In the 2025 MarTech Replacement Survey, 59.9% of respondents said they'd swapped out a marketing technology application in the previous year. That's down from 69.8% at the 2022 peak. CRM replacements hit their lowest level in the survey's history. Marketing automation replacements dropped from 31.1% in 2024 to 19.4% in 2025. Email platform replacements fell from 24.3% to 13.7%.
Replacement is slowing. Fast.
But among those who did replace something, 62.9% said their total application count increased over the past year. About 21% added three to five tools. Only 22.6% saw their stack shrink. The pattern isn't swap-and-simplify. It's layer-and-accumulate.
The operating model nobody designed
The old replacement cycle assumed a clean trade: one platform out, one in. The current pattern looks different. Organizations keep their core systems (CRM, marketing automation, email infrastructure) locked in place and bolt on specialized point solutions around the edges. SEO tools, analytics platforms, AI features, project management apps. Each addition is comparatively frictionless. No migration cost, no retraining, no workflow redesign. Just another API connection and another monthly invoice.
This makes perfect sense at the individual decision level. Replacing a marketing automation platform is a six-figure project with months of disruption. Adding a $200/month SEO analytics tool takes an afternoon.
The problem compounds at the stack level. A Gartner-cited report found that marketers used only about 33% of their martech stack's capability in 2023, down from 42% in 2022 and 58% in 2020. That decline tracks directly with sprawl: more tools, less mastery of each one, more integration points nobody owns.
Scott Brinker, in a March 2026 research report with Databricks, described the shift toward "composable" architectures where apps and AI agents plug into a universal data layer. "This isn't a rip-and-replace proposition," he wrote. "It's a three-to-five-year architectural vision." That framing is honest about the timeline. It's also honest about the implication: for most teams, the next several years will be spent managing growing complexity, not reducing it.
Where this hits pipeline
For demand gen operators, the mess isn't abstract. It shows up in specific, measurable ways.
Attribution breaks when data lives in disconnected systems that don't share a common identifier. Lead routing gets unreliable when CRM and marketing automation records diverge. Experimentation slows down because standing up a test requires stitching data from three platforms instead of querying one. Creative fatigue analysis becomes guesswork when ad performance data sits in one tool and conversion data sits in another.
The 2025 survey backs this up: integration capabilities and data centralization were among the top selection criteria for replacement platforms, cited by 37.1% and 42.7% of respondents respectively. Teams know the problem. They keep adding tools anyway, because the alternative (a full platform migration) is expensive and risky, and because composable architectures make layering feel safe.
Meanwhile, AI is making this worse, not better. Every new AI feature or agent introduced to the stack creates its own data dependencies, its own integration requirements, its own failure modes. MarTech.org has noted that AI-driven tool replacement is increasing stack churn and can worsen integration complexity. The martech ecosystem hit 15,384 solutions in 2025 (up 9% from 2024, per Factors.ai), even as 1,211 solutions were removed through acquisition or shutdown. Churn is high on both ends.
What actually helps (and what doesn't)
Consolidation sounds like the answer. Sometimes it is. But collapsing five tools into one suite doesn't fix a broken data model or unclear ownership of integration points. Complexity can persist inside a single platform just as easily as across twenty.
The more productive framing: treat the stack as an operating system that needs governance, not just procurement. That means three things.
- Integration ownership. Someone (RevOps, marketing ops, a named human) owns every connector, every data sync, every API dependency. If nobody owns the integration, the integration is already broken.
- Utilization audits before new purchases. If the team is using 33% of existing capability, the next dollar spent on a new tool has a worse expected ROI than the next dollar spent on training or configuration of what's already in the stack.
- Phased retirement, not just phased adoption. Every tool added should trigger a question: what does this replace, and when does the old tool get shut down? No answer, no purchase.
Best-of-breed stacks can still work for B2B SaaS teams, but only when interoperability is designed intentionally. Fewer tools isn't always the right goal. Fewer unowned integrations is.
The real constraint
Net-new software purchases fell 17% year over year in 2023, per Vendr data cited by ZoomInfo. Average B2B SaaS sales cycles stretched from 33 days in 2020 to 43 days overall, and 56 days for enterprises with 1,000+ employees. Budget scrutiny is real. ROI scrutiny is real. And yet stacks keep growing.
That tension won't resolve by adding another tool or by pretending a suite migration will fix everything. It resolves by treating the stack like infrastructure: something that requires an operating model, clear ownership, and the discipline to retire what you aren't using before you buy what you think you need. The 33% utilization number from Gartner isn't a technology problem. It's an organizational one. And organizational problems don't get solved with another vendor contract.
