Why Every MarTech Stack Needs a "Decisioning Layer"?
There is a Data Layer. There is an Engagement Layer. But what's generally missing - a Decisioning Layer. Let’s unpack why this is fast becoming essential for modern marketing teams.
Today, we are going back to basics and back in time. Strange, isn’t it? We’re always chasing the future, thinking about how and when we can implement that “Nirvana Agent”. Not today. Easy, Tiger!
Let’s go to the fundamentals of Customer Management Systems. David Raab, Godfather of CDP, divides them into three broad categories, best seen as layers in a unified architecture: Data, Decisions, and Delivery. So no, I am not claiming to be the inventor.
Over the last several years, I believe Data Systems and Delivery Systems (or let’s call them Engagement Systems) have matured significantly. Yet, Decisioning Systems haven’t quite got their due. They’ve often been buried inside Data Systems or bundled into Engagement Systems. It’s time to give “Decisioning Systems“ its due focus.
The Evolution Reveals the Gap
In the early days, marketing technology was reactive. We collected data, analysed it weeks later, and launched batch campaigns based on historical insights. Today's leaders are moving toward proactive, real-time engagement that adapts to customer behaviour as it happens.
Companies that are building sophisticated Decisioning Layers between their data and engagement systems are the ones set to win in this new landscape. Take Netflix, for example - their centralised Recommendation Engine powers the entire experience. The results are:
Netflix's personalisation algorithms save over $1 billion each year by keeping subscribers from canceling.
75-80% of all viewing hours come from algorithmic recommendations, not user searches.
Defining the Decisioning Layer
Data Layer collects and stores customer information, but raw data doesn't drive action. Data Activation moves data between systems, but movement without intelligence is just plumbing. Engagement Layer executes campaigns, but execution without smart decisioning is just broadcast marketing.
The Decisioning Layer is where business logic, machine learning models, real-time analytics, and customer intelligence converge to make thousands of micro-decisions every second. It's where segmentation rules become dynamic audiences, where triggers become intelligent workflows, and where campaigns become personalized experiences. Think of it as an always-on AI-powered marketing brain that dynamically answers: “Given everything we know about this customer right now, what should we do next?”
At a high level, this layer encompasses three core functions- Analytics, Decisioning and Orchestration.
If you look closely, the Decisioning Layer is often the real centre of your MarTech stack. But here’s the strange part, many organisations and leaders still don’t consciously see Decisioning as the centre of their ecosystem.
In fact, in the MarTech Composability Survey by ChiefMarTec and MartechTribe, there’s no mention of 'Decisioning Systems' as a distinct category. My hypothesis? It’s a mix of reasons. Many organisations are still channel-led, so nearly 50% see their CDP or Marketing Automation Platform as the centre of their stack. The other reason could be that Decisioning as a concept isn’t well known. Even if organisations are doing some form of Decisioning, it’s often buried inside their CDP, MAP, or other platforms - not recognised as its strategic layer.
Should Decisioning be Centralised or Decentralised?
Apoorv Durga from Real Story Group has written an excellent article - Nobody Personalizes at Scale - And That’s Okay which aligns closely with my point of view. With channel proliferation, it’s next to impossible to deliver true personalisation at scale without centralised decisioning.
He argues, "Too often, teams start with channel silos: one personalization engine in the CMS, another in email, and a third within a mobile app." This fragmented approach creates duplicated effort, inconsistent logic, and lost context. The problem isn't just operational- it's strategic. When each channel operates its own personalisation or decisioning logic, customers experience disjointed interactions that feel more like marketing automation than genuine personalisation. Durga's research with enterprises struggling with personalisation consistently reveals the same pattern: channel-specific personalisation is a trap.
The solution? "Treat personalisation as a channel-agnostic service - a shared decisioning layer that feeds the correct variant to the right surface without reinventing logic and content rules for each system". This is precisely what the Decisioning Layer accomplishes: it becomes the single source of truth for customer intelligence, ensuring that every touchpoint benefits from the same rich understanding of customer context and intent.
The Competitive Imperative and the Future
The Decisioning Layer isn't a nice-to-have; it's a competitive necessity. Companies that can "re-decision multiple times within a single experience" will become far more relevant than those who cannot. The traditional approach of planned campaigns and batch processing is being displaced by always-on personalisation and real-time responsiveness. Brands that fail to implement sophisticated decisioning capabilities will find themselves competing with increasingly outdated tools against companies operating with AI-powered intelligence
The Decisioning Layer represents more than a technological upgrade - it's a fundamental shift toward customer-centric, data-driven marketing that adapts to individual needs in real-time. As AI continues to advance and customer expectations rise, the gap between companies with sophisticated decisioning capabilities and those without will only widen.
The companies that recognise this shift and invest in building robust Decisioning Layers today will be the ones setting the pace for customer engagement tomorrow. The question isn't whether you need a Decisioning Layer—it's how quickly you can build one that transforms your customer relationships and drives sustainable competitive advantage.
The age of reactive marketing is over. The age of intelligent, real-time customer decisioning is NOW.
I couldn’t agree more about the importance of the decisioning layer - my question is what tooling does this well today?
Pega is clunky. Evergage got bought by salesforce. Adobe’s vision if bold but expensive and requires a lot of support. Everything else in between is ultimately just a hard to use rule builder that’s hard to use without a dedicated “cdp” team.
My take is that there isn’t current an offering in market that elegantly solves the problem of real-time, cross-channel decisioning. Though I do believe we should expect to see new entrants to a category I’ve coined as “vibe decisioning” - ai powered web personalization and channel orchestration tools that work way better than the legacy rule builders ever could have.