What the composability revolution means for the martech stack

This is the third article in a three-part series. The first, on composable CDPs, is available here ; the second, on composable customer engagement platforms, is available here.

In the CDP space, there’s been a lot of talk lately about composable CDPs. Not only are there CDPs designed primarily to be composable, like Simon Data built on Snowflake, but traditional packaged CDPs like ActionIQ now offer a composable option. Composable in this context means tight integration with a data warehouse (or “lakehouse”) allowing the CDP to activate data in the warehouse rather than ingesting data from the warehouse (and other sources) to create its own independent, persistent database.

The same trend is seen in customer engagement, where platforms like MessageGears, Iterable, and Braze are pulling the right data from the warehouse to support personalized, omnichannel customer messaging. It seems clear that these platforms are keeping copies of the data in the data warehouse so they are ready to respond to customer actions in real time; where rapid retargeting in response to customer actions is a perceived need, that data might be stored for a year or two.

What will happen as more applications adopt this composable structure, such as marketing automation? According to Gartner analyst Ben Bloom, we could see a “decoupling” of applications and data at every level.

Dig Deeper: What the Composability Revolution Means for Customer Engagement

The unbundled martech stack

What does this mean? Martech stacks have traditionally consisted of a series of more or less well-integrated applications, most of which manage their own native data sets. DAM has its data, marketing automation has its data, CRM has its data, social media, etc. In a sense, the traditional packaged CDP was meant to solve this problem, acting as a single source of truth for customer data.

If the trend to centralize both customer data and other business data in a data warehouse (Amazon Redshift, Google Big Query, Databricks, Snowflake, etc.) continues, we can imagine a stack in which there is a data repository and a series of applications, decoupled from the data, forming a layer “where we do the work,” as Bloom puts it.

But is this vision of the future (too simplified, certainly, but made clear by Gartner’s representation) really realistic?

Dig deeper: Cloud data warehouses will disrupt the martech stack

Composable CDPs don’t dominate the space yet

First, it’s worth noting that despite all the talk about composable CDP, it doesn’t yet dominate the CDP space. This is evident from a recent study by David Raab of the CDP Institute. Just looking at Google search volumes, the term “CDP” is still searched for significantly more than the term “composable CDP.”

“While the CDP industry is clearly at a standstill, the reason is far from clear,” the Institute says. Composable CDPs may be growing slightly faster (based on employee count) than traditional packaged CDPs, but not enough to explain the slowdown in the traditional CDP market.

The numbers speak for themselves, but they don’t prove that composable CDPs won’t dominate the market in the future. They could still climb to the top of Gartner’s hype cycle.

Dig deeper: What the Composability Revolution Means for CDPs

A return to reality on “unbundling”

Kevin Wang, chief product officer at Braze, a customer engagement platform that can pull data from data warehouses, says the “unbundled” stack model is plausible for some applications, such as analytics applications that just need to look at data that previously came from different sources without taking any action. “I don’t think that will apply to Braze at all. We’re activating data from a data warehouse, but we’re first-party, zero-party data generators ourselves. Plus, we need data to have that real-time responsiveness that’s critical to the use cases we’re enabling.”

Raab’s reaction to the separation of applications and data bordered on disbelief. “Are they really not going to have their own data anymore?” Even if an application connects to the warehouse, it will still make its own copy of some data. “The interesting part is whether you have a central platform or not,” he said. “It could be a data warehouse or the Salesforce Data Cloud, or Adobe’s data platform, and then you have applications that sit on top of that platform. But that’s an architecture we’ve been working with for a long time. It has nothing to do with composability.” in itself. I don’t think everything will go directly to the warehouse; I’m not sure.

What we’re dealing with, once again, may not be so much a complete overhaul of the martech stack as a swinging pendulum. For years, the martech pendulum has swung between all-in-one marketing technology suites and collections of point solutions assembled in one way or another (what Pega’s Alan Trefler called the Frankenstack a decade ago).

Recently, the pendulum has become somewhat stable around a central hub (often one of the large suites) with selected point solutions connected – a situation recognized by the growth of, for example, HubSpot’s and Salesforce’s app marketplaces.

But now we have a new dimension in which the pendulum can swing. Between the world of apps and data and the utopia, Ben Bloom suggests, of decoupled apps and data.

The article What the composability revolution means for the martech stack appeared first on MarTech.