The technological landscape is vast and data-driven. Compared to recent years, we have more robust data pipelines, expanding cloud storage solutions, new software as a service (SaaS) offerings, and AI technology that uses all the collected data. This has created an inflection point, where the data and the tools are beginning to catch up with marketing teams’ goals and customer expectations.
For some, this makes it an exciting time to work in a field like marketing — and to see what the future holds. This was the theme of Scott Brinker’s keynote address at GrowthLoop Live 2024. The “Godfather of Martech” sat down to chat about why now is such an exciting time for the technology that powers marketing operations.
A central subject for Scott’s excitement was the idea of the universal data layer, a concept that he tied to data aggregation, customer experiences, and AI technology.
The universal data layer
Through his research in creating the Martech Map, Scott says he’s noticed that the martech landscape has “certainly not gotten any smaller.” He estimates there are around 14,000 different martech products, and he hears about new platforms constantly.
“Every single one of these pieces of software operates on data. It's generating data, it's leveraging data, and this has become over time one of the greatest challenges and opportunities we have,” Scott said.
Meanwhile, the data cloud and data warehouse technology has advanced to a point where there is a dynamic partner ecosystem of tools that can plug into an organization’s data cloud. Thus, the dream of the universal data layer is becoming a reality.
“We've really started to see this universal data layer emerge throughout the martech stack, and throughout the larger company stack,” Scott said. “And that's really opening up some very interesting opportunities in how not just the architecture of martech, but the actual operations of martech can move forward.”
What is the universal data layer?
The modern customer data stack is composed of technologies that companies use to take in raw data from sources, structure and store that data, and then use it in tools for insights and actions. It’s made up of various components organized into layers, including the:
- Ingestion layer (where data is taken in from various sources)
- Data layer (where data is stored)
- Activation layer (where data is sent to tools for activation)
The data in the data layer is typically stored in a data warehouse or data lake. It is centralized into a single storage location, where other applications can query it and activate or turn it into insights.
Historically, most of the data sent through a data layer was used for analytical purposes. Until recently, information from the data layer fell mostly in the domain of business analytics teams. However, as technology has evolved and new data tools emerge, it’s become more common for other teams to make use of the data layer — thus making this more of a unified, or “universal” data layer.
How is the universal data layer changing the tech landscape?
New technologies and offerings are providing access to that data layer in a way that previously required more data infrastructure (or “plumbing”, as Scott put it). The rise of composability in martech and tools that use the universal data layer are democratizing data, and making it more accessible with less infrastructure, putting marketers in a perfect position to capitalize on the data their organizations have already been collecting.
“All these things take time, and we’ve seen over the last five years in particular, a real investment in talent and in products to lean into this universal data layer. And so, it’s now coming to a point where the feasibility, the actionability, the pragmatic ability, is here for us at the exact same moment that we’re like ‘this is the only path to deliver on these customer expectations.’”
He called the rise of software that can use data stored in data lakes and warehouses a “crossing of the streams," comparing it to the climax of 1984’s Ghostbusters.
“Increasingly, now that we had [data] pooling in one central location, having the ability to let any of those other applications, basically the frontline operations of our business, be able to pull data from that central universal data layer and be able to act on it,” said Scott.
What the universal data layer means for marketers
With more tools and access to the universal data layer, marketers can begin to make smarter decisions and use better techniques to leverage their data and insights. Scott provided a few strategic directions for marketers to consider when planning how to leverage the universal data layer:
Remember you’re competing against the 'last best experience'
Each year, customers have more options and choices in products and services. The experience those companies offer is becoming more important as a deciding factor for whether customers return — which makes a satisfying customer journey more important now than ever.
Scott said, “There's this amazing phrase I heard once, like ‘the last best experience someone has anywhere becomes the expectation of the experience they want everywhere’. Which is just a little bit of pressure here for those of us in marketing and customer experience.”
Ultimately, the customers’ expectations will be set by their positive experiences with competitors. The question is whether your company’s data can help you compete with those higher expectations.
For example, a customer could receive an email that's “completely disconnected from the website," or speak to a call center and learn that the reps don’t have access to their information.
“I mean, it's very frustrating to people because they now expect that companies should be able to connect these dots.”
These rising customer expectations have created an “inflection point," as he called it. But, he says, there’s a second inflection point that can help relieve some of the pressure this puts on marketing teams: The rise of the universal data layer is giving sales, marketing, and customer success teams the insights they need to provide these customer experiences, with the help of new tools, and the IT and data teams.
Lean toward aggregation over consolidation
With the rise of the universal data layer, strategies around data also have to change. Previously, the focus was on consolidation — using one martech tool that could do everything. However, the consolidation strategy never quite delivered the intended results, which means the strategy has started to shift toward aggregation.
.png)
Aggregation, as Scott describes it, is about making a large set of data easier for different tools and teams to consume, allowing teams to draw from a single source. The data warehouse is central to this aggregation strategy in action: As data is collected, structured, and stored, it is available for teams and applications to pick and choose specific pieces of information to use elsewhere.
As Scott explained, “It's almost like we're interfacing to something that has the best of both worlds. It's simplified to a single interface — like we wanted with consolidation — but at the same time it has this incredible richness and depth of variety that doesn't get lost, as it would with traditional consolidation.”
As marketers and companies add more data sources to their central data warehouse, and more destinations that can use the data, we get “a really nice flywheel” that gives more value out of the data that goes into it.
Enhance your human operations with AI
The analytical capabilities of artificial intelligence have a powerful opportunity to work with the technologies already in place. They have the potential to transform marketing and data roles by leveraging the data companies are already collecting.
“Going back to the very beginning of what made digital so exciting for marketing, it dramatically reduced the cost of experimentation, versus running campaigns in the real world where you had to put up physical billboards.”
Now, AI is poised to accelerate that experimentation further, Scott said.
“It's with AI here that we're starting to see this real order of magnitude — if not two orders of magnitude — of superpowers in reducing the time to be able to put these experiments together and dramatically expanding the set of individuals in the marketing organization who more and more have the capability to create these experiments on their own.”
With his excitement about the analytical capabilities of AI, and using AI tools with the universal data layer, Scott added that human touchpoints will remain important.
“It’s very clear AI is not going to have us all just living in a world of talking to chatbots. We all crave that human interaction, particularly at key stages throughout our customer experiences. But if you can now empower the human agents with these amplifications of insights with AI, they’ll be in a position to deliver to those customers the best of both worlds.”
When asked what steps people can take to bring this vision, Scott had some suggestions to “really lean in on the people dimension of this,” which he outlined as:
- Develop the talent on your teams
- Invest in training those teams
- Give teams more time to collaborate and experiment.
On that last point, he also recommended that leaders need to “get their hands dirty,” that they should be using the tools, and figuring out how they work.
The next 10 years in martech are going to be a wild ride
Saying that “the timing is just right,” Scott said he is excited to see what these technologies can do together. As the tech improves and integrates, the focus will become less about crafting individual marketing pieces and more about how we orchestrate the whole customer journey.
"The way in which we bring cohesion to that is also going to come from AI. As long as we've got all the data connected, is going to be in a position to help us orchestrate that. So, I'm pretty bullish that the next 10 years are going to be a wild ride, but overall an incredibly productive one for all of us."
