Democratizing Data: Do Your People Have the Access They Need?

Organizations have invested heavily in engineering resources to centralize data across the enterprise, often creating sophisticated environments with robust data pipelines. But even as they have successfully gathered and corralled data this way, many still struggle with effectively sharing and orchestrating the data across the enterprise. 

That’s a pressing concern because, to successfully experiment, explore and activate data for the entire organization, IT, analytics and marketing teams must all have the data access they need to succeed. This notion isn’t new, but for many businesses, despite their commitment to democratizing data, that access—leveraging each group’s strengths—is insufficient or absent.

IT Challenges & CDP Solutions

This data-organizing process is often primarily driven by a centralized data organization within IT, and that role includes selecting and operating a solution to solve disparate, siloed information across the enterprise; that solution is the customer data platform (CDP). It seems to be a natural extension of IT’s role, but in fact it stretches its role—already critical in integrating and supporting the platform—beyond its mission while limiting the application of that data for the business. Not to mention, it places more strain on an already overburdened department.

This is an area where IT can collaborate very effectively with marketing and data science—to not only provide data access, but to serve up high-value, actionable insights and the ability to operationalize them at scale in a coordinated way across multiple channels, both inbound and outbound.   

Customer data platforms (CDPs) can enable and accelerate this collaboration. As a concerted group, they gain the ability to use the CDP to not only break through data silos and collect data from all sources, but to delve further to understand customer behaviors, unify customer profiles and deliver unified customer experiences on customers’ terms. Creating a single source of truth for all customers can be a tall order, incorporating identity resolution across devices, channels, brands and geographies—well beyond the charter of a typical IT group. However, it is a necessary foundational step, if the notion of a data democracy within an organization is to be credible.   

Empowering Data Science and Analytics 

A lot of powerful data science is done in data silos, making that science significantly less powerful in guiding business decisions on customer relationships. A centralized source such as a CDP can eliminate those silos, but the data scientists—assuming you have the talent you need from this highly-prized group—need to be involved at the outset. They need the data to be in an analytics-friendly data model so they can create models, predict and compare results to previous years, campaigns or prior model versions, as well as do complex testing across messages, segments, channels and offers. 

Many of these data scientists focus on algorithms behind the scene, but the solution lies in a consumption layer. They can feed algorithmic output into the CDP data pipeline to create model scores and create derived attributes for marketers to act on. Keeping data and model scores in a single data pipeline creates effectiveness in the CDP. They need to help shape the centralized data early on so they can flex their analytical muscles and work effectively with marketing to help execute customer strategy and drive desired business outcomes. 

Marketing: Self-Serve and Control

Meanwhile, marketers are often trying to extract and act on the most accurate customer picture and insights. 

As marketing has become central to business strategy, evolving from a cost center to a revenue driver, this group has a stronger vote in the process. At least, they should. In fact, there are many that feel CDPs should be managed by marketers. But more than dwelling on the data itself, marketers want to zoom in on what it can do. They want a friendly interface and self-serve to unify profiles with privacy settings, create segments, size segments, and activate that data to the external systems and platforms that drive customer engagement. They tend to be attached to their execution tools of choice and want the CDP to be connected to, not replace, those tools.   

Whether their strategy is acquiring new customers or building the profitability of existing customers, marketers need that holistic customer view. Since they are on the front line, making them an afterthought in the centralized data process will under-serve the enterprise.

They need to be front and center with IT and data science from the start. For one thing, marketing can supply the use cases that are instrumental in guiding the process. The marketing strategy, based on a unified customer view and communications standpoint, is actively critical to meeting business goals. Often leaning on analytics findings, marketers pull value from centralized segmentation for slicing and dicing the best customer targets. At the same time, they need IT guiding them on key issues like data governance so they can trust the data and have full visibility into rules like privacy, while ensuring that the data they are using is consistent with that of the rest of the organization. This marketing layer must be built in at the outset.

Make or Break Synergy

As too many businesses have learned, trying to retrofit their data collection to meet these various needs is a costly, painful process. A truly successful CDP depends on the synergy between marketers and their IT and data science colleagues for an impact on business decisions greater than that which each discipline could supply alone. Whether the organization sets out to buy or build a CDP, that truth remains. And in a marketplace crowded with half-true, afterthought solutions, that team’s synergy can steer the organization clear of expensive dead-ends to find a solution that best reaches their ultimate goal, the customer. It also enhances the ability of the entire organization to be agile and flexible, able to respond to changing demands and unforeseen crises. That’s the power of data democracy.