The MarTech stack reckoning: why CMOs are cutting tools and gaining power

In 2023, Gartner reported that CMOs were utilizing only 33% of their MarTech stack's full capabilities, down from 58% just two years earlier. Meanwhile, average MarTech budgets had consumed 26% of total marketing spend. Think about that for a moment: a quarter of your budget allocated to tools your team is using at one-third capacity. If that were a factory floor, the board would have intervened years ago. The MarTech landscape, which Scott Brinker's annual supergraphic now counts at over 11,000 solutions, has quietly become one of the most expensive sources of organizational dysfunction in modern marketing.

The irony is that this explosion of capability was supposed to make CMOs more powerful. In many organizations, it has done the opposite, creating dependency on IT, fragmenting customer data across incompatible platforms, and turning marketing teams into tool administrators rather than strategy architects.

The great MarTech consolidation is already underway

The market is correcting itself in several visible ways. First, the major platform players, Salesforce, Adobe, HubSpot, and Oracle, are aggressively expanding their native ecosystems to reduce the need for point solutions. Adobe's acquisition of Marketo and its continued investment in Adobe Experience Platform is a direct bet that enterprise CMOs will pay a premium for integrated workflows over best-of-breed fragmentation. HubSpot, traditionally a mid-market player, is moving upstream with its AI-powered tools and CRMCRMCustomer Relationship Management: software and strategy to manage and analyse customer interactions throughout their lifecycle.View full definition → integrations, threatening the lower end of the enterprise stack.

Second, AI is accelerating consolidation from the inside. Tools that previously required separate vendors, social listening, content generation, campaign optimization, attribution modelingattribution modelingAttribution modeling is the method of assigning credit for a conversion across the marketing touchpoints a customer interacted with before buying or signing up.View full definition →, are now being absorbed into unified platforms powered by large language models. Jasper, once celebrated as a standalone AI writing assistant, is being squeezed by the native AI features in Notion, HubSpot, and Salesforce's Einstein suite. When the incumbent platform adds "good enough" AI functionality, the specialist tool loses its budget justification overnight.

Third, privacy regulations, GDPR, CCPA, and the ongoing deprecation of third-party cookies, have exposed the structural weakness of stacks built on fragmented data collection. CMOs who invested heavily in third-party datathird-party dataData purchased from external aggregators, collected from audiences you don't own. It is bought or licensed rather than gathered through your own direct relationships.View full definition → tools are now facing a forced rebuild, and many are seizing the opportunity to rationalize rather than simply replace.

The net result: enterprise CMOs are conducting formal MarTech audits at a pace not seen since the post-pandemic budget freezes of 2022. The average organization is cutting between 15 and 30 percent of its active tools in these reviews.

What this means for the CMO

The rationalization wave creates both a strategic opportunity and a political risk that CMOs need to navigate with precision.

Reframe the stack as a business architecture decision

The worst mistake a CMO can make right now is treating MarTech rationalization as a cost-cutting exercise delegated to a marketing ops manager. Stack architecture is now a C-suite conversation. The choice between, say, building on Salesforce Data Cloud versus a composable CDPCDPA Customer Data Platform unifies customer data from all sources into persistent, actionable profiles that other systems can use.View full definition → from Segment directly shapes how the company can personalize at scale, how quickly it can respond to market changes, and how cleanly data flows into finance and product teams. CMOs who let IT or procurement drive this decision will spend the next three years fighting for workarounds.

Build for the first-party datafirst-party dataData collected directly from your own customers and prospects through your own channels: your most reliable and privacy-compliant source.View full definition → imperative

Every tool evaluation should now pass a single filter: does this strengthen or dilute our first-party data strategy? Companies like Marriott and Nike have demonstrated that owned data ecosystems, loyalty programs, apps, direct commerce, generate compounding returns that rented audience tools simply cannot match. CMOs should audit which tools are actively building their customer data asset and which are creating extraction points that leak value to third parties.

Invest in fewer integrations, not more tools

The hidden cost of MarTech isn't the licensing fee, it's the integration debt. Each connection between platforms requires maintenance, creates latency, and introduces failure points. A leaner, more integrated stack with high utilization consistently outperforms a sprawling ecosystem of underused specialists. Pragmatically, this means developing a formal "integration tax" framework: any new tool proposal must account for the full cost of connecting it to existing systems, not just the subscription price.

Develop internal MarTech fluency as a leadership competency

CMOs who rely entirely on their technology teams to evaluate and operate the stack are ceding strategic control. The most effective marketing leaders, think Sridhar Ramaswamy's data-drivendata-drivenAn approach where decisions are systematically informed by data analysis rather than intuition alone.View full definition → approach at Neeva or Ann Lewnes' Adobe transformation, are deeply conversant in how their platforms work, where data lives, and what the architecture enables or prevents. This doesn't mean coding; it means understanding data flows, APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.View full definition → logic, and model training well enough to make consequential decisions without waiting for a technical translation.

Key Takeaways

• Conduct a utilization audit, not just a cost audit. Before adding any new tool to the stack, measure actual feature utilization across your existing platforms. Low utilization is almost always an organizational problem before it's a technology problem, and buying more tools won't solve it.
• Define your platform core and protect it aggressively. Identify the two or three platforms that anchor your customer data, campaign execution, and measurement. Everything else should be evaluated for strategic fit, not vendor enthusiasm or trend-chasing.
• Make AI integration a vendor selection criterion, not a bonus feature. Evaluate how deeply AI capabilities are embedded in your core platforms rather than purchasing standalone AI tools. Native AI reduces integration complexity and improves data access, both critical for performance.
• Treat MarTech decisions as talent decisions. The stack you choose determines what skills you need on your team and what skills become obsolete. A Salesforce-centric organization needs different expertise than a composable, API-first architecture. Align stack evolution with your three-year hiring roadmap.

---

The CMOs who will define the next decade of marketing are not the ones with the most sophisticated stacks, they are the ones who built the most purposeful ones. The question worth sitting with is not "what technology are we missing?" but "what would we be capable of if we mastered what we already have?" Your stack is either an engine or an anchor. Right now, for most organizations, it is both, and that is a leadership problem before it is a technology problem.