Key Takeaways
Legacy platforms can’t support real-time, behavior-driven engagement at scale.
A modern data stack uses your warehouse or CDP as the source of truth for customer data.
Native cross-channel orchestration replaces siloed tools with a unified customer view.
AI must be built into the platform’s infrastructure — bolt-on solutions won’t deliver.
Composable architecture lets you activate data without ripping and replacing your stack.
Traditional marketing stacks were built for a different era — batch sends, static segments, and scheduled campaigns. Today’s customers expect brands to respond the moment intent signals, not hours or days later.
If your current platform can’t keep pace with those expectations, it’s time to rethink your data stack. Here’s how to evaluate martech solutions that deliver value todayand scale for tomorrow.
Why It’s Time to Rethink Your MarTech Stack
Legacy platforms were built for a bygone era, when marketing meant mass emails, basic segmentation, and static campaigns. Today’s tech-savvy consumers expect hyper-personalized experiences that feel seamless, not stitched together.
The martech landscape reflects this shift. According to chiefmartec:
The martech ecosystem has grown 100x since 2011
There are now 15,000+ solutions in the market
Nearly two-thirds (64%) of marketers we surveyed at Activate Summit 2025 reported sending the majority or entirety of their messages as one-size-fits-all sends. Only 6% were mostly moments-based, with less than 30% batch sends.
It’s not that marketers want to be stuck in the past. Their outdated platforms are holding them back:
Siloed or inaccessible data prevents a unified view of the customer
Manual workflows and technical bottlenecks slow down execution
Low engagement and high unsubscribe rates as a result of static sends
Inability to respond in real time to customer behavior and intent
A lack of tangible ROI from tech that overpromises and underdelivers
Modern marketing demands smarter, faster, and more scalable tools. It’s not just about ticking boxes off a feature checklist. It’s about activating real results and business outcomes.
How a Customer Engagement Platform Fits Into the Modern Data Stack
The modern data stack treats your data warehouse or customer data platform (CDP) as the single source of truth for customer information. Analytics, machine learning models, and business intelligence tools connect to this foundation.
A customer engagement platform like Iterable sits on the activation layer. We activate that trusted, governed data — using live behavioral signals to decide what to send, when to send it, and which channel will resonate — turning it into real-time, personalized experiences across email, SMS, push, in-app, and more.
This composable approach lets us activate your source of truth to power the real-time decisions that drive engagement.
5 Things to Look for When Evaluating MarTech Platforms
With so many tools and potential capabilities to choose from, selecting the right platform can feel paralyzing. How do you know what to prioritize?
Here are five factors that should be top of mind during your search:
1. Native Cross-Channel Orchestration: A True Cohesive Experience
The Problem: Many legacy tools were designed for a single channel, whether that’s email, mobile, or social media. This siloed view leads to fragmented messaging and customer experiences that feel disjointed.
Why It Matters: Customers don’t engage in silos. Brands that coordinate three or more channels see a 494% higher order rate than single-channel campaigns, according to Omnisend. Omnichannel shoppers are more valuable over time. If you want more valuable customers, you need a centralized hub for cross-channel orchestration.
What to Look For: Choose a platform that offers native support for all critical channels—email, SMS, mobile and web push, in-app messaging, WhatsApp, and more—within a single environment. Your solution should intelligently route messages to the right channel based on individual customer behavior and preferences, creating one seamless experience rather than six parallel ones.
Iterable Resource: Download The Marketer’s Guide to Cross-Channel Success to deliver personalized experiences that meet your customers where they are.
2. AI-Optimized Personalization and Automation — Not a Feature Add-On
“I believe that built-in AI is a strategic advantage in a martech platform…we‘re transitioning to a built-in AI martech world, but many of the current offerings are bolt-on AI, packaged in various ways by marketing teams.“
– Jon Goodman, President at Range Digital
The Problem: Too many martech providers have retrofitted AI onto legacy systems, essentially speeding up broken processes instead of rethinking them. Bolting on AI after the fact is not a transformation. It’s a patch.
Why It Matters: AI isn’t just about saving time or efficiency gains — done well, it drives growth. AI leaders that embed AI deeply achieve 1.7x higher revenue growth than laggards, according to BCG. But reaching that level requires deep integration of AI into your platform’s infrastructure. Basic genAI plugins won’t get you there.
