GTM maturity score
Reactive
Based on your inputs, your GTM operates primarily in the Reactive stage today.
Execution relies more on individual effort than on a connected, repeatable system. Many organizations remain in this stage longer than they expect. There may be variation across teams or regions, but the overall pattern suggests performance depends more on heroics than on aligned execution.
That’s fixable, and most teams can progress faster than they think.
Table of Contents
What this stage typically feels like day-to-day
Work moves, but it feels harder than it should.
Initiatives launch, yet adoption varies. Sellers receive input from multiple functions, often out of sequence. “Go find it” becomes the default operating model because guidance lives across documents, shared drives, chat messages, and inboxes.
Managers become the source of truth because the systems aren’t fully trusted. Sellers reconcile conflicting instructions from Marketing, Ops, Legal, Pricing, and Product teams to keep deals moving. Reporting conversations lean on anecdotes because dashboards aren’t consistently reliable.
AI tools may be in use, but without shared standards, learning stays local and execution varies.
You are working hard. But the engine isn’t fully working for you.
How Reactive shows up in your GTM engine
Reactive maturity creates fragmentation across the GTM engine.
People
Teams operate with limited shared context. Functions optimize for their own KPIs over shared commercial outcomes. Coaching depends on individual manager rigor, and trust in data is low, so opinions often replace shared insights. Success exists in pockets, rather than across the system.
Processes
Processes vary by region or team. There is no clear end-to-end view from marketing to sales to post-sale, creating messy handoffs, buyer friction, and inconsistent conversion. Enablement is reactive rather than embedded into workflow. Onboarding lacks structure and reinforcement.
Technology
Tools and data operate in silos. Each function selects systems independently to solve for immediate issues, resulting in fragmented workflows and inconsistent governance. CRM adoption varies. Visibility into what’s actually driving performance is limited. Content grows but is underutilized. AI experimentation is active but unstructured, increasing variability and compliance exposure.
