Cloud Data Warehouses: Rethinking the Martech Stack for the Future

Cloud Data Warehouses: Rethinking the Martech Stack for the Future

Cloud data warehouses (CDWs) are disrupting the martech stack. Gartner VP Ben Bloom explains how marketers can leverage CDWs to unbundle apps and data for a more efficient, data-centric approach.

Premium brands’ growing use of cloud data warehouses will challenge our thinking about martech stacks. It goes beyond the composable CDP and the composable customer engagement platform and calls for a radical rethinking of the relationship between applications and data.

That was a challenging but compelling message that Ben Bloom, Gartner VP and Analyst, delivered during his session at the Gartner Symposium.

The way we are

The martech stack has been failing marketers, whether it be (primarily) an integrated suite or a collection of point solutions circuiting a central hub. Utilization of martech tools has fallen from 58% in 2020 to 33% in 2023.

“The teams that chose the best-of-breed approach and the teams that chose more of an integrated suite approach did not have different results when it came to their levels of marketing technology utilization,” Bloom told us.

Enter the cloud data warehouse

AWS, Google Big Query, Snowflake, and the cloud data warehouse (CDW) are not new. They have typically been a repository for any brand data, not just customer data, and have been the purview of IT. What is new is the sudden and dramatic impact they are having on marketing—to the extent that marketing teams must be prepared to be actively involved in CDW purchase decisions.

What this signals, said Bloom, is a movement away from an app eco-system to a data eco-system. Thus far, many apps have been standalone in the stack, hopefully integrating with others. “So you buy some multichannel marketing solution,” Bloom explained. “You can put data into it, manage those audiences, send out email messages to your contacts, and get some reporting as a result.”

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This model creates enormous risk, Bloom continued. “You don’t just have one data store; you’ve got data in every one of these applications. From the perspective of how much data is now at risk of being copied, replicated, or ungoverned across these applications. The customer data platform was supposed to be the savior, but the problem may worsen. It’s not neutral territory because most CDP bundles’ data capabilities are designed around marketers’ use cases. If functions outside of marketing need that data, that kind of marketing-specific solution is less appealing.”

Unbundling apps and data


Using a CDW creates the possibility of “unbundling” the app, “where we do the work,” said Bloom, and the data.

In other words, the applications — marketing automation tools, CDPs, customer engagement platforms, DXPs, etc. — reach down into the CDW for the data they need for specific tasks. There are many ways of doing that. Bloom repeatedly emphasized that it’s okay to copy data; for example, people have been doing that for years.

Sixty-six percent of CDW adopters report that they have the following solutions in their stack, sitting atop the warehouse:

  • Customer data platform
  • Data clean room
  • Identity resolution
  • Multichannel marketing hub
  • Personalization engine
  • Web and digital experience analytics

In some ways, these are the familiar elements of a marketing stack assembled differently (contrast the “stack” pictured above with a typical stack representation). As more apps become warehouse-native, apps without connectivity to the warehouse become targets for consolidation or redundancy, potentially reducing the under-utilization problem.

“Genius” or “gifted brands (the two top echelons in Gartner’s Digital IQ index) are most likely to store data in a CDW. Interestingly, they’re also more likely than less smart brands to have a CDW and a CDP. “Many organizations are stuck in a war over which approach misses an opportunity because most marketing teams will not want to spend much time in that warehouse directly. You will likely need both or some of the components of both.” The CDP, of course, would be connected to the CDW.

Remember the 360-degree view?

These reflections seem consistent with the skepticism about the need for a 360-degree view of the customer expressed at last year’s Symposium. This model rejects pushing all available customer data into some marketing stack hub.

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“It could be that there are data sets you need, say for advertising,” Bloom agreed, “or matching cookie data to an onboarding or identity provider. That data doesn’t need to live in the CDP. We’re hearing from clients that they have to think about their warehouse potentially enabling some of that activation almost in parallel with other parts of their ecosystem. I’m no fan of the 360-degree view concept because it’s costly and potentially leads marketing teams down the wrong path. But it could also be that the experience you’re trying to enable for advertising might be so different that you shouldn’t try to combine it all and say there’s an all-encompassing data set we’re going to place in one [application].”

Roadmap recommendations from Gartner:

  1. Identify the owners of cloud-based data warehouse capabilities within your enterprise data stack and embed marketing capability owners in their decision-making processes.
  2. Audit your data use cases for cross-functional dependence to align your martech stack to the future state of enterprise data.
  3. Cull martech vendors, especially those with poor warehouse integration features or roadmaps, to strategically consolidate for the future.
  4. Accept and embrace data duplication where realistically necessary to power personalization and decisions at the edge.