With Google’s plan to stop supporting third-party cookies on Chrome, a new “cookieless” world of customer data is coming, and with it, new complexities for data management. Those organizations that have relied on cookie tracking for customer behavior insights will need to refocus on opt-in permission for data gathering and use. Without cookies, marketing data will be missing key behavioral signals from company websites and advertisements. To be prepared, companies need to start shifting to first-party information—the data a company collects directly via opt-in processes from its customers. And that means building out robust, adaptable data governance that can scale to meet this new need.
Enterprises addressing the need for more first-party customer data find Chief Marketing Officers (CMOs) giving customer data platforms (CDPs) another look for their “martech stack.” A recent survey showed the largest planned investment from marketing leaders was for CDPs, with nearly 40 percent making CDPs a priority. CDPs typically ingest data from multiple systems and augment rather than replace all customer data sources. Research also shows CDPs may be directly purchased outside IT involvement, leading to new and unplanned pressure for customer data integration, data quality, and governed access. In this blog, data leaders will learn more about the evolution of the “martech stack,” key issues in managing associated customer data risk, and new opportunities to get more value from customer data.
Fast Facts for the CDO: the Rise of the “Martech Stack”
As long as companies have sought to translate customer behavior into high-value data for business optimization, there have been technology providers ready to help—and to help CMOs reduce dependence on IT for support. As you’ll learn, this has implications for data management in a cookieless world.
Marketing technology (Martech) solutions are typically low-code, democratized tools designed to empower marketers to learn more about and do more with prospects and customers. They include Customer Management Systems (CMS) like Salesforce and Hubspot, Digital Asset Management (DAM) platforms such as Adobe and Brandfolder, and E-commerce platforms like Shopify and Square. But whatever their focus, Martech applications consume and generate data, and the explosion of Martech adoption over time adds complexity to integration and governance.
Although the rise of the Martech stack has empowered CMOs, it’s also led to some decoupling of customer data management from IT and data leaders. According to Gartner, nearly 30 percent of marketers control Martech vendor evaluation and selection without IT as a partner, a trend that’s increased by nearly 10 percent over the past two years. While research shows some preference is given to integrated suites such as CDPs, the reality is most Martech stacks comprise best-of-breed tools as well as a platform or two. This complexity, and the reduction in IT partnership, potentially expose the organization to compliance and data management risk as it seeks a 360-degree view of customers. With first-party customer data use on the rise, the time is now for data leadership to refresh its role as a partner for CMOs.
Two Key Ways to Use the Cookieless Future to Re-engage on Data Value with CMOs
CMOs need support and guidance from CDOs to ensure the transition to a 100 percent first-party data, cookieless future state has enterprise governance baked in. CDOs and data leadership can also use this moment to partner with CMOs on two important additional value drivers for customer data.
Customer Intimacy via Controlled Use of Generative AI
Generative AI like OpenAI’s ChatGPT and Dall-E has captured the attention of the executive suite. Although known risks are still being sorted for generative AI, it will be worth a conversation with CMOs to hear their thoughts on use cases for improved chatbot and recommender bots. Morgan Stanley is already testing generative AI for its financial advisors’ use. Partner with your marketing leadership to test generative AI tools for customer intimacy use cases.
Multidimensional Data Monetization and Value Extension
First-party customer data can add value across the enterprise, and represents an expanding source for data productization—defined by TDWI as “using the enterprise-owned data and data-derived assets (such as machine learning models) to build revenue-generating products and services to be sold to external customers.” According to Deloitte, marketing organizations lead in AI-related use cases that extend the value of data, and those that outperform their peers by more than 10 percent use documented processes for governance and data quality.
Next Steps to Ensure First-party Data is Governed and Adds Value
Your enterprise needs your expertise to help manage risk as cookies are phased out, and first-party customer data becomes the norm. Here are some thoughts for your next Data Center of Excellence (CoE) or similar workgroup.
- Use the fact that generative AI is a hot topic for enterprise leadership to ensure marketing participation at the next Data Center of Excellence or Data Workstream group.
- Prepare an agenda including an overview of potential generative AI use cases with a focus on marketing (the Morgan Stanley and Deloitte links above can help).
- Make sure the coming cookieless world, and the need for more first-party customer data, is on the agenda for discussion.
- Prepare participants so they can come with information about the extent of your organization’s martech stack, and what governance controls are in place.
For more information on TIBCO for data governance, read about the award-winning TIBCO EBX master data management solution.
