{"id":7826,"date":"2024-06-06T18:55:49","date_gmt":"2024-06-06T18:55:49","guid":{"rendered":"https:\/\/tup.kxe.temporary.site\/cloud-data-warehouses-set-to-disrupt-the-martech-stack\/"},"modified":"2024-06-06T18:55:49","modified_gmt":"2024-06-06T18:55:49","slug":"cloud-data-warehouses-set-to-disrupt-the-martech-stack","status":"publish","type":"post","link":"https:\/\/okdesign.ca\/en\/cloud-data-warehouses-set-to-disrupt-the-martech-stack\/","title":{"rendered":"Cloud data warehouses set to disrupt the martech stack"},"content":{"rendered":"


\n<\/p>\n

\n

The growing use of cloud data warehouses by premium brands will challenge how we think about martech stacks. It goes beyond the composable CDP and the composable customer engagement platform. It calls for a radical rethinking of the relationship between applications and data.<\/p>\n

That was the challenging, but also compelling, message delivered by Ben Bloom, Gartner VP, analyst, in his session at the Gartner Symposium this week.<\/p>\n

The way we are<\/h2>\n

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 (all research quoted here is from Gartner).<\/p>\n

\u201cThe 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,\u201d Bloom told us. \u201c<\/p>\n

Enter the cloud data warehouse<\/h2>\n

AWS, Google Big Query, Snowflake; the cloud data warehouse (CDW) is not a new technology. It has typically been a repository for any brand data, not just customer data, and has been the purview of IT. What is new is the sudden and dramatic impact it is having on marketing \u2014 to the extent that marketing teams must be prepared to be actively involved in CDW purchase decisions.<\/p>\n

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 elements in the stack, hopefully integrating with other apps. \u201cSo you buy some multichannel marketing solution,\u201d Bloom explained. \u201cYou can put data into it, manage those audiences, send out email messages to your contacts and you get some reporting as a result.\u201d <\/p>\n

This model creates enormous risk, Bloom continued. \u201cYou don\u2019t just have one data store; you\u2019ve 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 it may make the problem worse. It\u2019s not neutral territory because the data capabilities of most CDP bundles are really designed around the use cases of marketers. If there are functions outside of marketing that need that data, that kind of marketing-specific solution is less appealing.\u201d<\/p>\n

Unbundling apps and data<\/h2>\n
\n
\"Cdw1\"\"Cdw1\"<\/figure>\n<\/div>\n

Using a CDW creates the possibility of \u201cunbundling\u201d the app, \u201cwhere we do the work,\u201d said Bloom, and the data.<\/p>\n

The applications, in other words \u2014 be they marketing automation tools, CDPs, customer engagement platforms, DXPs, etc. \u2014 reach down into the CDW for the data they need for specific tasks. There are many ways of doing that; Bloom emphasized repeatedly that it\u2019s okay to copy data, for example; people have been doing that for years.<\/p>\n

Sixty-six percent of CDW adopters report that they have the following solutions in their stack, sitting atop the warehouse:<\/p>\n