Feature
The Gist
- Frankenstacks slow marketing down. Disjointed, bloated martech stacks trap data, waste budget, and burn out teams.
- Composability changes the rules. Modular, API-first tools replace brittle integrations with seamless, flexible systems.
- AI is the connective tissue. It automates workflows, bridges data gaps, and orchestrates customer experiences in real time.
- The payoff is agility. Composable, AI-driven stacks help marketers scale faster, cut costs, and deliver personalized experiences.
Marketers have spent years stitching together marketing technology “Frankenstacks”—bloated, patchwork collections of tools that barely talk to each other. The result? More headaches than harmony, and plenty of missed opportunities. But that era is fading fast. Thanks to the rise of composable architectures and the integration of AI, businesses are finally breaking free from brittle, one-size-fits-none martech setups.
Today, a new approach is emerging—one that prizes flexibility, interoperability, and smart automation over intolerable complexity. Here’s why composability (and the right AI) are changing the game for marketers everywhere.
Table of Contents
- What Are Frankenstacks in the Marketing Technology World?
- The Frankenstack Problem: How Did We Get Here?
- What Is Composability in Martech?
- The Role of AI in the New Martech Stack
- Benefits of a Composable, AI-Driven Martech Stack
- Barriers & Challenges to Composability
- How to Get Started: Practical Steps for Marketing Leaders
- Conclusion: Goodbye, Frankenstack in Martech
What Are Frankenstacks in the Marketing Technology World?
The infamous "Frankenstack" isn’t just a metaphor—it’s the day-to-day reality for many marketers. Picture this: a customer relationship management platform (CRM) here, an email platform there, a handful of analytics tools, a chatbot bolted on top, all patched together with custom integrations and manual data transfers.
Each new tool was meant to solve a problem, but over time, every addition just created more complexity, trapped more data and made campaigns harder to manage. It’s no wonder marketers started calling these tangled stacks "Frankenstacks."
Frankenstack vs. Composable Martech: Feature Comparison
| Feature | Frankenstack | Composable Martech |
|---|---|---|
| Integration | Manual, fragile, and time-consuming | Seamless, API-driven, modular |
| Data Flow | Siloed and inconsistent | Unified and real-time |
| Scalability | Difficult and expensive | Flexible and on-demand |
| Cost | High, with redundant tools | Optimized, reduces tech debt |
| Time-to-Market | Slow, with frequent delays | Fast, supports rapid launches |
These unwieldy martech stacks aren’t just an IT headache. They sap marketing agility, drive up costs and make it nearly impossible to deliver the unified, personalized experiences customers expect. Every workaround is a reminder that the stack wasn’t built to flex, scale or evolve.
But that’s changing. A new approach—composability—is taking hold. Instead of stitching together incompatible parts, composable martech lets you assemble best-in-class modules that fit together by design. And with AI in the mix, marketers can finally automate manual tasks, bridge data gaps, and orchestrate campaigns in real time.
Related Article: Beyond the Mirage: A Data-Driven Blueprint to Tame Martech Complexity
The Frankenstack Problem: How Did We Get Here?
Frans Riemersma, founder of technology research firm MartechTribe and a CMSWire contributing author, told CMSWire that "Frankenstacks" are the result of martech myopia. "Martech doesn’t solve anything unless the company has a clear goal. Outperformers know this and keep the core of their stack lean and mean."
The term “Frankenstack” captures the reality facing many marketing teams today: a sprawling patchwork of disconnected tools, cobbled together over time in response to shifting needs, new channels and vendor promises. Born out of necessity—and sometimes desperation—these martech stacks were never architected as a single, cohesive system. Instead, they’re stitched together piece by piece, much like Frankenstein’s monster, with each addition intended to solve a specific problem but often creating new ones in the process.
Why Frankenstacks Fail in Martech
Disconnected stacks fragment customer context, making hyper-personalization impossible and sapping team energy.
Maryna Hradovich, co-founder and COO at Maestra, told CMSWire, "Disconnected tools shred context into pieces, and without context, hyper-personalization—the standard customers now expect—just can’t happen...marketing teams that try to personalize with fragmented stacks are like heroes fighting their own tools—stuck in technical battles instead of serving customers. The outcome is costly: companies pour resources into IT but still fail to achieve true real-time personalization across all channels."
