming a customer service problem – puts emphasis on the need for operational alignment and thus elevates data quality to the C-level.

A Harvard Business Review study highlights the insidious nature of poor data quality and shows how easy it is to fall into the “faster horse” rut. According to its research, employees who work with data waste up to 50 percent of their time hunting for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust.

With perfected data that persists across departments and functions, that wasted time could instead be used to deliver a consistently relevant customer experience that spans an entire dynamic customer journey. A focus on data quality as a top-down initiative helps ensure an entire organization is empowered with perfect customer data to deliver a perfect customer experience.

Related Content

Marketing’s Star Turn: How to Secure Enterprise Buy-in for a Customer-Centric Approach

Perfect Data, Creative Marketing: A Cyclical Flow of Excellence

Data as a Revenue Engine: How to Monetize Customer Data with a Single Point of Control

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