What to Look For: Look for a platform built for AI from the start—with an architecture that activates large datasets and personalizes as behavior happens. Seek out prescriptive, conversational, and goal-based AI that helps you dynamically adjust your engagement strategies based on live customer behavior—not after-the-fact reports.
Iterable Resource: Download our checklist on unlocking the power of AI to discover optimization opportunities that foster team efficiencies.
Bonus: Nova Intelligence, our native AI layer, enables marketers to tap into generative and predictive AI to power more accurate and effective decision-making. Generative work is handled by Nova Agents, while forecasting capabilities like Predictive Audiences, part of Nova Intelligence, help identify high-value customers and churn risks before they disengage.
3. Composability: A Platform That Adapts to Your Existing Tech Stack
“Future-ready stacks are flexible, well-integrated, and built on strong data foundations with embedded AI, open architecture, and clear roadmaps. Success also hinges on scalability, governance, and user adoption.“
– , Head of Technology Strategy at Merkle
The Problem: Siloed systems and clunky, legacy integrations make it nearly impossible for marketers to activate the customer data they already have. Much of the customer data teams collect ends up sitting unused across disconnected tools.
Why It Matters: Your data is only as useful as your ability to act on it. If your martech platform can’t ingest and activate data from all sources—such as CRM, e-commerce, customer support, and analytics—you’re navigating without a map.
What to Look For: Choose a platform with an open, composable architecture that allows you to plug into your existing stack—without heavy engineering. Look for marketer-first tools that let you move quickly, using every data point to improve targeting and measurement.
A composable platform activates data from your warehouse or CDP — your source of truth — so every team can act on the same governed customer data.
Iterable Resource: Download our guide with Hightouch that explains why the future of martech is composable and how to build an agile, data-driven stack.
4. Predictable Scalability and Costs
The Problem: Many software vendors lure teams in with low upfront costs, only to introduce unforeseen data overage fees or maintenance costs that snowball over time. This lack of transparency derails even the most promising martech investments.
Why It Matters: Your platform should grow with you — without surprise bills. Unpredictable overage and maintenance costs erode ROI as data volume and complexity scale. You need a solution that can grow with your business and offers transparent cost structures to ensure long-term ROI.
What to Look For: Opt for a cloud-native solution with pricing that’s easy to predict and scale. Avoid platforms that nickel-and-dime you for data ingestion, extensions, or advanced segmentation logic. Your costs should be tied to business value—not arbitrary compute limits.
Iterable Resource: Download The Cross-Channel Marketing Platform Migration Guide to help evaluate and switch platforms with confidence.
5. Best-in-Class Customer Support and Community
“Predictive analytics and generative AI are delivering measurable value in customer insights and scalable content creation, while agentic AI is freeing up human resources by handling complex tasks. However, many clients struggle to realise value due to gaps in strategy, talent, and data readiness.“
– Adam Chandley, Head of Technology Strategy at Merkle
The Problem: Even the most advanced tools can fall flat without the right people and support behind them. Technical skill gaps and resource constraints mean that marketers often need help bridging the gap between vision and execution.
Why It Matters: 74% of companies have yet to show tangible value from their AI investments, according to BCG, and much of that loss is due to a lack of education and support. In fact, 67% of marketing professionals cite lack of education and training as the top barrier to AI adoption, according to the Marketing AI Institute. It’s not enough to spend money on new tools if you’re not going to invest in the right resources, whether it’s quality customer support, structured onboarding, or ongoing professional services.
What to Look For: Seek a platform that acts as a partner, not just a vendor—with onboarding guidance and hands-on customer support that is aligned with your objectives. The best solutions have thriving communities and offer workshops and product showcases to keep your team ahead of the curve.
Iterable Resource: We don’t believe in gate-keeping our community, so everyone is welcome to gain valuable insights and collaborate with industry peers in the Iterable Plaza. Come join us and start making connections!
The Iterable Difference
We built Iterable for the modern marketer — from cross-channel journeys and a native AI layer to composable, open data that activates your source of truth.
Here’s what sets us apart:
Journeys — Unified cross-channel orchestration through our Visual Journey Builder, coordinating email, SMS, push, in-app, and WhatsApp from a single studio
Nova Intelligence — Our native AI layer powers predictive and generative capabilities, including Nova Agents for autonomous workflow building and Predictive Audiences for identifying high-value customers
Campaigns — High-speed, high-precision execution at scale with dynamic templates and 1:1 personalization — no engineering tickets required
Composable, open data — Activate trusted data from your warehouse or CDP to power real-time decisions across every channel
FAQs About Migrating to a Modern MarTech Stack
1. Why Should I Replace My Current Marketing Automation Platform?
If your existing tools are keeping you stuck in one-size-fits-all mode with manual workflows, limited personalization, or siloed data, it’s time to make the shift to behavior-driven engagement. A modern martech solution can greatly enhance your brand’s agility, engagement, and ROI.