Hradovich emphasized that fragmented stacks force marketers to focus on technical workarounds instead of customers, resulting in heavy IT spend and poor personalization outcomes.
The origins of the Frankenstack problem are easy to trace. As digital marketing exploded over the last decade, businesses chased innovation by adding specialized tools for everything from email automation to social media listening to personalization engines. Rather than consolidating around a unified platform, teams found themselves managing a tangled web of point solutions, homegrown integrations and overlapping features. What started as agility quickly became complexity.
Such complexity shows up in familiar pain points:
- Integration nightmares: Connecting data and workflows across tools is costly, fragile and time-consuming. When one system changes, the whole stack can break.
- Data silos: Customer information gets trapped in separate platforms, making unified insights and personalization nearly impossible.
- Bloated spend: Redundant or underused tools drive up costs, and “shadow IT” flourishes as teams buy their own solutions.
- Vendor lock-in: Teams become dependent on specific vendors’ proprietary systems, limiting flexibility and making migrations daunting.
Anjali Yakkundi, VP of product marketing at marketing agency Movable Ink, told CMSWire, "The Frankenstack approach relies too heavily on each solution owning its own data—a consequence of the mythical, long-pursued but largely unattainable '360-degree customer view.' Each tool collects data differently, and activating it requires complex, months-long integration projects. As a result, teams spend more time reconciling dashboards than acting on insights, which slows decision-making, leads to subpar customer experiences, and uneven (or even uninterpretable) results."
Consider a very likely real-world example: A retail brand adopts a popular CRM, then adds a separate email platform, a third-party analytics tool, and a chatbot service—each with its own database and reporting. Soon, marketing campaigns require endless CSV exports, manual updates and workarounds to synchronize data. Valuable insights are lost in the shuffle, and launching new campaigns or responding to customer needs becomes painfully slow.
Related Article: The Cost of Martech Chaos Is Rising
Hidden Costs of Patchwork Stacks
Marketers struggling with Frankenstacks face more than technical headaches—these patchwork systems slow growth, create workflow breakdowns and force talented employees to act as integrators rather than strategists.
The consequences of Frankenstack technology setups extend far beyond technical headaches. Teams become bogged down in integration work, campaign speed slows, and leadership loses faith when data doesn’t sync or attribution gets messy.
"Frankenstacks kill momentum. Every integration becomes duct tape. Every campaign hits latency. And when something breaks, no one knows where or why. You end up with teams chasing bugs instead of building. Data doesn’t sync, attribution gets messy, and leadership loses faith in the tech. We've seen marketers get burned out trying to force disconnected tools into alignment," said Bryan Cheung, co-founder and CMO at digital experience platform provider Liferay.
This is the heart of the Frankenstack dilemma: what began as a drive for innovation and best-of-breed solutions has left many businesses with a monster on their hands—one that’s difficult to control, expensive to maintain, and ill-equipped for the demands of modern, data-driven marketing.
What Is Composability in Martech?
A truly composable martech stack isn’t just a random assortment of tools. It’s built around modular, interoperable components—like Legos—grounded in shared data models and a digital experience platform (DXP), giving teams both structure and flexibility. Cheung explained, "A real composable stack is built like Lego, flexible but structured. It starts with shared data models, event-driven logic and a digital experience platform that lets marketers plug in what they need without breaking everything else. Unlike all-in-one suites that lock you in or Frankenstacks that fall apart, composable stacks give teams control. You can move fast, scale smart and avoid the trap of building custom solutions for problems that shouldn’t exist in the first place."
Yakkundi stressed that composability isn’t about cobbling together best-of-breed tools or buying into monolithic all-in-one suites. Instead, she argued that composable stacks should make it easy to access and activate federated data—connecting loyalty programs, CDPs and data warehouses without months of custom integration. Real composability, she noted, is achieved through sustainable, user-friendly integrations and empowering marketers to own business logic and journey orchestration, not just IT.
