2025 and Beyond: Convergence, Challenges and Opportunities in Adtech and Martech
As we conclude 2024, I've been reflecting on the current landscape of marketing technology—and, to some extent, advertising technology.
Who would have thought global warming could impact martech too? Jokes aside, the past few years have been anything but predictable. Whether we’ve been in the eye of the storm or just caught in the chaos, it’s clear this ride hasn’t been smooth sailing.
Taking a Look Inside Categories
Let’s dig into a few categories. I’ll take a “top-down” approach, starting with delivery systems, to explore how and why different categories are converging with their adjacent ones. This convergence isn’t just a buzzword anymore—it’s shaping the future of how martech and adtech ecosystems operate.
Legend for capabilities in each category: [Capability] => occasionally present
Channel Specific, such as ESP
Weather Forecast: Mostly cloudy — not much to happen
Capabilities: {For one channel} Audience Segmentation | [Orchestration] | Delivery
Category Growth: Adding channels, moving towards CEP
Vendor Examples: Iterable (email), Braze (AppBoy for mobile)
Many vendors initially specialized in single-channel delivery systems. For instance, Unica began with a focus on direct mail, while more recent players targeted digital channels like email or mobile. Over time, expanding into multiple channels became a natural progression, leading these vendors into the Customer Engagement Platform (CEP) category—a space that encompasses various acronyms such as Marketing Automation Platforms (MAP) and Multichannel Marketing Hubs (MMH).
Take Braze (formerly Appboy) and Iterable as examples. Braze started with a focus on mobile engagement, while Iterable began with email marketing. Today, both platforms offer orchestration across a broader spectrum of channels.
Conversely, solutions that remained email-centric became acquisition targets to enhance broader service portfolios. For example, SparkPost was acquired by MessageBird, and SendGrid was acquired by Twilio, initially specialized in mobile for developers and leveraging the acquisition to spin up its Twilio Engage offering.
Customer Engagement Platform (CEP)
Weather Forecast: Rain, holding steady on delivery
Capabilities: {For 2+ channels} Audience Segmentation | Orchestration | Delivery
Category Growth: (1) moving towards CDP, (2) adding paid media channels
Vendor Examples: Braze, Bloomreach, Klaviyo
The key advantage of CEPs over channel-specific solutions is their ability to control and execute customer experience (CX) use cases across multiple channels. Despite the observation that many organizations remain focused on a single channel, like email.
We’ve observed two main growth trajectories among CEP vendors:
Adding a CDP: CEPs face a fundamental limitation: they assume customer data is already clean and well-organized. When this assumption fails, implementations often crumble. Having built a customer 360 using a CEP tool myself, I can confidently recommend to steer away from this idea, it might work, but it’s not the right tool for the job.
Adding Paid Media Channels: With the ongoing convergence of martech and adtech, CEPs have started integrating directly with major paid media channels. For example, Braze and Iterable added integrations with Facebook, reflecting this shift.
However, there’s a looming threat for CEPs, and it’s coming from the next category I’ll cover: CDPs.
Customer Data Platform (CDP)
Weather Forecast: Thunderstorm (despite Forrester wave)
Capabilities: Identity Resolution | Audience Segmentation | [Orchestration] | Activation
Category Growth: (1) moving towards orchestration, and possibly even delivery, (2) adtech use cases, (3) data collaboration
Vendor Examples: ActionIQ, Twilio, Treasure Data
The CDP category is notoriously complex, largely due to the diverse origins of the solutions available on the market. To simplify, I’ll reference the original CDPi definition: a CDP is a solution designed to unify data and create a customer 360 view.
For the past few years, the rise of cloud data warehouses (CDW) has disrupted the CDP space in a big way. Many IT and data teams are opting to build their customer 360 directly in-house using these data warehouses—aka data lake, lakehouse, data cloud (it’s not all the same but in the context of a CDP, the differences don’t matter). This shift has opened the door for a category of vendors offering “reverse ETL” solutions to start tackling marketing use cases. Traditional packaged CDPs began evolving, introducing a new buzzword into the mix: composable CDP.
Some legacy vendors still argue for buying a fully packaged solution to build your customer 360, but many have pivoted to enhancing the business user experience on top of an existing C360. ActionIQ, for instance, has had a journey orchestration layer for quite some time, while vendors like Twilio and Treasure Data have more recently added their own orchestration capabilities.
This evolution has created an intriguing dynamic within organizations, where stacks now often resemble one of two configurations:
[CDP = Audience Segmentation + Orchestration] | [MAP = Delivery]
[CDP = Audience Segmentation] | [MAP = Orchestration + Delivery]
I’ve got more to say on how to choose between a CDP or a CEP for orchestration in today’s market—but I’ll save that discussion for another day. That said, it raises the question: will CDPs eventually integrate natively with delivery systems (like email), effectively merging the CDP and CEP categories?
To my knowledge, Adobe is the only enterprise vendor actively pursuing this vision today. Its Real-Time CDP handles audience segmentation, while Adobe Journey Optimizer offers orchestration and delivery—all built on Adobe Experience Platform (AEP). Adobe is attacking all fronts as they are also going after data collaboration use cases.
Data Clean Room (DCR)
Weather Forecast: Fog — not completely defined
Capabilities: Data Collaboration | Audience Segmentation | [Activation] | Measurement
Category Growth: Towards advanced audience segmentation, activation, possibly orchestration
Vendor Examples: InfoSum, LiveRamp, Snowflake, Adobe
DCR is the only adtech category I’ll touch on here, even though the broader adtech landscape—DSPs, SSPs, and more—has plenty to discuss. As one of the most recent entrants in the space, DCRs are the most likely to experience significant evolution as the category matures.
DCRs are often confused with CDPs. The two categories share overlapping capabilities, but their foundations are fundamentally different.
DCRs were originally designed for data collaboration between two or more parties, enabling secure work on their respective first-party data. Their primary use case was measurement. However, many DCRs have since added activation capabilities, which raises a question: Should brands activate through their DCR or their CDP?
And here’s another thought: What if DCRs began adding orchestration capabilities in the future? This potential evolution could blur the lines even further.
Additional Notes
Did I forget to mention DMPs? Apologies—even with Google giving third-party cookies another life extension, DMPs are pretty much zombies at this point. When they’re not outright abandoned (like Oracle and Salesforce’s DMPs), vendors such as Permutive have pivoted their approach entirely to stay relevant.
In the ongoing convergence of adtech and martech, one noteworthy growth strategy has been Zeta’s. Originally a CEP player, Zeta has made significant moves to become a platform across multiple categories: CEP, CDP, DSP, and even data provider, further expanded with their recent acquisition of LiveIntent.
Don’t Buy a Category
It’s all too tempting—and common—to hear, “I’m shopping for a [Insert Tech Category Here].” But given the significant overlaps and convergence in martech and adtech today, organizations need to rethink this approach. Instead of shopping by category, focus on the challenges you’re trying to solve within your existing stack, tools, or processes.
🔑 Your evaluation might lead you to vendors across multiple categories—and that’s perfectly fine. The key is to prioritize solving your specific problems, rather than chasing the expected capabilities tied to a particular category.
Looking ahead, I anticipate that AI—particularly GenAI—will disrupt traditional martech applications. That said, this disruption will take time. In 2025, we’ll likely see the continued emergence of opportunities without fully replacing how use cases are executed today. For now, the fog remains thick, obscuring our view of the shore.