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How to Handle Change Management Around a CDP

How to Handle Change Management Around a CDP

Change management requires clear leadership from the top and the middle. Here are our change management recommendations when adopting a customer data platform (CDP).

All the data management capabilities in the world cannot bring a company to the promised land of data-driven marketing without the right people and processes — and customer data platforms (CDPs) are no exception. Over the years, we have seen hundreds of companies declare their commitment to using data to drive marketing strategy. The ones that find success are those that invest in the people and processes required to make it stick. 

In all cases, change management requires clear leadership from the top and the middle. But who are the stakeholders in your company who must come together to create true change management around data? It all starts with the formation of a Data Center of Excellence. 

Developing a Data Center of Excellence

A serious team approach is required to build what we call the Data Center of Excellence (DCOE). The DCOE is usually comprised of internal folks from the media, analytics, and IT teams; smart consultants for change management; systems integration partners; and agencies. The companies who adopt such an approach reap near-term value in the beginning stages of their journey, which more than funds all of their subsequent efforts.

We think of the pillars of organizational adoption as PeopleProcess, and Technology. There is no partial credit: getting one or two of those right and the other wrong leads to failure. The greatest data technology in the world falls down without the right people behind it. The most well thought out and rigorous process fails to scale without the right technology. And of course, the best people in the world are ineffective without the right habits and processes in place to coordinate their efforts.

It starts with people. When looking across the thousands of data software implementations we have supported, the companies that get value the most quickly have implicitly or explicitly created a DCOE that defines data strategy holistically and assigns ownership clearly across key stakeholders in the organization.

4 steps to establish a data center of excellence

  1. Take a team approach. To be successful, you’ll need to bring together internal and external partners. Gather their input on the types of data they want to capture and how they expect to use it, and build consensus on a common set of goals. 
  2. Establish detailed processes. Assign clear ownership to every step, identify key handoff points, and enact definite rules for communication.
  3. Adopt technology to empower people and processes. With the right team and process in place, technology will power and scale their efforts.
  4. Start seeing value. Companies that start with a team approach, establish thoughtful processes, and adopt the right technologies quickly see value.
Example of how you can structure a data center of excellence.
A data center of excellence helps users form a cohesive strategy and align partners

Aligning internal stakeholders

As we mentioned, a successful DCOE requires the collaboration of a full team of internal teams and external partners. Let’s focus on how to align internal stakeholders from your media, analytics, and IT/CRM teams.


Whether it’s the CMO managing cross-channel ad spending or the chief revenue officer (CRO) of a media company charged with yield optimization across various media offerings, the media team is usually the first group crying out for a coherent data strategy and the tools to make it work.

  • Have your media team identify their specific needs and KPIs around data. Typically, they’re looking for better audience discovery, more precise segmentation, tools to enable efficiency in media spending (or sales), the ability to get fast insights to support optimization opportunities, and the capacity to integrate with the tools currently in use.
  • Look to media to drive organizational efforts. We often see media teams’ evaluations of data technology serve as a hub for colleagues from analytics, IT, and its associated CRM counterparts to shape the organizational data initiative.
  • Set benchmarks to evaluate ROI. Media is also the fastest path to ROI. For advertisers, it offers the ability to optimize and reduce rogue or inefficient spending; for publishers, it is the ability to improve monetary yield through better audience segmentation.


Today’s analytics departments come to the table with a great deal of enthusiasm for data centralization and closer connections to the media team, which is a rich source of user intent data.

  • Understand and account for your analytics team’s top priorities. Many teams are tasked with combining rich, structured data they get from CRM, commerce, and offline sales data with newly available, fast-flowing media and unstructured data. Like their media counterparts, analytics teams have embraced many new technologies over the years for various use cases, and continually seek ways to make their insights easily digestible to management and other stakeholders.
  • Provide the tools and flexibility analysts need. The modern analyst needs built-in dashboards that can make the most common reports broadly accessible. They also need flexibility to draw from a single source of organizational data to run custom reports, perform modeling, and drive deeper levels of analysis. The analyst is concerned with uncovering richer insights, using data to identify better customer experiences, model customer lifetime value, propensity to purchase, and richer segmentation. She is eager to connect this data with that of the media team to provide better planning, optimization strategies, and measurement.


Much has been made about the convergence of the CMO and CIO functions, and for good reason. The modern CMO cannot execute a data strategy without being conversant in the technology tools and tactics required to execute it. In a perfect world, the role of chief data officer (CDO) would oversee the functional areas of both IT and CRM and serve as the ideal partner to join colleagues in media and analytics in a DCOE. Because not every company has made that leap, we often see both groups represented as IT.

  • Remove any barriers between media, analytics, and CRM to achieve alignment. IT departments are often charged with making sure the visions of the media and analytics teams conform to the overall corporate technology structure and segmentation strategy; they are responsible for aligning the investment goals of the group with the corporate technology and infrastructure budgets.
  • Empower IT/CRM to serve as strong stewards of their customer data. Most critically, the technology teams ensure that projects proceed with strong data governance, privacy rules, and existing security protocols. This is especially critical in a world in which privacy laws like General Data Protection Regulation (GDPR) are putting restrictions on how companies collect and stewart customer data.

Put stakeholders from these groups together around a common set of goals, and you have the framework from which true data-driven transformation can evolve.

In our next post, we will look at the key things to consider when selecting a CDP.

To learn more about the future of customer data and how to plan for change, check out this on-demand webinar.

Chris O'Hara Global product marketing and solutions expert

Chris O'Hara is global product marketing and solutions expert. He was previously vice president for product marketing at Salesforce. He is author of the award-winning business books "Data Driven" and "Customer Data Platforms."

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