Your company probably has the right data. It's just scattered across six different platforms that were never meant to talk to each other.
This is the quiet dysfunction behind many growth teams. It didn't happen because of bad decisions. It happened because each department did what made sense at the time. Marketing picked HubSpot. Sales adopted Salesforce. Finance standardized on NetSuite. Product moved into Jira. And IT approved them all.
The result: dozens of tools that don't communicate, and teams that reflect the same fragmentation. Not because people don't want to work together, but because their systems make alignment structurally difficult.
The Real Cost Is Hidden
The licensing fees are visible on a spreadsheet. The real cost isn't. It shows up in the Monday morning meeting where your CMO quotes one CAC and your CFO quotes another, from the same data, about the same customers, using the same time period. Both are right according to their tool. Neither is useful for making decisions.
When your systems define different things as a "customer," or count differently by default, or use different attribution windows, you don't have a data problem. You have an architecture problem. And you can't solve an architecture problem by adding another dashboard.
The trap looks like this: buy the category leader, force your team to adopt their workflow, wonder why adoption fails six months later, then buy another tool to compensate. Each new tool adds to the stack but doesn't reduce the underlying fragmentation.
What's Actually Changing
The companies getting this right aren't buying fewer tools. They're building a smarter layer above them.
The shift is from asking "what can this tool do?" to "what do we need done?" That reframe matters. It puts the business logic first and lets the tools serve the workflow instead of defining it.
An agentic layer, meaning software that understands your business definitions and maps them across all your systems, is the practical answer here. Imagine something that pulls from Salesforce, HubSpot, and your data warehouse simultaneously, applies your definitions rather than the vendor's, and delivers the same number to your CMO and CFO automatically.
This isn't futuristic. In my view, it's where operationally mature growth teams are headed. They're not replacing their tools. They're making the tools disappear into the process, invisible in the way that good infrastructure always is.
The Question Worth Asking
Every tool your company has adopted was justified by what it could do. The better question, and one that often goes unasked, is whether your tools are actively preventing the kind of alignment that drives growth.
If your CMO and CFO are looking at different numbers, the problem isn't the people. It's the architecture. Fix the architecture, and you remove an entire category of friction that slows down decisions, erodes trust, and forces smart people to spend time reconciling data instead of using it.
The winners won't be companies with the most tools or the fewest. They'll be companies whose tools have fully disappeared into how they operate.
David Manela is co-founder of Exactius, a growth and data science company. Follow him on LinkedIn for more frameworks on growth, marketing, and capital allocation.
David Manela
David Manela is the founder of Exactius and creator of the Growth Operating System — a framework for deploying capital-efficient, compounding growth inside scaling companies.
FAQ
Frequently asked
What does "Don't Let Tools Shape You" mean for growth teams?
It means business definitions and workflows should come first, with software chosen and configured to serve them. The author argues that when each department adopts its own platform, the tools end up dictating how teams define customers, count conversions and attribute revenue. His proposed fix is a layer above the stack that applies one set of company definitions across every system, so leaders work from the same numbers.
Why do marketing and finance leaders report different CAC from the same data?
Different platforms often define a customer differently, count events differently by default and apply different attribution windows. The author argues this is an architecture problem: each figure can be correct inside its own tool while the two still disagree. In his view, adding another dashboard does not resolve it. Agreeing on shared definitions and applying them across every system does.
How much of their martech stack do companies actually use?
Less than half, according to Gartner. Its 2025 Marketing Technology Survey reports that only 49% of martech tools are actively used. An earlier Gartner survey of 405 marketing leaders, run in May and June 2023, measured capability use instead. It found organizations used an average of 33% of their martech stack's capabilities, down from 42% in 2022 and 58% in 2020.
What does poor data quality cost a business?
Gartner research from 2020 estimates that poor data quality costs organizations at least $12.9 million a year on average. Conflicting definitions across systems can contribute to the problem. When platforms count customers or conversions differently, teams spend time reconciling figures and leaders lose confidence in the numbers they rely on to make decisions.
How do you audit a martech stack?
Gartner's guidance on martech audits starts with comparing each tool's cost against its utilization data to spot low adoption or redundant capabilities. It also recommends mapping the whole martech ecosystem with usage levels and checking whether each tool meets the objective it was bought for. The result gives a factual basis for deciding which tools to keep or retire before buying more.
What is a semantic layer, and how does it relate to the agentic layer the author describes?
A semantic layer is a central place where business metrics are defined once and then served to every downstream tool. dbt Labs' documentation explains that when metric definitions are centralized, a change made in one place is refreshed everywhere the metric is used. The author's agentic layer goes further, describing software that applies company definitions across systems automatically. That framing is his projection of where tooling is heading.
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