The early signs of traction in an AI company can be intoxicating. A handful of customers leaning in, deals moving quickly, urgency in every conversation. It feels like validation. In most cases, it is not. Mike Peroni has spent twenty years designing and scaling go-to-market (GTM) systems for early-stage and global enterprise technology companies. Most recently, he architected ETQ’s international expansion and developed the strategic positioning that led to a $1.2 billion acquisition. What he has learned across every stage of that work is that the distance between a promising signal and a truly scalable business is where most companies quietly lose ground. Closing that gap, Peroni argues, is intentional work.
Market Fit Scales. Market Signals Do Not
Early traction can look convincing and still be deeply misleading. The signal might be too narrow, concentrated in a customer profile that does not represent a real segment. It might be fragmented across too many different types of buyers, obscuring what the product actually does well. Or it might be dependent on a condition that simply cannot be repeated.
Peroni points to a content tracking and monetization platform he works with as a clear illustration. Customers were engaged. The team was building features in response. On the surface, it looked like product-market fit. But no one had tested whether those features reflected broader market needs or just the preferences of a few individual accounts.
His team began testing positioning and messaging with new prospects and tracked patterns across deals rather than within individual relationships. The signal was real, but highly fragmented. That analysis led the company to identify the specific segments where the problem, the product, and the value delivered were well aligned. That distinction, Peroni emphasizes, is what moves a company from signal to fit. Testing frequently in the early stage, and more deliberately over time, is not optional. It is the core of the work, especially in new AI categories where the market itself is still forming.
The Right System for the Right Stage
One of the most consistent mistakes Peroni sees is applying the wrong operational model to the stage a company is actually in. Early-stage companies do not need a mature sales process. They need the latitude to discover new value, to turn an insight from one call into a test on the next. Discipline applied too early kills the learning.
In the later stage, internationally distributed teams face the opposite challenge. They need consistency, shared definitions, and rigour inside every deal. At ETQ, Peroni built a unified commercial framework globally, standardized definitions regionally, and gave teams the tools to test assumptions about the deal stage directly with customers. The system centered on value selling, deal prioritization, and predictability at scale. The principle is direct: early-stage systems should prioritize learning and discovering fit, while later-stage systems should prioritize discipline, alignment, and execution. Getting this right is an operational decision, not a theoretical one.
Feedback Loops that Grow with the Company
No revenue system is static, and no feedback loop designed for 20 customers will serve a company with 200. The question is whether the organization has built the mechanism to evolve alongside the business. Early-stage feedback loops are about speed. Every pilot, every conversion, every lost deal tests assumptions and refines the message. The risk at this stage is failing to capture those insights in any structured way, which means the same lessons get relearned at real cost.
As companies scale, those loops must become more sophisticated. At ETQ, this meant standardizing definitions, tracking key deal behaviors, and embedding tests into the qualification framework so that assumptions were being validated consistently across a distributed team. The result was an organization that could grow without losing clarity about what was actually working.
Whether a company is in an early rapid-learning phase or a later stage of disciplined execution, the goal of a feedback loop remains the same: turn insight into predictable, scalable revenue. The gap between early traction and real scale is not closed by moving faster. It is closed by staying intentional about what the market is actually saying, building systems that match where the company is today, and designing the mechanisms that will carry it to where it needs to go.
Follow Mike Peroni on LinkedIn or visit ETQ for more insights.
