11 June 2026
Is your customer engagement platform really engaging?
Lisa Loftis
Principal Product Marketing Manager, SAS
If you haven’t focused on the middle layer of your customer engagement platform (and most haven’t), it could be taking you in the wrong direction – making engagement more difficult, less effective and more costly.
What came before the customer engagement platform?
History can yield some interesting insights here. Customer information file (CIF), marketing customer information file (MCIF), operational data store (ODS), master data management (MDM), customer data platform (CDP) and multichannel marketing hub (MMH) – I have lived through all of these and experienced their attendant shortcomings.
As marketers, we have been chasing the holy grail of unified data and personalized messages for a very long time, with each successive “innovation” promising to improve on the last. Most with only middling degrees of success (pun intended).
Fast forward to today with our current solution du jour: the customer engagement platform (CEP), which may finally be the closest thing yet to that holy grail.
A customer engagement platform connects customer data, decisioning, orchestration and delivery to help marketers create more relevant, timely and consistent experiences across the customer journey.
But achieving that holy grail status requires a prescriptive approach that focuses on the right areas.
What is a customer engagement platform?
A CEP connects data, decisioning and activation to deliver personalized customer experiences in real time across channels.
More complex MarTech stacks don’t equate to better customer engagement
On one hand, marketers are armed with money and have both the enthusiasm to spend it and the tools available to spend it on. McKinsey projects that the MarTech market will be valued at $215 billion or more by 2027, representing a near doubling in just five years. They also indicate that “more than a quarter of marketing decision-makers expect spending on MarTech to continue to increase, by up to 25% in the next three to five years.”
Scott Brinker calls MarTech stacks “rivers not lakes” because they are in constant motion. According to Brinker, “Organizations are bringing on more than eight new tools every month, representing an annualized growth rate above 35%. They’re also churning out tools they’ve stopped using. The stack is in constant motion – a river of apps flowing in and out, not a stagnant lake.” We are actively searching for and investing in ways to improve the flow of our rivers.
And AI is clearly fueling the fire – for both enthusiasm and spending. According to Brinker, spending on AI-native applications jumped 108% overall.
On the flip side, enthusiasm and budget do not automatically ensure success. Marketers today are also suffering from underutilization of existing MarTech, bloated stacks with duplicated capabilities, channel proliferation and a lack of ability to prove ROI.
In addition to their data on spending and enthusiasm, McKinsey also highlights issues with today’s stacks, saying complexity corrupts the customer connection. According to McKinsey, “47% of MarTech decision-makers cite stack complexity as well as system and data integration challenges as key blockers that prevent (or could prevent) them from getting value from their MarTech tools.”
When MarTech value suffers, mediocre results typically follow.
The 3 layers of a customer engagement platform
Regardless of current complexity issues, customer engagement platforms are considered to have three distinct layers: data, delivery, and decisioning and orchestration.
Data layer
The bottom layer is where the data to fuel the marketing machine resides. The data layer includes applications such as standalone CDPs (originally conceived to ingest, unify and provision customer data), data warehouses, cloud data platforms such as AWS or Snowflake, some CRMs and older applications such as CIF, ODS and MDM.
Delivery layer
The top layer – also called the activation layer – is where the ultimate payoff happens. Marketing messages are delivered and responses are captured. It includes email, mobile, web, social, advertising solutions, etc.
Decisioning and orchestration layer
The middle layer identifies and segments audiences, defines customer journeys, tests assumptions, optimizes outcomes, applies AI and sets up the decisions. This layer is the brain of the whole operation. And this is where the magic happens.
So where does the CDP fit in a customer engagement platform?
A customer data platform is designed to unify customer data and create a clearer view of the customer. A customer engagement platform then builds on that foundation by using that data to make decisions, orchestrate journeys and coordinate interactions across channels. Think of it this way: A CDP helps you know the customer, while a CEP helps you act on that knowledge.
How is a CEP different from a CDP?
A CDP unifies customer data. A customer engagement platform uses that data to make decisions and deliver personalized messages. Together, they turn unified data into more relevant customer interactions.
What is the middle layer – and why does it matter?
Think of the middle as what’s between the beginning and the end – or between the top and bottom when it comes to the MarTech stack. When you consider all the important functions that happen in the middle – segmentation, journey definition, AI, real-time decisions – there’s no doubt that this layer is the heart of the modern customer engagement platform. It’s the destination we’ve arrived at after a journey with many other iterations along the way.
Knowing all this, it seems like the importance of the middle should be a no-brainer, right? Unfortunately, that’s not the current reality.
In their latest benchmark survey, Demand Gen articulated the problem quite well: “Marketers in recent years have been drowning in data but starved for insight. … The struggle was clear: a lack of visibility across the buyer’s journey, messy CRM data, and an inability to track activity between channels.”
Key benefits of a modern customer engagement platform
Why are we just now arriving at a clear focus on the middle – and why does it matter? At SAS, we see this shift driven by several factors. Marketers have long underinvested in the middle for various reasons. However, as MarTech stacks evolve, the middle is essential – delivering capabilities and benefits marketers have historically lacked.