"Large enterprises will never realistically achieve a perfect 360-degree view of the customer, and they shouldn’t spend years chasing it. Instead, brands should focus on composable solutions that make it easy to access and activate federated data across systems," Yakkundi reiterated.
Related Article: The Composable Mindset: It's Not About the Technology
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Composability as the Antidote
Composability is the antidote to Frankenstack chaos. At its core, composability in martech means building your stack out of modular, interchangeable components that are designed to work together without friction—no matter where they come from or who built them. Instead of wrestling with rigid, monolithic platforms or patching together a jumble of point solutions, composable martech lets you select the best tools for each job and connect them through open standards.
Unlike the “suite” approach—where a single vendor supplies most of your tools—or the “best-of-breed” model—where you cherry-pick top solutions but risk integration headaches—composability is about flexibility without the friction. Every component is designed to be plug-and-play, so marketing teams can swap out tools, scale up, or innovate without tearing everything down and starting from scratch. Key components of composability include:
- Modularity: Each part of the stack is self-contained but easily connects to others, so you can update or replace tools without major disruption.
- Interoperability: Tools share data and workflows through standardized connections, eliminating silos and optimizing operations.
- API-First Design: Every solution is built with integration in mind, using robust APIs that enable pain-free connections, automation, and orchestration of processes across your entire business.
While composability is about flexibility and modularity, it still requires a unified foundation. As Hradovich explained, "When choosing a unified solution, I recommend selecting one with a Customer Data Platform (CDP) at its core. A CDP builds a single, unified profile of each customer that brings the missing context marketers need." She suggested that with the right foundation in place, brands can personalize at scale and realize measurable business impact.
Finally, Riemersma emphasized that the best composable stacks are rolled out “with decommissioning in mind.” Only those features or modules that map directly to business goals are added—so teams can easily swap, retire, or upgrade tools as needs evolve, rather than accumulating tech debt.
The Role of AI in the New Martech Stack
AI isn’t just another layer in the martech stack—it’s becoming the engine that powers smarter, more connected marketing environments. With composable architectures, AI can finally do what it does best: bridge gaps, automate tedious work, and unlock insights that traditional systems would miss.
AI now powers far more than isolated marketing features—it acts as connective tissue across the stack, driving automation, orchestration, and self-improvement when given clean integration points. "AI is moving from buzzword to backbone. At Liferay, we’ve seen it radically improve how we manage support operations. Right now, 48% of our support tickets are resolved without a human touch," said Cheung. "AI can be great not just at proposing a fix but also at auditing its own work and correcting its logic when it misfires. That kind of orchestration is where AI shines. It doesn't just assist. It connects, decides, and learns, if the stack gives it room to move. Without clean integration, AI’s potential stays stuck at the edge."
Riemersma highlighted that AI isn’t just making integration easier for commercial tools; it’s increasingly being embedded in homegrown, "Hypertail" applications—from customer portals to configurators—enabling new levels of automation and orchestration via agentic AI components.
AI as Marketing’s Operating System
By weaving AI into composable stacks, marketers can move beyond rule-based triggers and static workflows. AI can analyze customer behavior in real time, personalize content and offers on the fly, and put together campaigns across multiple channels with minimal manual input. For example, an AI-driven CDP can unify customer data from dozens of sources, segment audiences dynamically, and trigger tailored experiences—no human intervention required.
Marketers have long struggled to access and activate customer data spread across siloed tools, often spending more time reconciling dashboards than acting on insights. "AI is changing this dynamic by serving as the connective tissue, simplifying integrations, harmonizing data, and enabling real-time orchestration. For example, at Movable Ink we’re exploring how AI can automatically map fields and resolve data schema mismatches between systems, making it seamless for marketers to activate their data," said Yakkundi.
AI also plays a crucial role in automating the connections between modular tools. Integration Platform as a Service (iPaaS) solutions powered by AI can intelligently route data, resolve errors, and suggest optimizations, eliminating much of the headache that once came with managing integrations. Similarly, workflow automation tools now use AI to predict next steps, recommend actions, and even adapt processes as business needs evolve.