“The singular biggest challenge we see is underutilization of tools or redundancies across their entire Martech stack. Lack of utilization can be a symptom of something larger at play, including data access or lack of data integration that is needed.“
– , Director of Technical Solutions and Services at Shaw/Scott
2. What Are the Signs That My MarTech Stack Is Outdated?
The top signs that marketers have reported, according to our survey data, include fragmented or inconsistent data, which results in a lack of real-time personalization. This inability to personalize at scale ultimately leads to low engagement rates and negative brand sentiment.
“Clients also often underutilize their martech stack by focusing on producing more communication rather than analyzing and activating customer data to create great communication that actually delivers value.“
– , Co-Founder and CEO at Miltton
It’s critical to upgrade your martech stack before your business is outpaced by brands that have the tools to activate data in seconds—not hours or days.
“Features that drive efficiency while creating business value, especially those that handle large data volumes to automate highly granular, on-brand personalized offers, are strong indicators of future-ready martech.“
– Marten Tilosius, Co-Founder and CEO at Miltton
3. What’s the ROI of Switching to a Modern MarTech Platform?
According to BCG, AI leaders have achieved 1.5x higher revenue growth over the past three years than other companies.
“A marketer’s ROI for deploying new martech may look like faster-to-market campaign deployment with less lift on teams and an increase in percentage of utilized capabilities in the platform, but it could also be measured by higher deliverability and increased engagement across campaigns. ROI on martech can also look like better attribution for omnichannel. An over-reliance on last-touch attribution, despite standing up multi-channel journeys, is something we see a lot. While easier to set parameters to, this tunnel-vision view of attribution really limits the marketer from truly understanding what opportunities there are to act on with those raised hand moments.“
– Maile Kaulukukui, Director of Technical Solutions and Services at Shaw/Scott
To estimate the value a platform like Iterable can bring to your brand, try the Iterable Value Calculator.
4. What Happens to My Existing MarTech Tools? Do I Need to Rip and Replace Them?
No, a best-in-breed martech should adapt to and enhance your current tech stack. Look for composable solutions that integrate with your existing platforms rather than all-in-one marketing clouds that keep your customer data siloed and inaccessible.
“Robust, scalable, and comprehensive open REST APIs is the basis of a good tool and the vast majority (~80%) of martech platforms do not have sufficiently good APIs or interconnectivity––either because they can‘t interact with core pieces of the platform or they do not have the speed and rate limits necessary to operate in a modern high-scale environment.“
– Steven Aldrich, SVP, Marketing Services at Apply Digital
5. Can Non-Technical Marketers Use AI-Driven Platforms?
Absolutely. The best martech solutions are both built for marketers and loved by engineers. They remove bottlenecks by making the most complex decisions easy to execute for any marketing team.
“Built-in AI is considered table stakes in today‘s requirements, allowing marketers to go from 0 to 1 very quickly. Few companies have their own models that are ready for production therefore a built-in model allows organisations to leverage AI in a way that allows them to activate it.“
– Julien De Visscher, Managing Director at Human37
Make sure to adopt platforms that offer intuitive and conversational interfaces, drag-and-drop journey builders, and prescriptive, AI-powered guidance.
6. What Is a Modern Data Stack, and How Does a Customer Engagement Platform Fit Into It?
A modern data stack is an architecture where your data warehouse or CDP serves as the central, governed source of truth for customer information. Analytics tools, machine learning models, and operational systems all connect to this foundation.
A customer engagement platform sits on the activation layer — it takes the trusted data from your source of truth and turns it into real-time, personalized experiences across channels. The engagement platform activates that foundation, using live signals to power decisions about timing, channel, and content.
See Iterable in Action
Modern marketing requires a platform that activates your data foundation to power real-time, behavior-driven engagement across every channel.
Ready to see how Iterable can modernize your martech? Explore The New Era of Moments-Based Marketing to understand how leading brands are making the shift.
Or get in touch for a demo to see how our platform can help your team build better customer experiences. help your team build better customer experiences.