Break down channel silos to deliver consistent customer experiences
Brands are often siloed into channels (e.g., email, direct mail, web, social media) with personalization engines for each individual channel – leading to disconnected, siloed experiences. The middle layer treats customer journey orchestration and decisioning as a channel-agnostic service layer – fixing disjointed communications and vastly improving customer experiences and marketing results.
Enable real-time customer engagement and decisioning
The world has moved from reactive, batch-processed campaigns to proactive, real-time engagement that adapts to customer behavior as it happens. This requires a middle layer that can make personalized and contextual decisions in milliseconds. In today’s world, real-time decisions must actually be made in real time.
Maximize AI-powered decisioning and personalization
AI-powered intelligence is becoming the conductor for marketing activity. The middle layer now combines predictive analytics, machine learning models and rules engines to determine the right content, timing and channel for each individual – automatically.
Why analysts are focusing on the middle layer
Analysts and MarTech experts agree that the emergence of the middle layer is essential. Scott Brinker discusses how the MarTech stack is shifting from SaaS (software as a service) to CaaS (context as a service).
Brinker notes, “Context is different. Context is personal and situational. It’s knowing not just what the data says, but what it means for this marketer making this decision, or for this customer in this moment. Context is where domain expertise meets operational reality.” This is the perfect description of the middle.
And even the ubiquitous and ever-changing CDP is getting in the game. MarTech Square noted in a recent Substack article that “one of the more telling signals in this year’s Gartner [Magic Quadrant] report isn’t where vendors landed, but how the language has shifted.
“There’s far less emphasis on the single customer view and much more on context, decisioning and orchestration. ‘Decisioning’ is referenced 35 times and ‘Orchestration’ is referenced 39 times in the CDP MQ report.”
And where do decisioning and orchestration come together? Right in the middle.
6 signs your middle layer needs an overhaul
So, as marketers, how do we get there? How do we ensure our middle layer is primed to master the decisioning and orchestration capabilities we need?
First, take a good look at the challenges you are facing. If you recognize two or more of these challenges, your customer engagement platform’s middle layer likely needs attention:
- Lack of real-time customer insights. Your team struggles to access and act on customer data quickly for hyperpersonalized experiences.
- Inconsistent brand experience across channels. Unifying messaging and engagement across multiple touchpoints is difficult.
- Scaled personalization without complexity. Current AI capabilities are not living up to the promise to scale tailored marketing efforts efficiently.
- Measurement of brand strategy impact. You cannot easily track and prove ROI for innovative brand initiatives.
- Fragmented MarTech stack. Your stack includes multiple tools that don’t integrate well, leading to inefficiencies and data silos.
- Lack of time for strategic work. You and your team are bogged down in execution, with no bandwidth to focus on higher-level strategy.
Why does the middle layer matter in a CEP?
Without a strong middle layer, MarTech stacks struggle to deliver effective, consistent customer engagement. This layer connects data with activation, so marketers can deliver real-time, personalized experiences across channels.
What are the key features of a modern customer engagement platform?
When you are ready to shore up that middle decisioning and orchestration layer, these are the must-have capabilities to look for in a customer engagement platform:
Zero-copy data activation
The CEP should be able to access and activate unified customer audiences without moving data, eliminating CDP complexity, costly ETL and infrastructure expansion. The platform is cloud‑ready, data‑agnostic and integrates with existing systems for hybrid and multicloud strategies. There are capabilities that allow for any data, any source, any time and incorporate AI and agentic AI audience creation and validation.
Native and extensible architecture
Look out for large vendors whose middle-layer capabilities are by acquisition since this will not resolve stack complexity, integration and timeliness issues. Native architectures, built from the ground up, help eliminate integration issues across your stack and truly tie all three layers together seamlessly.
Open and extensible middle layers, out-of-the-box connections to cloud-based data sources, extensive API connector frameworks and bidirectional connectors to applications across and beyond the MarTech environment help you make the best use of existing MarTech capabilities while also strengthening the middle.
AI-powered marketing analytics
Your CEP should include customer analytics and marketing analytics capabilities that work for marketers as well as for data scientists, with embedded marketing-oriented use cases, guided AI data preparation and model building specifically for marketers. AI capabilities should enable rapid predictive modeling with full IP ownership, provide transparent, explainable analytics, and have built-in bias and performance monitoring.
Decisioning for marketers
Business rules that produce good decisions (e.g., ones that can optimize between multiple possible offers) can be very complex. Many decisioning engines require a data analyst or data scientist to build the decision nodes.
Instead, look for decisioning components that incorporate intuitive, flexible marketer-led frameworks that cater to marketing use cases (such as next-best action, abandoned basket, churn, etc.) with out-of-the-box templates that make it easy for the marketer to create and deploy. Incorporation of AI models and true real-time decisioning capabilities is also critical.
The heart of your customer engagement platform
As decisioning and orchestration become the convergence point within the MarTech stack, the middle layer is where it all comes together. It brings together data, decisioning and activation to enable real-time, personalized customer engagement across channels.
So as you evaluate your customer engagement platform, remember: MarTech success stories really do begin in the middle.
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SAS® Customer Intelligence 360 is an AI-powered customer engagement platform that turns customer insights into real-time, personalized actions across every channel. It delivers intelligence in the critical middle layer – connecting your data foundation to journey orchestration and activation at scale.