AI excels at translating, connecting, and analyzing data across multiple sources, even if you don’t want to fully re-integrate everything. "AI does a fantastic job at understanding and translating data. It can take your five different sources of data and figure out that 'company_name' in one system corresponds to 'account_title' in another, even when the actual company names are formatted differently. Even if you don't want to embark on a full integration initiative, AI can make connections between your data sources and provide complex analysis with ease," said Lewis.
In a composable martech stack, AI is the connective tissue—it turns a collection of modular tools into a responsive, learning system that adapts in real time. The result is a marketing engine that’s not only flexible, but continuously improving, capable of delivering the right message to the right person at the right moment—without the manual heavy lifting.
Benefits of a Composable, AI-Driven Martech Stack
Switching to a composable, AI-powered martech stack isn’t just about solving old problems—it’s about unlocking new advantages that can transform the way marketing teams operate.
Top Benefits of Composable, AI-Driven Martech
The table below outlines the primary advantages of composable, AI-driven martech stacks compared to traditional setups.
| Benefit | Description |
|---|---|
| Agility | Easily adapt to new channels, tools, or market needs. |
| Personalization | Deliver targeted, relevant experiences in real time. |
| Cost Efficiency | Reduce redundant tools and lower tech maintenance costs. |
| Unified Data | Break down silos for a single view of the customer. |
| Future-Proofing | Build a stack that evolves as your business grows. |
| Flexibility and Scalability | Composable architectures enable you to swap, add, or upgrade tools as your needs change, without tearing down your entire stack. Whether launching a new campaign, entering a new market, or experimenting with emerging channels, you can adapt quickly—no vendor lock-in or months-long migrations required. |
| Holistic Attribution | Composable stacks enable flexibility, attribution, and growth without the chaos of traditional approaches. Marie Bahl, CMO at enterprise marketing platform provider Uptempo, noted: “The key advantages over traditional approaches are agility, cost-efficiency, and scalability. Composability bridges this: you get best-in-class flexibility without the chaos, enabling faster pivots, better ROI through holistic attribution, and reduced vendor lock-in.” |
| Faster Time-to-Market | With modular systems and AI-driven automation, new campaigns and customer experiences can be built, tested, and launched at speed. Marketers no longer wait on IT for integrations or get bogged down by manual workflows, so ideas move from whiteboard to reality faster than ever. |
| Improved Data Flow and CX | Composable stacks break down data silos and enable pain-free sharing across platforms. With AI handling real-time analysis and orchestration, marketers can deliver more personalized, relevant experiences. |
| Reduced Tech Debt | By eliminating redundant tools and optimizing integrations, composable stacks help cut unnecessary costs and reduce ongoing technical debt. Teams can focus resources on innovation and growth rather than maintaining brittle, outdated systems. |
| Repeatable Growth | A composable, governed data core means faster changes, cleaner experiments, and better results. |
Barriers & Challenges to Composability
While the promise of composable, AI-driven martech is compelling, the journey isn’t without its hurdles. For many businesses, the biggest barriers are as much about people and process as they are about technology.
Shifting to a composable approach often means rethinking long-held beliefs about technology ownership, vendor relationships, and how teams work together. Some leaders worry about losing control, while team members may be reluctant to let go of familiar tools and processes. In businesses where change moves slowly, even the most logical upgrade can can be met with skepticism or outright pushback.
Overcoming Resistance to Change
Think of how 8-tracks replaced albums, cassettes replaced 8-tracks, CDs replaced cassettes, and DVDs replaced CDs—only for all of them to be replaced by streaming media. Change (and hence, progress) is always difficult to accept, but it’s constant, relentless, and the only thing you can truly count on.
Success with composability starts with rethinking the goal—from adding tools to unifying the customer experience. Hradovich reiterated that "The first step is a mindset shift: stop thinking in terms of tools or channels and start thinking in terms of customers. From there, leaders should simplify rather than expand—map where data lives today, cut overlapping tools, and build around a single customer profile that every channel can tap into."
Legacy platforms weren’t built for easy integration. Connecting modern, API-first tools to outdated systems can require significant time, effort, and investment. Meanwhile, the shift to composability and AI puts a premium on technical skills—not just for IT, but for marketers as well. Many teams find themselves needing to upskill, hire, or rely more heavily on external partners to make the transition work.
