

The Future of MarTech Is Composable
How to Power Customer Engagement With Data
- Faster access to actionable data—no IT bottlenecks, no redundant storage.
- Seamless cross-channel personalization—AI-driven decisioning for precision engagement.
- Unmatched flexibility and scalability—choose the tools that fit your needs without vendor lock-in.
The Future of MarTech Is Composable
How to Power Customer Engagement With Data
- Faster access to actionable data—no IT bottlenecks, no redundant storage.
- Seamless cross-channel personalization—AI-driven decisioning for precision engagement.
- Unmatched flexibility and scalability—choose the tools that fit your needs without vendor lock-in.


The MarTech Stack Dilemma—Promise vs. Reality
Martech stacks are built on a simple promise: manage the customer data lifecycle and empower marketing teams with actionable insights. But in reality, most stacks fall short—fragmented data, siloed tools, and disconnected workflows slow down execution and limit impact.
There’s much debate about how to architect and build a martech stack for optimal data performance. For example:
- How should marketing and data teams collaborate for seamless activation?
- What’s the right balance between governance and agility across multiple solutions?
- Should you use specialized point players or consolidate under an all-in-one platform?
The debate isn’t new. As a recent industry analysis put it:
“The martech landscape has long been caught between two competing narratives: the promise of all-in-one marketing suites and the flexibility of point solutions.”
The future of marketing isn’t about choosing one or the other—it’s about breaking free from rigid, outdated models and activating customer data on your terms. Let’s explore how that works.
The Reality of All-in-One Platforms
All-in-one platforms promise to be the “single source of truth” for customer data. But in practice, they rarely deliver. The average company juggles over 2,000 data silos, making it nearly impossible for marketing teams—and the data engineers supporting them—to consolidate everything into a marketer-friendly system on their own.
For data centralization to be successful, you need a company-wide effort. To compensate, businesses often store the same information across multiple tools, creating duplicative storage.
What is duplicative storage?
Duplicative storage happens when the same customer data is stored across multiple systems due to disconnected platforms and siloed workflows. This redundancy increases costs, creates inefficiencies, and leads to inconsistent insights. Consolidating data into a centralized warehouse eliminates redundancies, improves accessibility, and ensures more accurate, up-to-date insights.
But even then, data remains locked in separate systems, forcing data teams to extract insights manually. The result? No single, unified view of customers, campaigns, or performance. It’s no surprise that only 4.2% of companies use multi-product marketing suites as their central platform.
The problem doesn’t stop there. Even when marketers buy into an all-in-one solution, they still need point solutions to get the job done. 83% of companies end up using alternative tools instead of the built-in features of their primary platform. Why? Because most all-in-one platforms aren’t truly integrated—they’re a patchwork of acquired technologies, not purpose-built solutions.
This leads to:
- Fragmented workflows – Marketers juggle multiple logins just to access basic functionality.
- Disconnected data – Customer insights remain siloed across channels.
- Lagging performance – Even when data is available, it’s often not in real-time, slowing decision-making and delaying critical marketing moments.
This gap between the promise of all-in-one platforms and reality has significant negative consequences for marketing teams.
The Cost of Fragmented MarTech
Efficiency Gap |
Marketing Impact |
Broken Workflows Marketers must switch between multiple logins and disconnected tools just to execute customer communications. |
Reduced Marketer Agility Marketers file JIRA tickets for data access, slowing down their ability to deploy customer communications at the right marketing moments and drive real-time decisioning. |
Disconnected Data Customer insights remain siloed, making it difficult to orchestrate seamless, personalized experiences across channels. |
Backlogged Data Teams Data teams must allocate bandwidth to support marketing with extraction and integration versus transforming data into valuable signals or predictive models. |
Lagging Performance Even when data is accessible, it’s often delayed, leading to missed opportunities for timely engagement. |
Increased Organizational Spend Internal inefficiencies and missed engagement windows drive up spend on re-engagement and manual workarounds. Budget that could be allocated to customer acquisition, headcount, and more is spent on technology. |