The good news is, these challenges aren’t insurmountable. Clear communication about the benefits, involving stakeholders early, and starting with pilot projects can help build buy-in and momentum. Investing in training and prioritizing platforms that play well with others can ease the technical transition. Most importantly, leaders who frame composability as an enabler of innovation—not just a tech refresh—can help their teams see change as an opportunity, rather than a threat.
How to Get Started: Practical Steps for Marketing Leaders
To move from theory to action, marketing leaders need to rethink how they view their tech stacks—not just as collections of tools, but as dynamic systems with distinct roles and purposes. Riemersma explained that brands should make a clear distinction between the role of a stack as Factory versus Laboratory. "The Factory supports current revenue—start with the 80/20 rule: 20% of customer journeys bring 80% of the revenue. The Laboratory supports future revenue, enabling marketing to run experiments and growth hacks."
Before adopting new tools, businesses should focus on data hygiene. As Brady Lewis, senior director of AI innovation at fractional marketing firm Marketri, told CMSWire, "I sound like a broken record, but data is where you have to start. Would you buy a new Mercedes, fill the gas tank with whatever you have in your fridge, and expect it to get you to Disney World? I hope not. That new G-Wagon is useless without the right fuel. Your martech stack is useless without the right data. Focus on proper data hygiene before tools. Otherwise, you're just putting expired almond milk in your Mercedes."
Transitioning away from Frankenstacks isn’t about swapping out software for its own sake. "Start by reframing the goal,” said Cheung. “This isn’t about swapping tools—rather, it’s about designing for adaptability. Composable success starts with architecture, not software. Focus first on experience gaps. Where are customers or teams stuck? Build your stack around removing those frictions. Keep AI close to real workflows.”
Like the other experts we spoke with, Cheung suggested that brands treat integration as a product, not a project. “And remember, it’s not about more tools, it’s about smarter connections."
Making the move to a composable, AI-driven martech stack doesn’t have to be overwhelming. For marketing leaders, a thoughtful, phased approach—supported by leading analyst frameworks such as Gartner and Forrester, and the advice of industry experts—can turn the promise of composability into real, measurable progress.
- Start by mapping out every tool, platform, and integration your team relies on. Identify where data is flowing—and where it isn’t. This audit will reveal not just what you have, but how everything connects (or doesn’t).
- Look for the symptoms of a “Frankenstack." Manual data transfers, duplicated tools, disconnected customer experiences, or costly workarounds. Listen to your team—chances are, they know exactly where the bottlenecks and breakdowns are.
- Evaluate new platforms and vendors with composability in mind. Seek out API-first, modular solutions that make it easy to swap, scale, or integrate as your needs change. Prioritize partners who embrace openness and flexibility, not just feature lists.
- Don’t just plug in AI as an afterthought. Look for tools that use AI to power smarter connections, automate repetitive work, and deliver actionable insights. iPaaS, AI-enabled workflow automation, and composable CDPs can accelerate your journey.
- Finally, resist the urge to overhaul everything at once. Instead, tackle high-impact pain points first, run pilot programs, and build in phases. The goal isn’t a perfect stack, but a flexible one—ready to evolve with your business and your customers.
By taking these steps, marketing leaders can break free from Frankenstack frustrations and start building a stack that’s agile, intelligent, and truly fit for the future.
Yakkundi cautioned that when evaluating new solutions, brands should not be swayed by the sheer number of features. Instead, she advised leaders to focus on the ability to activate data wherever it resides, look for pre-defined API workflows (not just open-ended APIs), and choose partners that have proven they can deliver business outcomes.
Conclusion: Goodbye, Frankenstack in Martech
The era of Frankenstack marketing is ending. Composability—powered by modular design and AI—offers a flexible, future-ready foundation for martech. By building stacks that can adapt, connect, and scale, marketing leaders can finally move past fragmented tools and deliver pain-free customer experiences. The path forward isn’t about chasing perfection, but about choosing agility and integration—turning technology into a true driver of marketing success.
